7632 lines
964 KiB
Plaintext
7632 lines
964 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(5,) (5, 3)\n",
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"(1000, 1) (1000, 1000)\n"
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]
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}
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],
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"source": [
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"import vectorbt as vbt\n",
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"from vectorbt.portfolio.enums import *\n",
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"\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"from numba import njit\n",
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"from datetime import datetime, timedelta\n",
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"\n",
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"seed = 42\n",
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"\n",
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"price = pd.Series([1., 2., 3., 4., 5.], index=pd.Index([\n",
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" datetime(2020, 1, 1),\n",
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" datetime(2020, 1, 2),\n",
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" datetime(2020, 1, 3),\n",
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" datetime(2020, 1, 4),\n",
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" datetime(2020, 1, 5)\n",
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"]))\n",
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"price_wide = price.vbt.tile(3, keys=['a', 'b', 'c'])\n",
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"print(price.shape, price_wide.shape)\n",
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"\n",
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"big_price = pd.DataFrame(np.random.uniform(0.9, 1.1, size=(1000,)))\n",
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"big_price.index = [datetime(2018, 1, 1) + timedelta(days=i) for i in range(1000)]\n",
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"big_price_wide = big_price.vbt.tile(1000)\n",
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"print(big_price.shape, big_price_wide.shape)\n",
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"\n",
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"# Disable caching for performance testing\n",
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"# NOTE: Expect waterfall of executions, since some attributes depend on other attributes \n",
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"# that have to be calculated again and again\n",
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"vbt.settings.caching['enabled'] = False\n",
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"vbt.settings.portfolio['attach_call_seq'] = True"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## from_orders"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"order_size = pd.Series([np.inf, -np.inf, np.nan, np.inf, -np.inf], index=price.index)\n",
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"order_size_wide = order_size.vbt.tile(3, keys=['a', 'b', 'c'])\n",
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"\n",
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"big_order_size = pd.DataFrame.vbt.empty((1000,), 1, dtype=np.float64)\n",
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"big_order_size.iloc[1::2] = -1\n",
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"big_order_size_wide = big_order_size.vbt.tile(1000)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 46,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"2.24 ms ± 179 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(big_price, big_order_size, init_cash=np.inf)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"67 ms ± 2.3 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(big_price_wide, big_order_size_wide, init_cash=np.inf)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"64.3 ms ± 1.05 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.repeat(np.arange(500), 2))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"65.9 ms ± 1.68 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.repeat(np.arange(500), 2), cash_sharing=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"71.7 ms ± 510 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, call_seq=CallSeqType.Auto)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"66.3 ms ± 285 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.full(1000, 0))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"63.7 ms ± 728 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.full(1000, 0), cash_sharing=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"68.3 ms ± 443 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit vbt.Portfolio.from_orders(\\\n",
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" big_price_wide, big_order_size_wide, init_cash=np.inf, \\\n",
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" group_by=np.full(1000, 0), cash_sharing=True, call_seq=CallSeqType.Auto)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {},
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"outputs": [],
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"source": [
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"def test_per_direction(price=price, size=order_size, **kwargs):\n",
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" print('Both')\n",
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" try:\n",
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" portfolio = vbt.Portfolio.from_orders(price, size, direction='both', **kwargs)\n",
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" print(portfolio.orders.records)\n",
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" except Exception as e:\n",
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" print(e)\n",
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" print('LongOnly')\n",
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" try:\n",
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" portfolio = vbt.Portfolio.from_orders(price, size, direction='longonly', **kwargs)\n",
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" print(portfolio.orders.records)\n",
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" except Exception as e:\n",
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" print(e)\n",
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" print('ShortOnly')\n",
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" try:\n",
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" portfolio = vbt.Portfolio.from_orders(price, size, direction='shortonly', **kwargs)\n",
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" print(portfolio.orders.records)\n",
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" except Exception as e:\n",
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" print(e)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"All\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 0\n",
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"1 1 1 0 200.0 2.0 0.0 1\n",
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"2 2 3 0 100.0 4.0 0.0 0\n",
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"LongOnly\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 0\n",
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"1 1 1 0 100.0 2.0 0.0 1\n",
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"2 2 3 0 50.0 4.0 0.0 0\n",
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"3 3 4 0 50.0 5.0 0.0 1\n",
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"ShortOnly\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 1\n",
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"1 1 1 0 100.0 2.0 0.0 0\n"
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]
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}
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],
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"source": [
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"test_per_direction()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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||
"metadata": {},
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||
"outputs": [
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{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
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"All\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 0\n",
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||
"1 1 1 0 200.0 2.0 0.0 1\n",
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||
"2 2 3 0 100.0 4.0 0.0 0\n",
|
||
"3 3 0 1 100.0 1.0 0.0 0\n",
|
||
"4 4 1 1 200.0 2.0 0.0 1\n",
|
||
"5 5 3 1 100.0 4.0 0.0 0\n",
|
||
"6 6 0 2 100.0 1.0 0.0 0\n",
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||
"7 7 1 2 200.0 2.0 0.0 1\n",
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||
"8 8 3 2 100.0 4.0 0.0 0\n",
|
||
"LongOnly\n",
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||
" id idx col size price fees side\n",
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||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 100.0 2.0 0.0 1\n",
|
||
"2 2 3 0 50.0 4.0 0.0 0\n",
|
||
"3 3 4 0 50.0 5.0 0.0 1\n",
|
||
"4 4 0 1 100.0 1.0 0.0 0\n",
|
||
"5 5 1 1 100.0 2.0 0.0 1\n",
|
||
"6 6 3 1 50.0 4.0 0.0 0\n",
|
||
"7 7 4 1 50.0 5.0 0.0 1\n",
|
||
"8 8 0 2 100.0 1.0 0.0 0\n",
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"9 9 1 2 100.0 2.0 0.0 1\n",
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"10 10 3 2 50.0 4.0 0.0 0\n",
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"11 11 4 2 50.0 5.0 0.0 1\n",
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"ShortOnly\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 1\n",
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"1 1 1 0 100.0 2.0 0.0 0\n",
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"2 2 0 1 100.0 1.0 0.0 1\n",
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"3 3 1 1 100.0 2.0 0.0 0\n",
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"4 4 0 2 100.0 1.0 0.0 1\n",
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"5 5 1 2 100.0 2.0 0.0 0\n"
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]
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}
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],
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"source": [
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"test_per_direction(price=price_wide)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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||
"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"All\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 0\n",
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"1 1 0 1 100.0 1.0 0.0 1\n",
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"LongOnly\n",
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" id idx col size price fees side\n",
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"0 0 0 0 100.0 1.0 0.0 0\n",
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"ShortOnly\n",
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" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 1\n"
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]
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||
}
|
||
],
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||
"source": [
|
||
"test_per_direction(size=[[np.inf, -np.inf]])"
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||
]
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||
},
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||
{
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||
"cell_type": "code",
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||
"execution_count": 52,
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||
"metadata": {},
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||
"outputs": [],
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"source": [
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"order_size_one = pd.Series([1, -1, np.nan, 1, -1], index=price.index)"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 53,
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||
"metadata": {},
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||
"outputs": [
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||
{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"All\n",
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||
" id idx col size price fees side\n",
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||
"0 0 0 0 99.009901 1.01 0.0 0\n",
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"1 1 1 0 198.019802 2.02 0.0 1\n",
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"2 2 3 0 99.009901 4.04 0.0 0\n",
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"LongOnly\n",
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" id idx col size price fees side\n",
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"0 0 0 0 99.009901 1.01 0.0 0\n",
|
||
"1 1 1 0 99.009901 2.02 0.0 1\n",
|
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"2 2 3 0 49.504950 4.04 0.0 0\n",
|
||
"3 3 4 0 49.504950 5.05 0.0 1\n",
|
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"ShortOnly\n",
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||
" id idx col size price fees side\n",
|
||
"0 0 0 0 99.009901 1.01 0.0 1\n",
|
||
"1 1 1 0 99.009901 2.02 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(price=price * 1.01)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 54,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.1 0\n",
|
||
"5 5 1 1 1.0 2.0 0.2 1\n",
|
||
"6 6 3 1 1.0 4.0 0.4 0\n",
|
||
"7 7 4 1 1.0 5.0 0.5 1\n",
|
||
"8 8 0 2 1.0 1.0 1.0 0\n",
|
||
"9 9 1 2 1.0 2.0 2.0 1\n",
|
||
"10 10 3 2 1.0 4.0 4.0 0\n",
|
||
"11 11 4 2 1.0 5.0 5.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.1 0\n",
|
||
"5 5 1 1 1.0 2.0 0.2 1\n",
|
||
"6 6 3 1 1.0 4.0 0.4 0\n",
|
||
"7 7 4 1 1.0 5.0 0.5 1\n",
|
||
"8 8 0 2 1.0 1.0 1.0 0\n",
|
||
"9 9 1 2 1.0 2.0 2.0 1\n",
|
||
"10 10 3 2 1.0 4.0 4.0 0\n",
|
||
"11 11 4 2 1.0 5.0 5.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 0 1.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1.0 4.0 0.0 1\n",
|
||
"3 3 4 0 1.0 5.0 0.0 0\n",
|
||
"4 4 0 1 1.0 1.0 0.1 1\n",
|
||
"5 5 1 1 1.0 2.0 0.2 0\n",
|
||
"6 6 3 1 1.0 4.0 0.4 1\n",
|
||
"7 7 4 1 1.0 5.0 0.5 0\n",
|
||
"8 8 0 2 1.0 1.0 1.0 1\n",
|
||
"9 9 1 2 1.0 2.0 2.0 0\n",
|
||
"10 10 3 2 1.0 4.0 4.0 1\n",
|
||
"11 11 4 2 1.0 5.0 5.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, fees=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 55,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.1 0\n",
|
||
"5 5 1 1 1.0 2.0 0.1 1\n",
|
||
"6 6 3 1 1.0 4.0 0.1 0\n",
|
||
"7 7 4 1 1.0 5.0 0.1 1\n",
|
||
"8 8 0 2 1.0 1.0 1.0 0\n",
|
||
"9 9 1 2 1.0 2.0 1.0 1\n",
|
||
"10 10 3 2 1.0 4.0 1.0 0\n",
|
||
"11 11 4 2 1.0 5.0 1.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.1 0\n",
|
||
"5 5 1 1 1.0 2.0 0.1 1\n",
|
||
"6 6 3 1 1.0 4.0 0.1 0\n",
|
||
"7 7 4 1 1.0 5.0 0.1 1\n",
|
||
"8 8 0 2 1.0 1.0 1.0 0\n",
|
||
"9 9 1 2 1.0 2.0 1.0 1\n",
|
||
"10 10 3 2 1.0 4.0 1.0 0\n",
|
||
"11 11 4 2 1.0 5.0 1.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 0 1.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1.0 4.0 0.0 1\n",
|
||
"3 3 4 0 1.0 5.0 0.0 0\n",
|
||
"4 4 0 1 1.0 1.0 0.1 1\n",
|
||
"5 5 1 1 1.0 2.0 0.1 0\n",
|
||
"6 6 3 1 1.0 4.0 0.1 1\n",
|
||
"7 7 4 1 1.0 5.0 0.1 0\n",
|
||
"8 8 0 2 1.0 1.0 1.0 1\n",
|
||
"9 9 1 2 1.0 2.0 1.0 0\n",
|
||
"10 10 3 2 1.0 4.0 1.0 1\n",
|
||
"11 11 4 2 1.0 5.0 1.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, fixed_fees=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 56,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.1 0.0 0\n",
|
||
"5 5 1 1 1.0 1.8 0.0 1\n",
|
||
"6 6 3 1 1.0 4.4 0.0 0\n",
|
||
"7 7 4 1 1.0 4.5 0.0 1\n",
|
||
"8 8 0 2 1.0 2.0 0.0 0\n",
|
||
"9 9 1 2 1.0 0.0 0.0 1\n",
|
||
"10 10 3 2 1.0 8.0 0.0 0\n",
|
||
"11 11 4 2 1.0 0.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.1 0.0 0\n",
|
||
"5 5 1 1 1.0 1.8 0.0 1\n",
|
||
"6 6 3 1 1.0 4.4 0.0 0\n",
|
||
"7 7 4 1 1.0 4.5 0.0 1\n",
|
||
"8 8 0 2 1.0 2.0 0.0 0\n",
|
||
"9 9 1 2 1.0 0.0 0.0 1\n",
|
||
"10 10 3 2 1.0 8.0 0.0 0\n",
|
||
"11 11 4 2 1.0 0.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 0 1.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1.0 4.0 0.0 1\n",
|
||
"3 3 4 0 1.0 5.0 0.0 0\n",
|
||
"4 4 0 1 1.0 0.9 0.0 1\n",
|
||
"5 5 1 1 1.0 2.2 0.0 0\n",
|
||
"6 6 3 1 1.0 3.6 0.0 1\n",
|
||
"7 7 4 1 1.0 5.5 0.0 0\n",
|
||
"8 8 0 2 1.0 0.0 0.0 1\n",
|
||
"9 9 1 2 1.0 4.0 0.0 0\n",
|
||
"10 10 3 2 1.0 0.0 0.0 1\n",
|
||
"11 11 4 2 1.0 10.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, slippage=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 57,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.0 0\n",
|
||
"5 5 1 1 1.0 2.0 0.0 1\n",
|
||
"6 6 3 1 1.0 4.0 0.0 0\n",
|
||
"7 7 4 1 1.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.0 0\n",
|
||
"5 5 1 1 1.0 2.0 0.0 1\n",
|
||
"6 6 3 1 1.0 4.0 0.0 0\n",
|
||
"7 7 4 1 1.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 0 1.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1.0 4.0 0.0 1\n",
|
||
"3 3 4 0 1.0 5.0 0.0 0\n",
|
||
"4 4 0 1 1.0 1.0 0.0 1\n",
|
||
"5 5 1 1 1.0 2.0 0.0 0\n",
|
||
"6 6 3 1 1.0 4.0 0.0 1\n",
|
||
"7 7 4 1 1.0 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, min_size=[[0., 1., 2.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 58,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 0\n",
|
||
"1 1 1 0 0.5 2.0 0.0 1\n",
|
||
"2 2 3 0 0.5 4.0 0.0 0\n",
|
||
"3 3 4 0 0.5 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.0 0\n",
|
||
"5 5 1 1 1.0 2.0 0.0 1\n",
|
||
"6 6 3 1 1.0 4.0 0.0 0\n",
|
||
"7 7 4 1 1.0 5.0 0.0 1\n",
|
||
"8 8 0 2 1.0 1.0 0.0 0\n",
|
||
"9 9 1 2 1.0 2.0 0.0 1\n",
|
||
"10 10 3 2 1.0 4.0 0.0 0\n",
|
||
"11 11 4 2 1.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 0\n",
|
||
"1 1 1 0 0.5 2.0 0.0 1\n",
|
||
"2 2 3 0 0.5 4.0 0.0 0\n",
|
||
"3 3 4 0 0.5 5.0 0.0 1\n",
|
||
"4 4 0 1 1.0 1.0 0.0 0\n",
|
||
"5 5 1 1 1.0 2.0 0.0 1\n",
|
||
"6 6 3 1 1.0 4.0 0.0 0\n",
|
||
"7 7 4 1 1.0 5.0 0.0 1\n",
|
||
"8 8 0 2 1.0 1.0 0.0 0\n",
|
||
"9 9 1 2 1.0 2.0 0.0 1\n",
|
||
"10 10 3 2 1.0 4.0 0.0 0\n",
|
||
"11 11 4 2 1.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 1\n",
|
||
"1 1 1 0 0.5 2.0 0.0 0\n",
|
||
"2 2 3 0 0.5 4.0 0.0 1\n",
|
||
"3 3 4 0 0.5 5.0 0.0 0\n",
|
||
"4 4 0 1 1.0 1.0 0.0 1\n",
|
||
"5 5 1 1 1.0 2.0 0.0 0\n",
|
||
"6 6 3 1 1.0 4.0 0.0 1\n",
|
||
"7 7 4 1 1.0 5.0 0.0 0\n",
|
||
"8 8 0 2 1.0 1.0 0.0 1\n",
|
||
"9 9 1 2 1.0 2.0 0.0 0\n",
|
||
"10 10 3 2 1.0 4.0 0.0 1\n",
|
||
"11 11 4 2 1.0 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, max_size=[[0.5, 1., np.inf]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 59,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 1 1 1.0 2.0 0.0 1\n",
|
||
"5 5 3 1 1.0 4.0 0.0 0\n",
|
||
"6 6 4 1 1.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1.0 2.0 0.0 1\n",
|
||
"2 2 3 0 1.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1.0 5.0 0.0 1\n",
|
||
"4 4 3 1 1.0 4.0 0.0 0\n",
|
||
"5 5 4 1 1.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 0 1.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1.0 4.0 0.0 1\n",
|
||
"3 3 4 0 1.0 5.0 0.0 0\n",
|
||
"4 4 3 1 1.0 4.0 0.0 1\n",
|
||
"5 5 4 1 1.0 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one, reject_prob=[[0., 0.5, 1.]], seed=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 60,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
"__init__() got an unexpected keyword argument 'close_first'\n",
|
||
"LongOnly\n",
|
||
"__init__() got an unexpected keyword argument 'close_first'\n",
|
||
"ShortOnly\n",
|
||
"__init__() got an unexpected keyword argument 'close_first'\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=pd.Series([np.inf, -np.inf, -np.inf, np.inf, np.inf]), close_first=[[False, True]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 61,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1000.0 2.0 0.0 1\n",
|
||
"2 2 3 0 500.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1000.0 5.0 0.0 1\n",
|
||
"4 4 1 1 1000.0 2.0 0.0 1\n",
|
||
"5 5 4 1 1000.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 100.0 2.0 0.0 1\n",
|
||
"2 2 3 0 50.0 4.0 0.0 0\n",
|
||
"3 3 4 0 50.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1000.0 1.0 0.0 1\n",
|
||
"1 1 1 0 550.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1000.0 4.0 0.0 1\n",
|
||
"3 3 4 0 800.0 5.0 0.0 0\n",
|
||
"4 4 0 1 1000.0 1.0 0.0 1\n",
|
||
"5 5 3 1 1000.0 4.0 0.0 1\n",
|
||
"6 6 4 1 1000.0 5.0 0.0 0\n",
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 200.0 2.0 0.0 1\n",
|
||
"2 2 3 0 100.0 4.0 0.0 0\n",
|
||
"3 3 0 1 100.0 1.0 0.0 0\n",
|
||
"4 4 1 1 200.0 2.0 0.0 1\n",
|
||
"5 5 3 1 100.0 4.0 0.0 0\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 100.0 2.0 0.0 1\n",
|
||
"2 2 3 0 50.0 4.0 0.0 0\n",
|
||
"3 3 4 0 50.0 5.0 0.0 1\n",
|
||
"4 4 0 1 100.0 1.0 0.0 0\n",
|
||
"5 5 1 1 100.0 2.0 0.0 1\n",
|
||
"6 6 3 1 50.0 4.0 0.0 0\n",
|
||
"7 7 4 1 50.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 1\n",
|
||
"1 1 1 0 100.0 2.0 0.0 0\n",
|
||
"2 2 0 1 100.0 1.0 0.0 1\n",
|
||
"3 3 1 1 100.0 2.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one * 1000, allow_partial=[[True, False]])\n",
|
||
"test_per_direction(size=order_size, allow_partial=[[True, False]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 62,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 1000.0 2.0 0.0 1\n",
|
||
"2 2 3 0 500.0 4.0 0.0 0\n",
|
||
"3 3 4 0 1000.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 100.0 2.0 0.0 1\n",
|
||
"2 2 3 0 50.0 4.0 0.0 0\n",
|
||
"3 3 4 0 50.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1000.0 1.0 0.0 1\n",
|
||
"1 1 1 0 550.0 2.0 0.0 0\n",
|
||
"2 2 3 0 1000.0 4.0 0.0 1\n",
|
||
"3 3 4 0 800.0 5.0 0.0 0\n",
|
||
"All\n",
|
||
"Final size is less than requested\n",
|
||
"LongOnly\n",
|
||
"Final size is less than requested\n",
|
||
"ShortOnly\n",
|
||
"Final size is less than requested\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=order_size_one * 1000, allow_partial=True, raise_reject=True)\n",
|
||
"test_per_direction(size=order_size_one * 1000, allow_partial=False, raise_reject=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 63,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col group cash position debt free_cash val_price value \\\n",
|
||
"0 0 0 0 0 100.0 0.0 0.0 100.0 1.0 100.0 \n",
|
||
"1 1 1 0 0 0.0 100.0 0.0 0.0 2.0 200.0 \n",
|
||
"2 2 2 0 0 400.0 -100.0 200.0 0.0 3.0 100.0 \n",
|
||
"3 3 3 0 0 400.0 -100.0 200.0 0.0 4.0 0.0 \n",
|
||
"4 4 4 0 0 0.0 0.0 0.0 0.0 5.0 0.0 \n",
|
||
"\n",
|
||
" ... new_free_cash new_val_price new_value res_size res_price \\\n",
|
||
"0 ... 0.0 1.0 100.0 100.0 1.0 \n",
|
||
"1 ... 0.0 2.0 200.0 200.0 2.0 \n",
|
||
"2 ... 0.0 3.0 100.0 NaN NaN \n",
|
||
"3 ... 0.0 4.0 0.0 100.0 4.0 \n",
|
||
"4 ... 0.0 5.0 0.0 NaN NaN \n",
|
||
"\n",
|
||
" res_fees res_side res_status res_status_info order_id \n",
|
||
"0 0.0 0 0 -1 0 \n",
|
||
"1 0.0 1 0 -1 1 \n",
|
||
"2 NaN -1 1 0 -1 \n",
|
||
"3 0.0 0 0 -1 2 \n",
|
||
"4 NaN -1 2 6 -1 \n",
|
||
"\n",
|
||
"[5 rows x 37 columns]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(price, order_size, log=True, direction='both')\n",
|
||
"\n",
|
||
"print(portfolio.logs.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 64,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 200.0 2.0 0.0 1\n",
|
||
"2 2 3 0 100.0 4.0 0.0 0\n",
|
||
"3 3 0 1 100.0 1.0 0.0 0\n",
|
||
"4 4 1 1 200.0 2.0 0.0 1\n",
|
||
"5 5 3 1 100.0 4.0 0.0 0\n",
|
||
"6 6 0 2 100.0 1.0 0.0 0\n",
|
||
"7 7 1 2 200.0 2.0 0.0 1\n",
|
||
"8 8 3 2 100.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, order_size, \n",
|
||
" group_by=np.array([0, 0, 1]), direction='both')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 65,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 200.0 2.0 0.0 1\n",
|
||
"2 2 3 0 100.0 4.0 0.0 0\n",
|
||
"3 3 0 2 100.0 1.0 0.0 0\n",
|
||
"4 4 1 2 200.0 2.0 0.0 1\n",
|
||
"5 5 3 2 100.0 4.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 0\n",
|
||
"2020-01-02 0 1 0\n",
|
||
"2020-01-03 0 1 0\n",
|
||
"2020-01-04 0 1 0\n",
|
||
"2020-01-05 0 1 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, order_size, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 66,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 1 100.0 1.0 0.0 0\n",
|
||
"1 1 1 1 200.0 2.0 0.0 1\n",
|
||
"2 2 3 1 100.0 4.0 0.0 0\n",
|
||
"3 3 0 2 100.0 1.0 0.0 0\n",
|
||
"4 4 1 2 200.0 2.0 0.0 1\n",
|
||
"5 5 3 2 100.0 4.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 1 0 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, order_size, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='reversed')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 67,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 0 200.0 2.0 0.0 1\n",
|
||
"2 2 3 1 100.0 4.0 0.0 0\n",
|
||
"3 3 4 1 120.0 5.0 0.0 1\n",
|
||
"4 4 0 2 100.0 1.0 0.0 0\n",
|
||
"5 5 1 2 200.0 2.0 0.0 1\n",
|
||
"6 6 3 2 100.0 4.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 0\n",
|
||
"2020-01-02 0 1 0\n",
|
||
"2020-01-03 0 1 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 0 1 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 1 100.0 1.0 0.0 0\n",
|
||
"1 1 1 1 200.0 2.0 0.0 1\n",
|
||
"2 2 3 1 100.0 4.0 0.0 0\n",
|
||
"3 3 0 2 100.0 1.0 0.0 0\n",
|
||
"4 4 1 2 200.0 2.0 0.0 1\n",
|
||
"5 5 3 2 100.0 4.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 0 1 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, order_size, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='random')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, order_size, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='random', seed=42)\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 68,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 2 100.0 1.0 0.0 0\n",
|
||
"1 1 1 2 200.0 1.0 0.0 1\n",
|
||
"2 2 1 1 200.0 1.0 0.0 0\n",
|
||
"3 3 2 1 200.0 1.0 0.0 1\n",
|
||
"4 4 2 0 200.0 1.0 0.0 0\n",
|
||
"5 5 3 0 200.0 1.0 0.0 1\n",
|
||
"6 6 3 2 200.0 1.0 0.0 0\n",
|
||
"7 7 4 2 200.0 1.0 0.0 1\n",
|
||
"8 8 4 1 200.0 1.0 0.0 0\n",
|
||
" 0 1 2\n",
|
||
"0 0 1 2\n",
|
||
"1 2 0 1\n",
|
||
"2 1 2 0\n",
|
||
"3 0 1 2\n",
|
||
"4 2 0 1\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 100.0\n",
|
||
"1 0.0 200.0 -100.0\n",
|
||
"2 200.0 0.0 -100.0\n",
|
||
"3 0.0 0.0 100.0\n",
|
||
"4 0.0 200.0 -100.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 2 100.0 1.0 0.0 0\n",
|
||
"1 1 1 2 100.0 1.0 0.0 1\n",
|
||
"2 2 1 1 100.0 1.0 0.0 0\n",
|
||
"3 3 2 1 100.0 1.0 0.0 1\n",
|
||
"4 4 2 0 100.0 1.0 0.0 0\n",
|
||
"5 5 3 0 100.0 1.0 0.0 1\n",
|
||
"6 6 3 2 100.0 1.0 0.0 0\n",
|
||
"7 7 4 2 100.0 1.0 0.0 1\n",
|
||
"8 8 4 1 100.0 1.0 0.0 0\n",
|
||
" 0 1 2\n",
|
||
"0 0 1 2\n",
|
||
"1 2 0 1\n",
|
||
"2 1 2 0\n",
|
||
"3 0 1 2\n",
|
||
"4 2 0 1\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 100.0\n",
|
||
"1 0.0 100.0 0.0\n",
|
||
"2 100.0 0.0 0.0\n",
|
||
"3 0.0 0.0 100.0\n",
|
||
"4 0.0 100.0 0.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 2 100.0 1.0 0.0 1\n",
|
||
"1 1 1 2 100.0 1.0 0.0 0\n",
|
||
"2 2 2 0 100.0 1.0 0.0 1\n",
|
||
"3 3 3 0 100.0 1.0 0.0 0\n",
|
||
"4 4 4 1 100.0 1.0 0.0 1\n",
|
||
" 0 1 2\n",
|
||
"0 2 0 1\n",
|
||
"1 1 0 2\n",
|
||
"2 0 2 1\n",
|
||
"3 2 1 0\n",
|
||
"4 1 0 2\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 -100.0\n",
|
||
"1 0.0 0.0 0.0\n",
|
||
"2 -100.0 0.0 0.0\n",
|
||
"3 0.0 0.0 0.0\n",
|
||
"4 0.0 -100.0 0.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for direction in ('Both', 'LongOnly', 'ShortOnly'):\n",
|
||
" print(direction)\n",
|
||
" portfolio = vbt.Portfolio.from_orders(1., pd.DataFrame([\n",
|
||
" [0., 0., np.inf],\n",
|
||
" [0., np.inf, -np.inf],\n",
|
||
" [np.inf, -np.inf, 0.],\n",
|
||
" [-np.inf, 0., np.inf],\n",
|
||
" [0., np.inf, -np.inf],\n",
|
||
" ]), group_by=np.array([0, 0, 0]), \n",
|
||
" cash_sharing=True, call_seq='auto', direction=direction)\n",
|
||
"\n",
|
||
" print(portfolio.orders.records)\n",
|
||
" print(portfolio.call_seq)\n",
|
||
" print(portfolio.assets())\n",
|
||
" print(portfolio.value())\n",
|
||
" # notice how shorting with np.inf only accounts for current cash, not for other assets!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 75.0 1.0 0.0 0\n",
|
||
"1 1 0 1 75.0 1.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 75.0 1.0 0.0 0\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 75.0 1.0 0.0 1\n",
|
||
" 0 1\n",
|
||
"2020-01-01 75.0 -75.0\n",
|
||
"2020-01-02 75.0 -75.0\n",
|
||
"2020-01-03 75.0 -75.0\n",
|
||
"2020-01-04 75.0 -75.0\n",
|
||
"2020-01-05 75.0 -75.0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 75.0 1.0 0.0 0\n",
|
||
"1 1 0 1 25.0 1.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 75.0 25.0 0.0\n",
|
||
"2020-01-02 75.0 25.0 0.0\n",
|
||
"2020-01-03 75.0 25.0 0.0\n",
|
||
"2020-01-04 75.0 25.0 0.0\n",
|
||
"2020-01-05 75.0 25.0 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=[[75., -75.]], size_type=SizeType.TargetAmount)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price, [[75., -75.]], size_type=SizeType.TargetAmount, direction='both')\n",
|
||
"print(portfolio.assets())\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, 75., size_type=SizeType.TargetAmount, \n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True, direction='both')\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.assets())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 70,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 25.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 8.333333 3.0 0.0 1\n",
|
||
"3 3 3 0 4.166667 4.0 0.0 1\n",
|
||
"4 4 4 0 2.500000 5.0 0.0 1\n",
|
||
"5 5 0 1 50.000000 1.0 0.0 1\n",
|
||
"6 6 1 1 25.000000 2.0 0.0 0\n",
|
||
"7 7 2 1 8.333333 3.0 0.0 0\n",
|
||
"8 8 3 1 4.166667 4.0 0.0 0\n",
|
||
"9 9 4 1 2.500000 5.0 0.0 0\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 25.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 8.333333 3.0 0.0 1\n",
|
||
"3 3 3 0 4.166667 4.0 0.0 1\n",
|
||
"4 4 4 0 2.500000 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 1\n",
|
||
"1 1 1 0 25.000000 2.0 0.0 0\n",
|
||
"2 2 2 0 8.333333 3.0 0.0 0\n",
|
||
"3 3 3 0 4.166667 4.0 0.0 0\n",
|
||
"4 4 4 0 2.500000 5.0 0.0 0\n",
|
||
" 0 1\n",
|
||
"2020-01-01 50.0 -50.0\n",
|
||
"2020-01-02 50.0 -50.0\n",
|
||
"2020-01-03 50.0 -50.0\n",
|
||
"2020-01-04 50.0 -50.0\n",
|
||
"2020-01-05 50.0 -50.0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 0\n",
|
||
"1 1 0 1 50.000000 1.0 0.0 0\n",
|
||
"2 2 1 0 25.000000 2.0 0.0 1\n",
|
||
"3 3 1 1 25.000000 2.0 0.0 1\n",
|
||
"4 4 1 2 25.000000 2.0 0.0 0\n",
|
||
"5 5 2 0 8.333333 3.0 0.0 1\n",
|
||
"6 6 2 1 8.333333 3.0 0.0 1\n",
|
||
"7 7 2 2 8.333333 3.0 0.0 1\n",
|
||
"8 8 3 0 4.166667 4.0 0.0 1\n",
|
||
"9 9 3 1 4.166667 4.0 0.0 1\n",
|
||
"10 10 3 2 4.166667 4.0 0.0 1\n",
|
||
"11 11 4 0 2.500000 5.0 0.0 1\n",
|
||
"12 12 4 1 2.500000 5.0 0.0 1\n",
|
||
"13 13 4 2 2.500000 5.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 50.0 50.0 0.0\n",
|
||
"2020-01-02 50.0 50.0 50.0\n",
|
||
"2020-01-03 50.0 50.0 50.0\n",
|
||
"2020-01-04 50.0 50.0 50.0\n",
|
||
"2020-01-05 50.0 50.0 50.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=[[50., -50.]], size_type=SizeType.TargetValue)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price, [[50., -50.]], size_type=SizeType.TargetValue, direction='both')\n",
|
||
"print(portfolio.asset_value())\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, 50., size_type=SizeType.TargetValue, \n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True, direction='both')\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.asset_value(group_by=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 71,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"All\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 12.500000 2.0 0.0 1\n",
|
||
"2 2 2 0 6.250000 3.0 0.0 1\n",
|
||
"3 3 3 0 3.906250 4.0 0.0 1\n",
|
||
"4 4 4 0 2.734375 5.0 0.0 1\n",
|
||
"5 5 0 1 50.000000 1.0 0.0 1\n",
|
||
"6 6 1 1 37.500000 2.0 0.0 0\n",
|
||
"7 7 2 1 6.250000 3.0 0.0 0\n",
|
||
"8 8 3 1 2.343750 4.0 0.0 0\n",
|
||
"9 9 4 1 1.171875 5.0 0.0 0\n",
|
||
"LongOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 12.500000 2.0 0.0 1\n",
|
||
"2 2 2 0 6.250000 3.0 0.0 1\n",
|
||
"3 3 3 0 3.906250 4.0 0.0 1\n",
|
||
"4 4 4 0 2.734375 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 1.0 0.0 1\n",
|
||
"1 1 1 0 37.500000 2.0 0.0 0\n",
|
||
"2 2 2 0 6.250000 3.0 0.0 0\n",
|
||
"3 3 3 0 2.343750 4.0 0.0 0\n",
|
||
"4 4 4 0 1.171875 5.0 0.0 0\n",
|
||
" 0 1\n",
|
||
"2020-01-01 0.5 -0.5\n",
|
||
"2020-01-02 0.5 -0.5\n",
|
||
"2020-01-03 0.5 -0.5\n",
|
||
"2020-01-04 0.5 -0.5\n",
|
||
"2020-01-05 0.5 -0.5\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.0 1.0 0.0 0\n",
|
||
"1 1 0 1 50.0 1.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.500000 0.500000 0.0\n",
|
||
"2020-01-02 0.666667 0.666667 0.0\n",
|
||
"2020-01-03 0.750000 0.750000 0.0\n",
|
||
"2020-01-04 0.800000 0.800000 0.0\n",
|
||
"2020-01-05 0.833333 0.833333 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=[[0.5, -0.5]], size_type=SizeType.TargetPercent)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price, [[0.5, -0.5]], size_type=SizeType.TargetPercent, direction='both')\n",
|
||
"print(portfolio.asset_value() / portfolio.value())\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_wide, 0.5, size_type=SizeType.TargetPercent, \n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True, direction='both')\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.asset_value(group_by=False) / portfolio.value(group_by=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 72,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 70.0 0.0 30.0\n",
|
||
"2020-01-03 30.0 70.0 0.0\n",
|
||
"2020-01-04 0.0 30.0 70.0\n",
|
||
"2020-01-05 70.0 30.0 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"price_one = pd.Series([1., 1., 1., 1., 1.], index=price.index)\n",
|
||
"target_hold_value = pd.DataFrame({\n",
|
||
" 'a': [0., 70., 30., 0., 70.],\n",
|
||
" 'b': [30., 0., 70., 30., 30.],\n",
|
||
" 'c': [70., 30., 0., 70., 0.]\n",
|
||
"}, index=price.index)\n",
|
||
"print(target_hold_value)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 75,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 1 30.0 1.0 0.0 0\n",
|
||
"1 1 0 2 70.0 1.0 0.0 0\n",
|
||
"2 2 1 2 40.0 1.0 0.0 1\n",
|
||
"3 3 1 1 30.0 1.0 0.0 1\n",
|
||
"4 4 2 1 70.0 1.0 0.0 0\n",
|
||
"5 5 2 2 30.0 1.0 0.0 1\n",
|
||
"6 6 3 2 30.0 1.0 0.0 0\n",
|
||
"7 7 3 1 40.0 1.0 0.0 1\n",
|
||
"8 8 4 0 40.0 1.0 0.0 0\n",
|
||
"9 9 4 2 30.0 1.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 0.0 -30.0 -40.0\n",
|
||
"2020-01-03 0.0 70.0 -30.0\n",
|
||
"2020-01-04 0.0 -40.0 30.0\n",
|
||
"2020-01-05 40.0 0.0 -30.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 0.0 0.0 30.0\n",
|
||
"2020-01-03 0.0 70.0 0.0\n",
|
||
"2020-01-04 0.0 30.0 30.0\n",
|
||
"2020-01-05 40.0 30.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 2 0\n",
|
||
"2020-01-02 0 2 1\n",
|
||
"2020-01-03 1 0 2\n",
|
||
"2020-01-04 0 2 1\n",
|
||
"2020-01-05 1 0 2\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_one, target_hold_value, size_type=SizeType.TargetValue,\n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True,\n",
|
||
" call_seq='random', seed=43)\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.asset_flow())\n",
|
||
"print(portfolio.asset_value(group_by=False)) # order fixed -> cannot rebalance properly\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 76,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 1 30.0 1.0 0.0 0\n",
|
||
"1 1 0 2 70.0 1.0 0.0 0\n",
|
||
"2 2 1 2 40.0 1.0 0.0 1\n",
|
||
"3 3 1 1 30.0 1.0 0.0 1\n",
|
||
"4 4 1 0 70.0 1.0 0.0 0\n",
|
||
"5 5 2 0 40.0 1.0 0.0 1\n",
|
||
"6 6 2 2 30.0 1.0 0.0 1\n",
|
||
"7 7 2 1 70.0 1.0 0.0 0\n",
|
||
"8 8 3 1 40.0 1.0 0.0 1\n",
|
||
"9 9 3 0 30.0 1.0 0.0 1\n",
|
||
"10 10 3 2 70.0 1.0 0.0 0\n",
|
||
"11 11 4 2 70.0 1.0 0.0 1\n",
|
||
"12 12 4 0 70.0 1.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 70.0 -30.0 -40.0\n",
|
||
"2020-01-03 -40.0 70.0 -30.0\n",
|
||
"2020-01-04 -30.0 -40.0 70.0\n",
|
||
"2020-01-05 70.0 0.0 -70.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 70.0 0.0 30.0\n",
|
||
"2020-01-03 30.0 70.0 0.0\n",
|
||
"2020-01-04 0.0 30.0 70.0\n",
|
||
"2020-01-05 70.0 30.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 2\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 0 2 1\n",
|
||
"2020-01-04 1 0 2\n",
|
||
"2020-01-05 2 1 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_one, target_hold_value, size_type=SizeType.TargetValue, \n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True,\n",
|
||
" call_seq='auto')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.asset_flow())\n",
|
||
"print(portfolio.asset_value(group_by=False)) # order dynamic -> can rebalance\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 77,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 1 30.0 1.0 0.0 0\n",
|
||
"1 1 0 2 70.0 1.0 0.0 0\n",
|
||
"2 2 1 2 40.0 1.0 0.0 1\n",
|
||
"3 3 1 1 30.0 1.0 0.0 1\n",
|
||
"4 4 1 0 70.0 1.0 0.0 0\n",
|
||
"5 5 2 0 40.0 1.0 0.0 1\n",
|
||
"6 6 2 2 30.0 1.0 0.0 1\n",
|
||
"7 7 2 1 70.0 1.0 0.0 0\n",
|
||
"8 8 3 1 40.0 1.0 0.0 1\n",
|
||
"9 9 3 0 30.0 1.0 0.0 1\n",
|
||
"10 10 3 2 70.0 1.0 0.0 0\n",
|
||
"11 11 4 2 70.0 1.0 0.0 1\n",
|
||
"12 12 4 0 70.0 1.0 0.0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 70.0 -30.0 -40.0\n",
|
||
"2020-01-03 -40.0 70.0 -30.0\n",
|
||
"2020-01-04 -30.0 -40.0 70.0\n",
|
||
"2020-01-05 70.0 0.0 -70.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 30.0 70.0\n",
|
||
"2020-01-02 70.0 0.0 30.0\n",
|
||
"2020-01-03 30.0 70.0 0.0\n",
|
||
"2020-01-04 0.0 30.0 70.0\n",
|
||
"2020-01-05 70.0 30.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 2\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 0 2 1\n",
|
||
"2020-01-04 1 0 2\n",
|
||
"2020-01-05 2 1 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_one, target_hold_value / 100., size_type=SizeType.TargetPercent, \n",
|
||
" group_by=np.array([0, 0, 0]), cash_sharing=True,\n",
|
||
" call_seq='auto')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.asset_flow())\n",
|
||
"print(portfolio.asset_value(group_by=False))\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## from_signals"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(5,) (5, 3)\n",
|
||
"(5,) (5, 3)\n",
|
||
"(1000,) (1000, 1000)\n",
|
||
"(1000,) (1000, 1000)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"entries = pd.Series([True, True, True, False, False], index=price.index)\n",
|
||
"entries_wide = entries.vbt.tile(3, keys=['a', 'b', 'c'])\n",
|
||
"print(entries.shape, entries_wide.shape)\n",
|
||
"\n",
|
||
"exits = pd.Series([False, False, True, True, True], index=price.index)\n",
|
||
"exits_wide = exits.vbt.tile(3, keys=['a', 'b', 'c'])\n",
|
||
"print(exits.shape, exits_wide.shape)\n",
|
||
"\n",
|
||
"big_entries = pd.DataFrame.vbt.signals.empty((1000,), index=big_price.index)\n",
|
||
"big_entries.iloc[0::2] = True\n",
|
||
"big_entries_wide = big_entries.vbt.tile(1000)\n",
|
||
"print(big_entries.shape, big_entries_wide.shape)\n",
|
||
"\n",
|
||
"big_exits = pd.DataFrame.vbt.signals.empty((1000,), index=big_price.index)\n",
|
||
"big_exits.iloc[1::2] = True\n",
|
||
"big_exits_wide = big_exits.vbt.tile(1000)\n",
|
||
"print(big_exits.shape, big_exits_wide.shape)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2.72 ms ± 238 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price, big_entries, big_exits,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"95.1 ms ± 2.6 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"104 ms ± 1.87 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, sl_stop=np.inf, tp_stop=np.inf, accumulate=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"171 ms ± 6.43 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True, log=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"98.4 ms ± 250 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.repeat(np.arange(500), 2))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100 ms ± 564 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"101 ms ± 191 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# worst case\n",
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=np.arange(1000)[::-1], init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, call_seq=CallSeqType.Auto)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"98.6 ms ± 848 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.full(1000, 0))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"96 ms ± 501 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=1., init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"279 ms ± 1.83 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# worst case\n",
|
||
"%timeit vbt.Portfolio.from_signals(\\\n",
|
||
" big_price_wide, big_entries_wide, big_exits_wide,\\\n",
|
||
" size=np.arange(1000)[::-1], init_cash=np.inf, accumulate=True,\\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True, call_seq=CallSeqType.Auto)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def test_per_direction(price=price, entries=entries, exits=exits, **kwargs):\n",
|
||
" print('Both')\n",
|
||
" try:\n",
|
||
" portfolio = vbt.Portfolio.from_signals(price, entries, exits, direction='both', **kwargs)\n",
|
||
" print(portfolio.orders.records)\n",
|
||
" except Exception as e:\n",
|
||
" print(e)\n",
|
||
" print('LongOnly')\n",
|
||
" try:\n",
|
||
" portfolio = vbt.Portfolio.from_signals(price, entries, exits, direction='longonly', **kwargs)\n",
|
||
" print(portfolio.orders.records)\n",
|
||
" except Exception as e:\n",
|
||
" print(e)\n",
|
||
" print('ShortOnly')\n",
|
||
" try:\n",
|
||
" portfolio = vbt.Portfolio.from_signals(price, entries, exits, direction='shortonly', **kwargs)\n",
|
||
" print(portfolio.orders.records)\n",
|
||
" except Exception as e:\n",
|
||
" print(e)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 100.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 1\n",
|
||
"1 1 0 3 50.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 3 2.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 200.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 3 1.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 100.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 1.0 1.0 0.0 1\n",
|
||
"1 1 1 3 1.0 4.0 0.0 0\n",
|
||
"2 2 2 0 100.0 1.0 0.0 1\n",
|
||
"3 3 2 3 50.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=[[0, 1, np.inf]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
"SizeType.Percent does not support position reversal using signals\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 50.0 1.0 0.0 0\n",
|
||
"1 1 0 3 50.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 50.0 1.0 0.0 1\n",
|
||
"1 1 0 3 37.5 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=0.5, size_type='percent')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 50.000 1.0 0.0 0\n",
|
||
"1 1 0 1 12.500 2.0 0.0 0\n",
|
||
"2 2 0 3 65.625 4.0 0.0 1\n",
|
||
"3 3 0 4 26.250 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 50.000 1.0 0.0 0\n",
|
||
"1 1 0 1 12.500 2.0 0.0 0\n",
|
||
"2 2 0 3 31.250 4.0 0.0 1\n",
|
||
"3 3 0 4 15.625 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 50.000 1.0 0.0 1\n",
|
||
"1 1 0 1 12.500 2.0 0.0 1\n",
|
||
"2 2 0 3 21.875 4.0 0.0 0\n",
|
||
"3 3 0 4 8.750 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=0.5, size_type='percent', accumulate=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 99.009901 1.01 0.0 0\n",
|
||
"1 1 0 3 198.019802 4.04 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 99.009901 1.01 0.0 0\n",
|
||
"1 1 0 3 99.009901 4.04 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 99.009901 1.01 0.0 1\n",
|
||
"1 1 0 3 49.504950 4.04 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(price=price * 1.01)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 2.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.1 0\n",
|
||
"3 3 1 3 2.0 4.0 0.8 1\n",
|
||
"4 4 2 0 1.0 1.0 1.0 0\n",
|
||
"5 5 2 3 2.0 4.0 8.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.1 0\n",
|
||
"3 3 1 3 1.0 4.0 0.4 1\n",
|
||
"4 4 2 0 1.0 1.0 1.0 0\n",
|
||
"5 5 2 3 1.0 4.0 4.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 3 1.0 4.0 0.0 0\n",
|
||
"2 2 1 0 1.0 1.0 0.1 1\n",
|
||
"3 3 1 3 1.0 4.0 0.4 0\n",
|
||
"4 4 2 0 1.0 1.0 1.0 1\n",
|
||
"5 5 2 3 1.0 4.0 4.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, fees=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 2.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.1 0\n",
|
||
"3 3 1 3 2.0 4.0 0.1 1\n",
|
||
"4 4 2 0 1.0 1.0 1.0 0\n",
|
||
"5 5 2 3 2.0 4.0 1.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.1 0\n",
|
||
"3 3 1 3 1.0 4.0 0.1 1\n",
|
||
"4 4 2 0 1.0 1.0 1.0 0\n",
|
||
"5 5 2 3 1.0 4.0 1.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 3 1.0 4.0 0.0 0\n",
|
||
"2 2 1 0 1.0 1.0 0.1 1\n",
|
||
"3 3 1 3 1.0 4.0 0.1 0\n",
|
||
"4 4 2 0 1.0 1.0 1.0 1\n",
|
||
"5 5 2 3 1.0 4.0 1.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, fixed_fees=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 2.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.1 0.0 0\n",
|
||
"3 3 1 3 2.0 3.6 0.0 1\n",
|
||
"4 4 2 0 1.0 2.0 0.0 0\n",
|
||
"5 5 2 3 2.0 0.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.1 0.0 0\n",
|
||
"3 3 1 3 1.0 3.6 0.0 1\n",
|
||
"4 4 2 0 1.0 2.0 0.0 0\n",
|
||
"5 5 2 3 1.0 0.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 3 1.0 4.0 0.0 0\n",
|
||
"2 2 1 0 1.0 0.9 0.0 1\n",
|
||
"3 3 1 3 1.0 4.4 0.0 0\n",
|
||
"4 4 2 0 1.0 0.0 0.0 1\n",
|
||
"5 5 2 3 1.0 8.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, slippage=[[0., 0.1, 1.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 2.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.0 0\n",
|
||
"3 3 1 3 2.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1.0 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.0 0\n",
|
||
"3 3 1 3 1.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 3 1.0 4.0 0.0 0\n",
|
||
"2 2 1 0 1.0 1.0 0.0 1\n",
|
||
"3 3 1 3 1.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, min_size=[[0., 1., 2.]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 0\n",
|
||
"1 1 0 3 0.5 4.0 0.0 1\n",
|
||
"2 2 0 4 0.5 5.0 0.0 1\n",
|
||
"3 3 1 0 1.0 1.0 0.0 0\n",
|
||
"4 4 1 3 1.0 4.0 0.0 1\n",
|
||
"5 5 1 4 1.0 5.0 0.0 1\n",
|
||
"6 6 2 0 1.0 1.0 0.0 0\n",
|
||
"7 7 2 3 2.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 0\n",
|
||
"1 1 0 3 0.5 4.0 0.0 1\n",
|
||
"2 2 1 0 1.0 1.0 0.0 0\n",
|
||
"3 3 1 3 1.0 4.0 0.0 1\n",
|
||
"4 4 2 0 1.0 1.0 0.0 0\n",
|
||
"5 5 2 3 1.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 0.5 1.0 0.0 1\n",
|
||
"1 1 0 3 0.5 4.0 0.0 0\n",
|
||
"2 2 1 0 1.0 1.0 0.0 1\n",
|
||
"3 3 1 3 1.0 4.0 0.0 0\n",
|
||
"4 4 2 0 1.0 1.0 0.0 1\n",
|
||
"5 5 2 3 1.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, max_size=[[0.5, 1., np.inf]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 2.0 4.0 0.0 1\n",
|
||
"2 2 1 1 1.0 2.0 0.0 0\n",
|
||
"3 3 1 3 2.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1.0 4.0 0.0 1\n",
|
||
"2 2 1 1 1.0 2.0 0.0 0\n",
|
||
"3 3 1 3 1.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 3 1.0 4.0 0.0 0\n",
|
||
"2 2 1 1 1.0 2.0 0.0 1\n",
|
||
"3 3 1 3 1.0 4.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1., reject_prob=[[0., 0.5, 1.]], seed=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
"2 2 1 0 100.0 1.0 0.0 0\n",
|
||
"3 3 1 3 100.0 4.0 0.0 1\n",
|
||
"4 4 1 4 80.0 5.0 0.0 1\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 20.0 5.0 0.0 1\n",
|
||
"1 1 0 3 100.0 2.0 0.0 0\n",
|
||
"2 2 1 0 20.0 5.0 0.0 1\n",
|
||
"3 3 1 3 20.0 2.0 0.0 0\n",
|
||
"4 4 1 4 160.0 1.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price, entries, exits, direction='both',\n",
|
||
" upon_opposite_entry=[['reverse', 'close']]\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" pd.Series(price.values[::-1], index=price.index),\n",
|
||
" pd.Series(entries.values[::-1], index=price.index),\n",
|
||
" pd.Series(exits.values[::-1], index=price.index), \n",
|
||
" direction='both',\n",
|
||
" upon_opposite_entry=[['reverse', 'close']]\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1100.0 4.0 0.0 1\n",
|
||
"2 2 1 3 1000.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 100.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1000.0 1.0 0.0 1\n",
|
||
"1 1 0 3 275.0 4.0 0.0 0\n",
|
||
"2 2 1 0 1000.0 1.0 0.0 1\n",
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
"2 2 1 0 100.0 1.0 0.0 0\n",
|
||
"3 3 1 3 200.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 100.0 4.0 0.0 1\n",
|
||
"2 2 1 0 100.0 1.0 0.0 0\n",
|
||
"3 3 1 3 100.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 1\n",
|
||
"1 1 0 3 50.0 4.0 0.0 0\n",
|
||
"2 2 1 0 100.0 1.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1000, allow_partial=[[True, False]])\n",
|
||
"test_per_direction(size=np.inf, allow_partial=[[True, False]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 1100.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 100.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
"Not enough cash to cover fees\n",
|
||
"Both\n",
|
||
"Final size is less than requested\n",
|
||
"LongOnly\n",
|
||
"Final size is less than requested\n",
|
||
"ShortOnly\n",
|
||
"Final size is less than requested\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1000, allow_partial=True, raise_reject=True)\n",
|
||
"test_per_direction(size=1000, allow_partial=False, raise_reject=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 1 1.0 2.0 0.0 0\n",
|
||
"2 2 0 3 1.0 4.0 0.0 1\n",
|
||
"3 3 0 4 1.0 5.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 0 1 1.0 2.0 0.0 0\n",
|
||
"2 2 0 3 1.0 4.0 0.0 1\n",
|
||
"3 3 0 4 1.0 5.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 1\n",
|
||
"1 1 0 1 1.0 2.0 0.0 1\n",
|
||
"2 2 0 3 1.0 4.0 0.0 0\n",
|
||
"3 3 0 4 1.0 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(size=1, accumulate=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
" id group col idx cash position debt free_cash val_price value \\\n",
|
||
"0 0 0 0 0 100.0 0.0 0.0 100.0 1.0 100.0 \n",
|
||
"1 1 0 0 3 0.0 100.0 0.0 0.0 4.0 400.0 \n",
|
||
"\n",
|
||
" ... new_free_cash new_val_price new_value res_size res_price \\\n",
|
||
"0 ... 0.0 1.0 100.0 100.0 1.0 \n",
|
||
"1 ... 0.0 4.0 400.0 200.0 4.0 \n",
|
||
"\n",
|
||
" res_fees res_side res_status res_status_info order_id \n",
|
||
"0 0.0 0 0 -1 0 \n",
|
||
"1 0.0 1 0 -1 1 \n",
|
||
"\n",
|
||
"[2 rows x 37 columns]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(price, entries, exits, log=True, direction='both')\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.logs.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 0\n",
|
||
"1 1 1 1 1.0 2.0 0.0 0\n",
|
||
"2 2 2 1 1.0 2.0 0.0 0\n",
|
||
"3 3 3 1 1.0 2.0 0.0 0\n",
|
||
"4 4 4 1 1.0 2.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 0\n",
|
||
"1 1 1 0 1.0 1.0 0.0 0\n",
|
||
"2 2 2 1 1.0 2.0 0.0 0\n",
|
||
"3 3 2 2 1.0 3.0 0.0 1\n",
|
||
"4 4 3 1 1.0 2.0 0.0 0\n",
|
||
"5 5 3 2 1.0 3.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 1\n",
|
||
"1 1 1 0 1.0 1.0 0.0 1\n",
|
||
"2 2 2 1 1.0 2.0 0.0 1\n",
|
||
"3 3 2 2 1.0 3.0 0.0 0\n",
|
||
"4 4 3 1 1.0 2.0 0.0 1\n",
|
||
"5 5 3 2 1.0 3.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(price=price.iloc[:3], entries=pd.DataFrame([\n",
|
||
" [True, True, True, True, True],\n",
|
||
" [True, True, True, True, False],\n",
|
||
" [True, True, True, True, True]\n",
|
||
"]), exits=pd.DataFrame([\n",
|
||
" [True, True, True, True, True],\n",
|
||
" [False, False, False, False, True],\n",
|
||
" [True, True, True, True, True]\n",
|
||
"]), size=1., upon_long_conflict=[[\n",
|
||
" 'ignore', \n",
|
||
" 'entry', \n",
|
||
" 'exit', \n",
|
||
" 'opposite',\n",
|
||
" 'opposite'\n",
|
||
"]], upon_short_conflict=[[\n",
|
||
" 'ignore', \n",
|
||
" 'entry', \n",
|
||
" 'exit', \n",
|
||
" 'opposite',\n",
|
||
" 'opposite'\n",
|
||
"]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 0\n",
|
||
"1 1 1 0 1.0 1.0 0.0 0\n",
|
||
"2 2 2 0 1.0 1.0 0.0 1\n",
|
||
"3 3 2 1 2.0 2.0 0.0 0\n",
|
||
"4 4 2 2 2.0 3.0 0.0 1\n",
|
||
"5 5 3 1 1.0 2.0 0.0 0\n",
|
||
"6 6 3 2 2.0 3.0 0.0 1\n",
|
||
"7 7 4 1 1.0 2.0 0.0 1\n",
|
||
"8 8 4 2 2.0 3.0 0.0 0\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 0\n",
|
||
"1 1 1 1 1.0 2.0 0.0 0\n",
|
||
"2 2 2 1 1.0 2.0 0.0 0\n",
|
||
"3 3 3 1 1.0 2.0 0.0 0\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 1.0 2.0 0.0 1\n",
|
||
"1 1 1 1 1.0 2.0 0.0 1\n",
|
||
"2 2 2 1 1.0 2.0 0.0 1\n",
|
||
"3 3 3 1 1.0 2.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(price=price.iloc[:3], entries=pd.DataFrame([\n",
|
||
" [True, True, True, True, True],\n",
|
||
" [True, True, True, True, False],\n",
|
||
" [True, True, True, True, True]\n",
|
||
"]), exits=pd.DataFrame([\n",
|
||
" [True, True, True, True, True],\n",
|
||
" [False, False, False, False, True],\n",
|
||
" [True, True, True, True, True]\n",
|
||
"]), size=1., upon_dir_conflict=[[\n",
|
||
" 'ignore', \n",
|
||
" 'long', \n",
|
||
" 'short', \n",
|
||
" 'opposite',\n",
|
||
" 'opposite'\n",
|
||
"]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 3 1.0 4.0 0.0 1\n",
|
||
"1 1 1 0 1.0 1.0 0.0 0\n",
|
||
"2 2 1 3 2.0 4.0 0.0 1\n",
|
||
"3 3 2 0 1.0 1.0 0.0 0\n",
|
||
"4 4 2 3 2.0 4.0 0.0 1\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 1.0 1.0 0.0 0\n",
|
||
"1 1 1 3 1.0 4.0 0.0 1\n",
|
||
"2 2 2 0 1.0 1.0 0.0 0\n",
|
||
"3 3 2 3 1.0 4.0 0.0 1\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 1.00 1.0 0.0 1\n",
|
||
"1 1 0 3 0.25 4.0 0.0 0\n",
|
||
"2 2 1 0 1.00 1.0 0.0 1\n",
|
||
"3 3 1 3 0.50 4.0 0.0 0\n",
|
||
"4 4 2 0 1.00 1.0 0.0 1\n",
|
||
"5 5 2 3 1.00 4.0 0.0 0\n",
|
||
"Both\n",
|
||
"Attempt to go in long direction infinitely\n",
|
||
"LongOnly\n",
|
||
"Attempt to go in long direction infinitely\n",
|
||
"ShortOnly\n",
|
||
"Attempt to go in short direction infinitely\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"test_per_direction(price=price_wide, size=1., init_cash=[0., 1., 100.])\n",
|
||
"test_per_direction(init_cash=np.inf)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
"2 2 1 0 100.0 1.0 0.0 0\n",
|
||
"3 3 1 3 200.0 4.0 0.0 1\n",
|
||
"4 4 2 0 100.0 1.0 0.0 0\n",
|
||
"5 5 2 3 200.0 4.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price_wide, entries, exits, \n",
|
||
" group_by=np.array([0, 0, 1]), direction='both')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 0 100.0 1.0 0.0 0\n",
|
||
"1 1 0 3 200.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 200.0 4.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 0\n",
|
||
"2020-01-02 0 1 0\n",
|
||
"2020-01-03 0 1 0\n",
|
||
"2020-01-04 0 1 0\n",
|
||
"2020-01-05 0 1 0\n",
|
||
"Cannot modify grouping globally when cash_sharing=True\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price_wide, entries, exits, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)\n",
|
||
"try:\n",
|
||
" print(portfolio.regroup(group_by=False))\n",
|
||
"except Exception as e:\n",
|
||
" print(e)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 3 200.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 200.0 4.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 1 0 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price_wide, entries, exits, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='reversed')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 3 200.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 200.0 4.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 1 0 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 0 1 0\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 100.0 1.0 0.0 0\n",
|
||
"1 1 1 3 200.0 4.0 0.0 1\n",
|
||
"2 2 2 0 100.0 1.0 0.0 0\n",
|
||
"3 3 2 3 200.0 4.0 0.0 1\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 0 1 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price_wide, entries, exits, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='random')\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_signals(\n",
|
||
" price_wide, entries, exits, \n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, direction='both', call_seq='random', seed=42)\n",
|
||
"\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Both\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 2 0 100.0 1.0 0.0 0\n",
|
||
"1 1 2 1 200.0 1.0 0.0 1\n",
|
||
"2 2 1 1 200.0 1.0 0.0 0\n",
|
||
"3 3 1 2 200.0 1.0 0.0 1\n",
|
||
"4 4 0 2 200.0 1.0 0.0 0\n",
|
||
"5 5 0 3 200.0 1.0 0.0 1\n",
|
||
"6 6 2 3 200.0 1.0 0.0 0\n",
|
||
"7 7 2 4 200.0 1.0 0.0 1\n",
|
||
"8 8 1 4 200.0 1.0 0.0 0\n",
|
||
" 0 1 2\n",
|
||
"0 0 1 2\n",
|
||
"1 2 0 1\n",
|
||
"2 1 2 0\n",
|
||
"3 0 1 2\n",
|
||
"4 2 0 1\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 100.0\n",
|
||
"1 0.0 200.0 -100.0\n",
|
||
"2 200.0 0.0 -100.0\n",
|
||
"3 0.0 0.0 100.0\n",
|
||
"4 0.0 200.0 -100.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n",
|
||
"LongOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 2 0 100.0 1.0 0.0 0\n",
|
||
"1 1 2 1 100.0 1.0 0.0 1\n",
|
||
"2 2 1 1 100.0 1.0 0.0 0\n",
|
||
"3 3 1 2 100.0 1.0 0.0 1\n",
|
||
"4 4 0 2 100.0 1.0 0.0 0\n",
|
||
"5 5 0 3 100.0 1.0 0.0 1\n",
|
||
"6 6 2 3 100.0 1.0 0.0 0\n",
|
||
"7 7 2 4 100.0 1.0 0.0 1\n",
|
||
"8 8 1 4 100.0 1.0 0.0 0\n",
|
||
" 0 1 2\n",
|
||
"0 0 1 2\n",
|
||
"1 2 0 1\n",
|
||
"2 1 2 0\n",
|
||
"3 0 1 2\n",
|
||
"4 2 0 1\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 100.0\n",
|
||
"1 0.0 100.0 0.0\n",
|
||
"2 100.0 0.0 0.0\n",
|
||
"3 0.0 0.0 100.0\n",
|
||
"4 0.0 100.0 0.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n",
|
||
"ShortOnly\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 2 0 100.0 1.0 0.0 1\n",
|
||
"1 1 2 1 100.0 1.0 0.0 0\n",
|
||
"2 2 0 2 100.0 1.0 0.0 1\n",
|
||
"3 3 0 3 100.0 1.0 0.0 0\n",
|
||
"4 4 1 4 100.0 1.0 0.0 1\n",
|
||
" 0 1 2\n",
|
||
"0 2 0 1\n",
|
||
"1 1 0 2\n",
|
||
"2 0 1 2\n",
|
||
"3 2 1 0\n",
|
||
"4 1 0 2\n",
|
||
" 0 1 2\n",
|
||
"0 0.0 0.0 -100.0\n",
|
||
"1 0.0 0.0 0.0\n",
|
||
"2 -100.0 0.0 0.0\n",
|
||
"3 0.0 0.0 0.0\n",
|
||
"4 0.0 -100.0 0.0\n",
|
||
"0 100.0\n",
|
||
"1 100.0\n",
|
||
"2 100.0\n",
|
||
"3 100.0\n",
|
||
"4 100.0\n",
|
||
"dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for direction in ('Both', 'LongOnly', 'ShortOnly'):\n",
|
||
" print(direction)\n",
|
||
" portfolio = vbt.Portfolio.from_signals(1., pd.DataFrame([\n",
|
||
" [False, False, True],\n",
|
||
" [False, True, False],\n",
|
||
" [True, False, False],\n",
|
||
" [False, False, True],\n",
|
||
" [False, True, False],\n",
|
||
" ]), pd.DataFrame([\n",
|
||
" [False, False, False],\n",
|
||
" [False, False, True],\n",
|
||
" [False, True, False],\n",
|
||
" [True, False, False],\n",
|
||
" [False, False, True],\n",
|
||
" ]), group_by=np.array([0, 0, 0]), \n",
|
||
" cash_sharing=True, call_seq='auto', direction=direction)\n",
|
||
"\n",
|
||
" print(portfolio.orders.records)\n",
|
||
" print(portfolio.call_seq)\n",
|
||
" print(portfolio.assets())\n",
|
||
" print(portfolio.value())\n",
|
||
" # notice how shorting with np.inf only accounts for current cash, not for other assets!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## from_order_func"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from vectorbt.portfolio.nb import order_nb, order_nothing_nb\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def order_func_nb(c, size):\n",
|
||
" return order_nb(size if c.i % 2 == 0 else -size)\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def flex_order_func_nb(c, size):\n",
|
||
" if c.call_idx < c.group_len:\n",
|
||
" return c.from_col + c.call_idx, order_nb(size if c.i % 2 == 0 else -size)\n",
|
||
" return -1, order_nothing_nb()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"1.92 ms ± 156 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"2.02 ms ± 189 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"1.85 ms ± 140 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"1.85 ms ± 145 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price, order_func_nb, 1., init_cash=np.inf)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price, order_func_nb, 1., init_cash=np.inf, row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price, flex_order_func_nb, 1., init_cash=np.inf, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price, flex_order_func_nb, 1., init_cash=np.inf, row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"95 ms ± 181 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"101 ms ± 2.48 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"90.9 ms ± 489 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"89.1 ms ± 1.69 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"76.4 ms ± 217 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"84.2 ms ± 284 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"71.5 ms ± 1.39 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"71.1 ms ± 101 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, fill_pos_record=False)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, row_wise=True, fill_pos_record=False)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, fill_pos_record=False, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, row_wise=True, fill_pos_record=False, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"89.1 ms ± 851 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"93.5 ms ± 692 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"86.2 ms ± 287 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"86.3 ms ± 131 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), init_cash=np.inf)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), init_cash=np.inf, row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), init_cash=np.inf, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), init_cash=np.inf, row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"88.7 ms ± 763 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"93 ms ± 686 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"85.4 ms ± 39.1 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"85.7 ms ± 140 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, init_cash=np.inf)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, init_cash=np.inf, row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, init_cash=np.inf, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., \\\n",
|
||
" group_by=np.repeat(np.arange(500), 2), cash_sharing=True, init_cash=np.inf, row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 47,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"87 ms ± 487 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"86.2 ms ± 369 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"83.4 ms ± 151 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"83.3 ms ± 153 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0))\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"83.6 ms ± 622 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"82.7 ms ± 192 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"82.3 ms ± 927 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"82 ms ± 680 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True, row_wise=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True, flexible=True)\n",
|
||
"%timeit vbt.Portfolio.from_order_func(\\\n",
|
||
" big_price_wide, flex_order_func_nb, 1., init_cash=np.inf, \\\n",
|
||
" group_by=np.full(1000, 0), cash_sharing=True, row_wise=True, flexible=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 52,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def test_call_seq(call_seq, **kwargs):\n",
|
||
" return vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, \n",
|
||
" order_func_nb, \n",
|
||
" 1.,\n",
|
||
" group_by=np.array([0, 0, 0]),\n",
|
||
" call_seq=call_seq, **kwargs\n",
|
||
" ).call_seq\n",
|
||
"\n",
|
||
"def big_test_call_seq(call_seq, **kwargs):\n",
|
||
" return vbt.Portfolio.from_order_func(\n",
|
||
" big_price_wide, \n",
|
||
" order_func_nb, \n",
|
||
" 1.,\n",
|
||
" group_by=np.repeat(np.arange(500), 2),\n",
|
||
" call_seq=call_seq, **kwargs\n",
|
||
" ).call_seq"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0 1 2\n",
|
||
"2020-01-02 0 1 2\n",
|
||
"2020-01-03 0 1 2\n",
|
||
"2020-01-04 0 1 2\n",
|
||
"2020-01-05 0 1 2\n",
|
||
"46.2 ms ± 838 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
" a b c\n",
|
||
"2020-01-01 2 1 0\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 2 1 0\n",
|
||
"2020-01-04 2 1 0\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"46.4 ms ± 683 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
" a b c\n",
|
||
"2020-01-01 0 1 2\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 1 0 2\n",
|
||
"2020-01-04 2 0 1\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"55.1 ms ± 849 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(test_call_seq(CallSeqType.Default))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default)\n",
|
||
"\n",
|
||
"print(test_call_seq(CallSeqType.Reversed))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Reversed)\n",
|
||
"\n",
|
||
"print(test_call_seq(CallSeqType.Random))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Random)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 53,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"@njit\n",
|
||
"def pre_segment_func1_nb(c, *args):\n",
|
||
" c.call_seq_now[:] = np.arange(c.to_col - c.from_col - 1, -1, -1)\n",
|
||
" return ()\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def pre_segment_func2_nb(c, *args):\n",
|
||
" c.call_seq_now[:] = np.copy(c.call_seq_now[::-1])\n",
|
||
" return ()\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def pre_segment_func3_nb(c, *args):\n",
|
||
" call_seq_now = c.call_seq_now\n",
|
||
" n_cols = c.to_col - c.from_col\n",
|
||
" for k in range(n_cols):\n",
|
||
" call_seq_now[k] = n_cols - k - 1\n",
|
||
" return ()\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def pre_segment_func4_nb(c, *args):\n",
|
||
" np.random.shuffle(c.call_seq_now)\n",
|
||
" return ()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 54,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 2 1 0\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 2 1 0\n",
|
||
"2020-01-04 2 1 0\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"262 ms ± 109 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"206 ms ± 2.16 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
" a b c\n",
|
||
"2020-01-01 2 1 0\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 2 1 0\n",
|
||
"2020-01-04 2 1 0\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"209 ms ± 1.67 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"211 ms ± 1.97 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
" a b c\n",
|
||
"2020-01-01 2 1 0\n",
|
||
"2020-01-02 2 1 0\n",
|
||
"2020-01-03 2 1 0\n",
|
||
"2020-01-04 2 1 0\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"94.2 ms ± 1.26 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"99.2 ms ± 394 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 2 0\n",
|
||
"2020-01-02 0 1 2\n",
|
||
"2020-01-03 1 0 2\n",
|
||
"2020-01-04 1 0 2\n",
|
||
"2020-01-05 2 1 0\n",
|
||
"148 ms ± 2.78 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"148 ms ± 3.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func1_nb))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func1_nb)\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func1_nb, row_wise=True)\n",
|
||
"\n",
|
||
"print(test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func2_nb))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func2_nb)\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func2_nb, row_wise=True)\n",
|
||
"\n",
|
||
"print(test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func3_nb))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func3_nb)\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func3_nb, row_wise=True)\n",
|
||
"\n",
|
||
"print(test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func4_nb))\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func4_nb) # in-place fastest\n",
|
||
"%timeit big_test_call_seq(CallSeqType.Default, pre_segment_func_nb=pre_segment_func4_nb, row_wise=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Index([0], dtype='int64')\n",
|
||
"1\n",
|
||
"Index([0], dtype='int64', name='iteration_idx')\n",
|
||
"2\n",
|
||
"Index(['first'], dtype='object', name='custom')\n",
|
||
"2\n",
|
||
"Index([0, 1, 2], dtype='int64', name='iteration_idx')\n",
|
||
"2\n",
|
||
"Index(['first', 'second', 'third'], dtype='object', name='custom')\n",
|
||
"2\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, np.inf,\n",
|
||
" target_shape=(5,))\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, np.inf,\n",
|
||
" target_shape=(5, 1))\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, np.inf,\n",
|
||
" target_shape=(5, 1), keys=pd.Index(['first'], name='custom'))\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, np.inf,\n",
|
||
" target_shape=(5, 3))\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, np.inf,\n",
|
||
" target_shape=(5, 3), keys=pd.Index(['first', 'second', 'third'], name='custom'))\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 200.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 133.333333 3.0 0.0 0\n",
|
||
"3 3 3 0 66.666667 4.0 0.0 1\n",
|
||
"4 4 4 0 53.333333 5.0 0.0 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 200.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 133.333333 3.0 0.0 0\n",
|
||
"3 3 3 0 66.666667 4.0 0.0 1\n",
|
||
"4 4 4 0 53.333333 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(price, order_func_nb, np.inf)\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(price, order_func_nb, np.inf, row_wise=True)\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 200.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 133.333333 3.0 0.0 0\n",
|
||
"3 3 3 0 66.666667 4.0 0.0 1\n",
|
||
"4 4 4 0 53.333333 5.0 0.0 0\n",
|
||
"5 5 0 1 100.000000 1.0 0.0 0\n",
|
||
"6 6 1 1 200.000000 2.0 0.0 1\n",
|
||
"7 7 2 1 133.333333 3.0 0.0 0\n",
|
||
"8 8 3 1 66.666667 4.0 0.0 1\n",
|
||
"9 9 4 1 53.333333 5.0 0.0 0\n",
|
||
"10 10 0 2 100.000000 1.0 0.0 0\n",
|
||
"11 11 1 2 200.000000 2.0 0.0 1\n",
|
||
"12 12 2 2 133.333333 3.0 0.0 0\n",
|
||
"13 13 3 2 66.666667 4.0 0.0 1\n",
|
||
"14 14 4 2 53.333333 5.0 0.0 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 0 1 100.000000 1.0 0.0 0\n",
|
||
"2 2 0 2 100.000000 1.0 0.0 0\n",
|
||
"3 3 1 0 200.000000 2.0 0.0 1\n",
|
||
"4 4 1 1 200.000000 2.0 0.0 1\n",
|
||
"5 5 1 2 200.000000 2.0 0.0 1\n",
|
||
"6 6 2 0 133.333333 3.0 0.0 0\n",
|
||
"7 7 2 1 133.333333 3.0 0.0 0\n",
|
||
"8 8 2 2 133.333333 3.0 0.0 0\n",
|
||
"9 9 3 0 66.666667 4.0 0.0 1\n",
|
||
"10 10 3 1 66.666667 4.0 0.0 1\n",
|
||
"11 11 3 2 66.666667 4.0 0.0 1\n",
|
||
"12 12 4 0 53.333333 5.0 0.0 0\n",
|
||
"13 13 4 1 53.333333 5.0 0.0 0\n",
|
||
"14 14 4 2 53.333333 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(price_wide, order_func_nb, np.inf)\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(price_wide, order_func_nb, np.inf, row_wise=True)\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 0 1 100.000000 1.0 0.0 0\n",
|
||
"2 2 1 0 200.000000 2.0 0.0 1\n",
|
||
"3 3 1 1 200.000000 2.0 0.0 1\n",
|
||
"4 4 2 0 133.333333 3.0 0.0 0\n",
|
||
"5 5 2 1 133.333333 3.0 0.0 0\n",
|
||
"6 6 3 0 66.666667 4.0 0.0 1\n",
|
||
"7 7 3 1 66.666667 4.0 0.0 1\n",
|
||
"8 8 4 0 53.333333 5.0 0.0 0\n",
|
||
"9 9 4 1 53.333333 5.0 0.0 0\n",
|
||
"10 10 0 2 100.000000 1.0 0.0 0\n",
|
||
"11 11 1 2 200.000000 2.0 0.0 1\n",
|
||
"12 12 2 2 133.333333 3.0 0.0 0\n",
|
||
"13 13 3 2 66.666667 4.0 0.0 1\n",
|
||
"14 14 4 2 53.333333 5.0 0.0 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 0 1 100.000000 1.0 0.0 0\n",
|
||
"2 2 0 2 100.000000 1.0 0.0 0\n",
|
||
"3 3 1 0 200.000000 2.0 0.0 1\n",
|
||
"4 4 1 1 200.000000 2.0 0.0 1\n",
|
||
"5 5 1 2 200.000000 2.0 0.0 1\n",
|
||
"6 6 2 0 133.333333 3.0 0.0 0\n",
|
||
"7 7 2 1 133.333333 3.0 0.0 0\n",
|
||
"8 8 2 2 133.333333 3.0 0.0 0\n",
|
||
"9 9 3 0 66.666667 4.0 0.0 1\n",
|
||
"10 10 3 1 66.666667 4.0 0.0 1\n",
|
||
"11 11 3 2 66.666667 4.0 0.0 1\n",
|
||
"12 12 4 0 53.333333 5.0 0.0 0\n",
|
||
"13 13 4 1 53.333333 5.0 0.0 0\n",
|
||
"14 14 4 2 53.333333 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, np.inf,\n",
|
||
" group_by=np.array([0, 0, 1]))\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, np.inf,\n",
|
||
" group_by=np.array([0, 0, 1]), row_wise=True)\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 1 0 200.000000 2.0 0.0 1\n",
|
||
"2 2 2 0 133.333333 3.0 0.0 0\n",
|
||
"3 3 3 0 66.666667 4.0 0.0 1\n",
|
||
"4 4 4 0 53.333333 5.0 0.0 0\n",
|
||
"5 5 0 2 100.000000 1.0 0.0 0\n",
|
||
"6 6 1 2 200.000000 2.0 0.0 1\n",
|
||
"7 7 2 2 133.333333 3.0 0.0 0\n",
|
||
"8 8 3 2 66.666667 4.0 0.0 1\n",
|
||
"9 9 4 2 53.333333 5.0 0.0 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 100.000000 1.0 0.0 0\n",
|
||
"1 1 0 2 100.000000 1.0 0.0 0\n",
|
||
"2 2 1 0 200.000000 2.0 0.0 1\n",
|
||
"3 3 1 2 200.000000 2.0 0.0 1\n",
|
||
"4 4 2 0 133.333333 3.0 0.0 0\n",
|
||
"5 5 2 2 133.333333 3.0 0.0 0\n",
|
||
"6 6 3 0 66.666667 4.0 0.0 1\n",
|
||
"7 7 3 2 66.666667 4.0 0.0 1\n",
|
||
"8 8 4 0 53.333333 5.0 0.0 0\n",
|
||
"9 9 4 2 53.333333 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, np.inf,\n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True)\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, np.inf,\n",
|
||
" group_by=np.array([0, 0, 1]), cash_sharing=True, row_wise=True)\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[1.] 25.0\n",
|
||
"[2.] -33.33333333333333\n",
|
||
"[3.] -12.5\n",
|
||
"[4.] -6.666666666666668\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 25.000000 3.0 0.0 1\n",
|
||
"2 2 2 0 8.333333 4.0 0.0 1\n",
|
||
"3 3 3 0 4.166667 5.0 0.0 1\n",
|
||
"[1.] 25.0\n",
|
||
"[2.] -33.33333333333333\n",
|
||
"[3.] -12.5\n",
|
||
"[4.] -6.666666666666668\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 25.000000 3.0 0.0 1\n",
|
||
"2 2 2 0 8.333333 4.0 0.0 1\n",
|
||
"3 3 3 0 4.166667 5.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"@njit\n",
|
||
"def target_val_pre_segment_func_nb(c, val_price):\n",
|
||
" c.last_val_price[c.from_col:c.to_col] = val_price[c.i]\n",
|
||
" return ()\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def target_val_order_func_nb(c):\n",
|
||
" print(c.last_val_price[c.from_col:c.to_col], 50. / c.close[c.i, c.col] - c.position_now)\n",
|
||
" return order_nb(size=50., size_type=SizeType.TargetValue, price=c.close[c.i, c.col])\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_val_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_val_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[:-1],) # lagged valuation price\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_val_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_val_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[:-1],), row_wise=True\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[2.] 25.0\n",
|
||
"[3.] -8.333333333333332\n",
|
||
"[4.] -4.166666666666668\n",
|
||
"[5.] -2.5\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 25.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 8.333333 3.0 0.0 1\n",
|
||
"2 2 2 0 4.166667 4.0 0.0 1\n",
|
||
"3 3 3 0 2.500000 5.0 0.0 1\n",
|
||
"[2.] 25.0\n",
|
||
"[3.] -8.333333333333332\n",
|
||
"[4.] -4.166666666666668\n",
|
||
"[5.] -2.5\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 25.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 8.333333 3.0 0.0 1\n",
|
||
"2 2 2 0 4.166667 4.0 0.0 1\n",
|
||
"3 3 3 0 2.500000 5.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_val_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_val_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[1:],) # current order price\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_val_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_val_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[1:],), row_wise=True\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[1.] 25.0\n",
|
||
"[2.] -33.33333333333333\n",
|
||
"[3.] -6.25\n",
|
||
"[4.] -7.5\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000 2.0 0.0 0\n",
|
||
"1 1 1 0 25.000 3.0 0.0 1\n",
|
||
"2 2 3 0 3.125 5.0 0.0 1\n",
|
||
"[1.] 25.0\n",
|
||
"[2.] -33.33333333333333\n",
|
||
"[3.] -6.25\n",
|
||
"[4.] -7.5\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 50.000 2.0 0.0 0\n",
|
||
"1 1 1 0 25.000 3.0 0.0 1\n",
|
||
"2 2 3 0 3.125 5.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"@njit\n",
|
||
"def target_pct_pre_segment_func_nb(c, val_price):\n",
|
||
" c.last_val_price[c.from_col:c.to_col] = val_price[c.i]\n",
|
||
" return ()\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def target_pct_order_func_nb(c):\n",
|
||
" print(c.last_val_price[c.from_col:c.to_col], 0.5 * c.value_now / c.close[c.i, c.col] - c.position_now)\n",
|
||
" return order_nb(size=0.5, size_type=SizeType.TargetPercent, price=c.close[c.i, c.col])\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_pct_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_pct_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[:-1],) # lagged valuation price\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_pct_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_pct_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[:-1],), row_wise=True\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[2.] 25.0\n",
|
||
"[3.] -4.166666666666668\n",
|
||
"[4.] -2.604166666666668\n",
|
||
"[5.] -1.8229166666666643\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 25.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 4.166667 3.0 0.0 1\n",
|
||
"2 2 2 0 2.604167 4.0 0.0 1\n",
|
||
"3 3 3 0 1.822917 5.0 0.0 1\n",
|
||
"[2.] 25.0\n",
|
||
"[3.] -4.166666666666668\n",
|
||
"[4.] -2.604166666666668\n",
|
||
"[5.] -1.8229166666666643\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 25.000000 2.0 0.0 0\n",
|
||
"1 1 1 0 4.166667 3.0 0.0 1\n",
|
||
"2 2 2 0 2.604167 4.0 0.0 1\n",
|
||
"3 3 3 0 1.822917 5.0 0.0 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_pct_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_pct_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[1:],) # current order price\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price.iloc[1:], target_pct_order_func_nb, \n",
|
||
" pre_segment_func_nb=target_pct_pre_segment_func_nb,\n",
|
||
" pre_segment_args=(price.values[1:],), row_wise=True\n",
|
||
")\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 2 0 1.0 3.0 0.0 0\n",
|
||
"2 2 4 0 1.0 5.0 0.0 0\n",
|
||
" id idx col size price fees side\n",
|
||
"0 0 0 0 1.0 1.0 0.0 0\n",
|
||
"1 1 2 0 1.0 3.0 0.0 0\n",
|
||
"2 2 4 0 1.0 5.0 0.0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, 1.,\n",
|
||
" segment_mask=pd.Series([True, False, True, False, True]))\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price, order_func_nb, 1.,\n",
|
||
" segment_mask=pd.Series([True, False, True, False, True]), row_wise=True)\n",
|
||
"print(portfolio.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"preparing simulation\n",
|
||
"\tpreparing group 0\n",
|
||
"\t\tpreparing segment 0 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 2 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 3 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 4 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\tpreparing group 1\n",
|
||
"\t\tpreparing segment 0 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\t\tpreparing segment 1 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\t\tpreparing segment 2 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\t\tpreparing segment 3 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\t\tpreparing segment 4 (row)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"[1] [2] [10] [15]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"@njit\n",
|
||
"def pre_sim_func_nb(c, sim_i):\n",
|
||
" print('preparing simulation')\n",
|
||
" sim_i[0] += 1\n",
|
||
" return sim_i,\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def group_pre_sim_func_nb(c, sim_i, group_i):\n",
|
||
" print('\\tpreparing group', c.group)\n",
|
||
" group_i[0] += 1\n",
|
||
" return sim_i, group_i\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def pre_segment_func_nb(c, sim_i, group_i, segment_i):\n",
|
||
" print('\\t\\tpreparing segment', c.i, '(row)')\n",
|
||
" segment_i[0] += 1\n",
|
||
" return sim_i, group_i, segment_i\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def order_func_nb(c, sim_i, group_i, segment_i, order_i):\n",
|
||
" print('\\t\\t\\tprocessing order', c.call_idx, 'at column', c.col)\n",
|
||
" order_i[0] += 1\n",
|
||
" return NoOrder\n",
|
||
"\n",
|
||
"sim_i = np.array([0])\n",
|
||
"group_i = np.array([0])\n",
|
||
"segment_i = np.array([0])\n",
|
||
"order_i = np.array([0])\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, order_i, \n",
|
||
" group_by=np.array([0, 0, 1]), \n",
|
||
" pre_sim_func_nb=pre_sim_func_nb, pre_sim_args=(sim_i,),\n",
|
||
" pre_group_func_nb=group_pre_sim_func_nb, pre_group_args=(group_i,),\n",
|
||
" pre_segment_func_nb=pre_segment_func_nb, pre_segment_args=(segment_i,)\n",
|
||
")\n",
|
||
"print(sim_i, group_i, segment_i, order_i)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"preparing simulation\n",
|
||
"\tpreparing row 0\n",
|
||
"\t\tpreparing segment 0 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\tpreparing row 1\n",
|
||
"\t\tpreparing segment 0 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\tpreparing row 2\n",
|
||
"\t\tpreparing segment 0 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\tpreparing row 3\n",
|
||
"\t\tpreparing segment 0 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"\tpreparing row 4\n",
|
||
"\t\tpreparing segment 0 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 0\n",
|
||
"\t\t\tprocessing order 1 at column 1\n",
|
||
"\t\tpreparing segment 1 (group)\n",
|
||
"\t\t\tprocessing order 0 at column 2\n",
|
||
"[1] [5] [10] [15]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"@njit\n",
|
||
"def pre_sim_func_nb(c, sim_i):\n",
|
||
" print('preparing simulation')\n",
|
||
" sim_i[0] += 1\n",
|
||
" return sim_i,\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def row_pre_sim_func_nb(c, sim_i, row_i):\n",
|
||
" print('\\tpreparing row', c.i)\n",
|
||
" row_i[0] += 1\n",
|
||
" return sim_i, row_i\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def pre_segment_func_nb(c, sim_i, row_i, segment_i):\n",
|
||
" print('\\t\\tpreparing segment', c.group, '(group)')\n",
|
||
" segment_i[0] += 1\n",
|
||
" return sim_i, row_i, segment_i\n",
|
||
"\n",
|
||
"@njit\n",
|
||
"def order_func_nb(c, sim_i, row_i, segment_i, order_i):\n",
|
||
" print('\\t\\t\\tprocessing order', c.call_idx, 'at column', c.col)\n",
|
||
" order_i[0] += 1\n",
|
||
" return NoOrder\n",
|
||
"\n",
|
||
"sim_i = np.array([0])\n",
|
||
"row_i = np.array([0])\n",
|
||
"segment_i = np.array([0])\n",
|
||
"order_i = np.array([0])\n",
|
||
"\n",
|
||
"portfolio = vbt.Portfolio.from_order_func(\n",
|
||
" price_wide, order_func_nb, order_i, \n",
|
||
" group_by=np.array([0, 0, 1]), \n",
|
||
" pre_sim_func_nb=pre_sim_func_nb, pre_sim_args=(sim_i,),\n",
|
||
" pre_row_func_nb=row_pre_sim_func_nb, pre_row_args=(row_i,),\n",
|
||
" pre_segment_func_nb=pre_segment_func_nb, pre_segment_args=(segment_i,),\n",
|
||
" row_wise=True\n",
|
||
")\n",
|
||
"print(sim_i, row_i, segment_i, order_i)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## methods and properties"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"price_na = pd.DataFrame({\n",
|
||
" 'a': [np.nan, 2., 3., 4., 5.],\n",
|
||
" 'b': [1., 2., np.nan, 4., 5.],\n",
|
||
" 'c': [1., 2., 3., 4., np.nan]\n",
|
||
"}, index=price.index)\n",
|
||
"order_size = pd.Series([1., 0.1, -1., -0.1, 1.])\n",
|
||
"directions = ['longonly', 'shortonly', 'both']\n",
|
||
"group_by = pd.Index(['first', 'first', 'second'], name='group')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 0.1 2.02 0.10202 0\n",
|
||
"1 1 0 2 0.1 2.97 0.10297 1\n",
|
||
"2 2 0 4 1.0 5.05 0.15050 0\n",
|
||
"3 3 1 0 1.0 0.99 0.10990 1\n",
|
||
"4 4 1 1 0.1 1.98 0.10198 1\n",
|
||
"5 5 1 3 0.1 4.04 0.10404 0\n",
|
||
"6 6 1 4 1.0 4.95 0.14950 1\n",
|
||
"7 7 2 0 1.0 1.01 0.11010 0\n",
|
||
"8 8 2 1 0.1 2.02 0.10202 0\n",
|
||
"9 9 2 2 1.0 2.97 0.12970 1\n",
|
||
"10 10 2 3 0.1 3.96 0.10396 1\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 0 1 0.1 2.02 0.10202 0\n",
|
||
"1 1 0 2 0.1 2.97 0.10297 1\n",
|
||
"2 2 0 4 1.0 5.05 0.15050 0\n",
|
||
"3 3 1 0 1.0 0.99 0.10990 1\n",
|
||
"4 4 1 1 0.1 1.98 0.10198 1\n",
|
||
"5 5 1 3 0.1 4.04 0.10404 0\n",
|
||
"6 6 1 4 1.0 4.95 0.14950 1\n",
|
||
"7 7 2 0 1.0 1.01 0.11010 0\n",
|
||
"8 8 2 1 0.1 2.02 0.10202 0\n",
|
||
"9 9 2 2 1.0 2.97 0.12970 1\n",
|
||
"10 10 2 3 0.1 3.96 0.10396 1\n",
|
||
" id col idx size price fees side\n",
|
||
"0 0 1 0 1.0 0.99 0.10990 1\n",
|
||
"1 1 1 1 0.1 1.98 0.10198 1\n",
|
||
"2 2 0 1 0.1 2.02 0.10202 0\n",
|
||
"3 3 0 2 0.1 2.97 0.10297 1\n",
|
||
"4 4 1 3 0.1 4.04 0.10404 0\n",
|
||
"5 5 1 4 1.0 4.95 0.14950 1\n",
|
||
"6 6 0 4 1.0 5.05 0.15050 0\n",
|
||
"7 7 2 0 1.0 1.01 0.11010 0\n",
|
||
"8 8 2 1 0.1 2.02 0.10202 0\n",
|
||
"9 9 2 2 1.0 2.97 0.12970 1\n",
|
||
"10 10 2 3 0.1 3.96 0.10396 1\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio = vbt.Portfolio.from_orders(\n",
|
||
" price_na, order_size, size_type='amount', direction=directions,\n",
|
||
" fees=0.01, fixed_fees=0.1, slippage=0.01, log=True,\n",
|
||
" call_seq='reversed', group_by=None,\n",
|
||
" init_cash=[100., 100., 100.], freq='1D'\n",
|
||
") # independent\n",
|
||
"print(portfolio.orders.records)\n",
|
||
"\n",
|
||
"portfolio_grouped = vbt.Portfolio.from_orders(\n",
|
||
" price_na, order_size, size_type='amount', direction=directions,\n",
|
||
" fees=0.01, fixed_fees=0.1, slippage=0.01, log=True,\n",
|
||
" call_seq='reversed', group_by=group_by, cash_sharing=False,\n",
|
||
" init_cash=[100., 100., 100.], freq='1D'\n",
|
||
") # grouped\n",
|
||
"print(portfolio_grouped.orders.records)\n",
|
||
"\n",
|
||
"portfolio_shared = vbt.Portfolio.from_orders(\n",
|
||
" price_na, order_size, size_type='amount', direction=directions,\n",
|
||
" fees=0.01, fixed_fees=0.1, slippage=0.01, log=True,\n",
|
||
" call_seq='reversed', group_by=group_by, cash_sharing=True,\n",
|
||
" init_cash=[200., 100.], freq='1D'\n",
|
||
") # shared\n",
|
||
"print(portfolio_shared.orders.records)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(1000000,)\n",
|
||
"(1000000,)\n",
|
||
"(1000000,)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"big_group_by = np.repeat(np.arange(500), 2)\n",
|
||
"big_portfolio = vbt.Portfolio.from_orders(\n",
|
||
" big_price_wide, big_order_size)\n",
|
||
"print(big_portfolio.orders.values.shape)\n",
|
||
"\n",
|
||
"big_portfolio_grouped = vbt.Portfolio.from_orders(\n",
|
||
" big_price_wide, big_order_size, group_by=big_group_by)\n",
|
||
"print(big_portfolio_grouped.orders.values.shape)\n",
|
||
"\n",
|
||
"big_portfolio_shared = vbt.Portfolio.from_orders(\n",
|
||
" big_price_wide, big_order_size, group_by=big_group_by, cash_sharing=True)\n",
|
||
"print(big_portfolio_shared.orders.values.shape)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',\n",
|
||
" '2020-01-05'],\n",
|
||
" dtype='datetime64[ns]', freq=None)\n",
|
||
"Index(['a', 'b', 'c'], dtype='object')\n",
|
||
"2\n",
|
||
"None\n",
|
||
"True\n",
|
||
"True\n",
|
||
"True\n",
|
||
"DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',\n",
|
||
" '2020-01-05'],\n",
|
||
" dtype='datetime64[ns]', freq=None)\n",
|
||
"Index(['a', 'b', 'c'], dtype='object')\n",
|
||
"2\n",
|
||
"Index(['first', 'first', 'second'], dtype='object', name='group')\n",
|
||
"True\n",
|
||
"True\n",
|
||
"True\n",
|
||
"DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',\n",
|
||
" '2020-01-05'],\n",
|
||
" dtype='datetime64[ns]', freq=None)\n",
|
||
"Index(['a', 'b', 'c'], dtype='object')\n",
|
||
"2\n",
|
||
"Index(['first', 'first', 'second'], dtype='object', name='group')\n",
|
||
"False\n",
|
||
"True\n",
|
||
"False\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.wrapper.index)\n",
|
||
"print(portfolio.wrapper.columns)\n",
|
||
"print(portfolio.wrapper.ndim)\n",
|
||
"print(portfolio.wrapper.grouper.group_by)\n",
|
||
"print(portfolio.wrapper.grouper.allow_enable)\n",
|
||
"print(portfolio.wrapper.grouper.allow_disable)\n",
|
||
"print(portfolio.wrapper.grouper.allow_modify)\n",
|
||
"\n",
|
||
"print(portfolio_grouped.wrapper.index)\n",
|
||
"print(portfolio_grouped.wrapper.columns)\n",
|
||
"print(portfolio_grouped.wrapper.ndim)\n",
|
||
"print(portfolio_grouped.wrapper.grouper.group_by)\n",
|
||
"print(portfolio_grouped.wrapper.grouper.allow_enable)\n",
|
||
"print(portfolio_grouped.wrapper.grouper.allow_disable)\n",
|
||
"print(portfolio_grouped.wrapper.grouper.allow_modify)\n",
|
||
"\n",
|
||
"print(portfolio_shared.wrapper.index)\n",
|
||
"print(portfolio_shared.wrapper.columns)\n",
|
||
"print(portfolio_shared.wrapper.ndim)\n",
|
||
"print(portfolio_shared.wrapper.grouper.group_by)\n",
|
||
"print(portfolio_shared.wrapper.grouper.allow_enable)\n",
|
||
"print(portfolio_shared.wrapper.grouper.allow_disable)\n",
|
||
"print(portfolio_shared.wrapper.grouper.allow_modify)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 106,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 1 0 0.1 2.02 0.10202 0\n",
|
||
"1 1 2 0 0.1 2.97 0.10297 1\n",
|
||
"2 2 4 0 1.0 5.05 0.15050 0\n",
|
||
"3 3 0 1 1.0 0.99 0.10990 1\n",
|
||
"4 4 1 1 0.1 1.98 0.10198 1\n",
|
||
"5 5 3 1 0.1 4.04 0.10404 0\n",
|
||
"6 6 4 1 1.0 4.95 0.14950 1\n",
|
||
"7 7 0 2 1.0 1.01 0.11010 0\n",
|
||
"8 8 1 2 0.1 2.02 0.10202 0\n",
|
||
"9 9 2 2 1.0 2.97 0.12970 1\n",
|
||
"10 10 3 2 0.1 3.96 0.10396 1\n",
|
||
"a 3\n",
|
||
"b 4\n",
|
||
"c 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 5\n",
|
||
"b 5\n",
|
||
"c 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
"a 100.0\n",
|
||
"b 100.0\n",
|
||
"c 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 99.88010 99.87990\n",
|
||
"2020-01-02 99.89598 98.77612 100.77588\n",
|
||
"2020-01-03 99.89001 98.77612 101.71618\n",
|
||
"2020-01-04 99.89001 96.46808 101.70822\n",
|
||
"2020-01-05 99.68951 95.26858 101.70822\n",
|
||
"a 99.68951\n",
|
||
"b 95.26858\n",
|
||
"c 101.70822\n",
|
||
"Name: final_value, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.orders.records)\n",
|
||
"print(portfolio.orders.count())\n",
|
||
"print(portfolio.logs.count())\n",
|
||
"print(portfolio.close)\n",
|
||
"print(portfolio.init_cash)\n",
|
||
"print(portfolio.value())\n",
|
||
"print(portfolio.final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 107,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 1 0 0.1 2.02 0.10202 0\n",
|
||
"1 1 2 0 0.1 2.97 0.10297 1\n",
|
||
"2 2 4 0 1.0 5.05 0.15050 0\n",
|
||
"3\n",
|
||
"5\n",
|
||
"2020-01-01 NaN\n",
|
||
"2020-01-02 2.0\n",
|
||
"2020-01-03 3.0\n",
|
||
"2020-01-04 4.0\n",
|
||
"2020-01-05 5.0\n",
|
||
"Name: a, dtype: float64\n",
|
||
"100.0\n",
|
||
"2020-01-01 100.00000\n",
|
||
"2020-01-02 99.89598\n",
|
||
"2020-01-03 99.89001\n",
|
||
"2020-01-04 99.89001\n",
|
||
"2020-01-05 99.68951\n",
|
||
"Name: a, dtype: float64\n",
|
||
"99.68951\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio['a'].orders.records)\n",
|
||
"print(portfolio['a'].orders.count())\n",
|
||
"print(portfolio['a'].logs.count())\n",
|
||
"print(portfolio['a'].close)\n",
|
||
"print(portfolio['a'].init_cash)\n",
|
||
"print(portfolio['a'].value())\n",
|
||
"print(portfolio['a'].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 108,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 7 0 0 1.0 1.01 0.11010 0\n",
|
||
"1 8 1 0 0.1 2.02 0.10202 0\n",
|
||
"2 9 2 0 1.0 2.97 0.12970 1\n",
|
||
"3 10 3 0 0.1 3.96 0.10396 1\n",
|
||
"4\n",
|
||
"5\n",
|
||
"2020-01-01 1.0\n",
|
||
"2020-01-02 2.0\n",
|
||
"2020-01-03 3.0\n",
|
||
"2020-01-04 4.0\n",
|
||
"2020-01-05 NaN\n",
|
||
"Name: c, dtype: float64\n",
|
||
"100.0\n",
|
||
"2020-01-01 99.87990\n",
|
||
"2020-01-02 100.77588\n",
|
||
"2020-01-03 101.71618\n",
|
||
"2020-01-04 101.70822\n",
|
||
"2020-01-05 101.70822\n",
|
||
"Name: c, dtype: float64\n",
|
||
"101.70822\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio['c'].orders.records)\n",
|
||
"print(portfolio['c'].orders.count())\n",
|
||
"print(portfolio['c'].logs.count())\n",
|
||
"print(portfolio['c'].close)\n",
|
||
"print(portfolio['c'].init_cash)\n",
|
||
"print(portfolio['c'].value())\n",
|
||
"print(portfolio['c'].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 109,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 7 0 0 1.0 1.01 0.11010 0\n",
|
||
"1 8 1 0 0.1 2.02 0.10202 0\n",
|
||
"2 9 2 0 1.0 2.97 0.12970 1\n",
|
||
"3 10 3 0 0.1 3.96 0.10396 1\n",
|
||
"c 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"c 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
" c\n",
|
||
"2020-01-01 1.0\n",
|
||
"2020-01-02 2.0\n",
|
||
"2020-01-03 3.0\n",
|
||
"2020-01-04 4.0\n",
|
||
"2020-01-05 NaN\n",
|
||
"c 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
" c\n",
|
||
"2020-01-01 99.87990\n",
|
||
"2020-01-02 100.77588\n",
|
||
"2020-01-03 101.71618\n",
|
||
"2020-01-04 101.70822\n",
|
||
"2020-01-05 101.70822\n",
|
||
"c 101.70822\n",
|
||
"Name: final_value, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio[['c']].orders.records)\n",
|
||
"print(portfolio[['c']].orders.count())\n",
|
||
"print(portfolio[['c']].logs.count())\n",
|
||
"print(portfolio[['c']].close)\n",
|
||
"print(portfolio[['c']].init_cash)\n",
|
||
"print(portfolio[['c']].value())\n",
|
||
"print(portfolio[['c']].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 110,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 1 0 0.1 2.02 0.10202 0\n",
|
||
"1 1 2 0 0.1 2.97 0.10297 1\n",
|
||
"2 2 4 0 1.0 5.05 0.15050 0\n",
|
||
"3 3 0 1 1.0 0.99 0.10990 1\n",
|
||
"4 4 1 1 0.1 1.98 0.10198 1\n",
|
||
"5 5 3 1 0.1 4.04 0.10404 0\n",
|
||
"6 6 4 1 1.0 4.95 0.14950 1\n",
|
||
"7 7 0 2 1.0 1.01 0.11010 0\n",
|
||
"8 8 1 2 0.1 2.02 0.10202 0\n",
|
||
"9 9 2 2 1.0 2.97 0.12970 1\n",
|
||
"10 10 3 2 0.1 3.96 0.10396 1\n",
|
||
"group\n",
|
||
"first 7\n",
|
||
"second 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 10\n",
|
||
"second 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
"group\n",
|
||
"first 200.0\n",
|
||
"second 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group first second\n",
|
||
"2020-01-01 199.88010 99.87990\n",
|
||
"2020-01-02 198.67210 100.77588\n",
|
||
"2020-01-03 198.66613 101.71618\n",
|
||
"2020-01-04 196.35809 101.70822\n",
|
||
"2020-01-05 194.95809 101.70822\n",
|
||
"group\n",
|
||
"first 194.95809\n",
|
||
"second 101.70822\n",
|
||
"Name: final_value, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_grouped.orders.records)\n",
|
||
"print(portfolio_grouped.orders.count())\n",
|
||
"print(portfolio_grouped.logs.count())\n",
|
||
"print(portfolio_grouped.close)\n",
|
||
"print(portfolio_grouped.init_cash)\n",
|
||
"print(portfolio_grouped.value())\n",
|
||
"print(portfolio_grouped.final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 111,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 0 1 0 0.1 2.02 0.10202 0\n",
|
||
"1 1 2 0 0.1 2.97 0.10297 1\n",
|
||
"2 2 4 0 1.0 5.05 0.15050 0\n",
|
||
"3 3 0 1 1.0 0.99 0.10990 1\n",
|
||
"4 4 1 1 0.1 1.98 0.10198 1\n",
|
||
"5 5 3 1 0.1 4.04 0.10404 0\n",
|
||
"6 6 4 1 1.0 4.95 0.14950 1\n",
|
||
"7\n",
|
||
"10\n",
|
||
" a b\n",
|
||
"2020-01-01 NaN 1.0\n",
|
||
"2020-01-02 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN\n",
|
||
"2020-01-04 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0\n",
|
||
"200.0\n",
|
||
"2020-01-01 199.88010\n",
|
||
"2020-01-02 198.67210\n",
|
||
"2020-01-03 196.46613\n",
|
||
"2020-01-04 196.35809\n",
|
||
"2020-01-05 194.95809\n",
|
||
"Name: first, dtype: float64\n",
|
||
"194.95809\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_grouped['first'].orders.records)\n",
|
||
"print(portfolio_grouped['first'].orders.count())\n",
|
||
"print(portfolio_grouped['first'].logs.count())\n",
|
||
"print(portfolio_grouped['first'].close)\n",
|
||
"print(portfolio_grouped['first'].init_cash)\n",
|
||
"print(portfolio_grouped['first'].value())\n",
|
||
"print(portfolio_grouped['first'].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 112,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 7 0 0 1.0 1.01 0.11010 0\n",
|
||
"1 8 1 0 0.1 2.02 0.10202 0\n",
|
||
"2 9 2 0 1.0 2.97 0.12970 1\n",
|
||
"3 10 3 0 0.1 3.96 0.10396 1\n",
|
||
"4\n",
|
||
"5\n",
|
||
"2020-01-01 1.0\n",
|
||
"2020-01-02 2.0\n",
|
||
"2020-01-03 3.0\n",
|
||
"2020-01-04 4.0\n",
|
||
"2020-01-05 NaN\n",
|
||
"Name: c, dtype: float64\n",
|
||
"100.0\n",
|
||
"2020-01-01 99.87990\n",
|
||
"2020-01-02 100.77588\n",
|
||
"2020-01-03 101.71618\n",
|
||
"2020-01-04 101.70822\n",
|
||
"2020-01-05 101.70822\n",
|
||
"Name: second, dtype: float64\n",
|
||
"101.70822\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_grouped['second'].orders.records)\n",
|
||
"print(portfolio_grouped['second'].orders.count())\n",
|
||
"print(portfolio_grouped['second'].logs.count())\n",
|
||
"print(portfolio_grouped['second'].close)\n",
|
||
"print(portfolio_grouped['second'].init_cash)\n",
|
||
"print(portfolio_grouped['second'].value())\n",
|
||
"print(portfolio_grouped['second'].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 113,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" id idx col size price fees side\n",
|
||
"0 7 0 0 1.0 1.01 0.11010 0\n",
|
||
"1 8 1 0 0.1 2.02 0.10202 0\n",
|
||
"2 9 2 0 1.0 2.97 0.12970 1\n",
|
||
"3 10 3 0 0.1 3.96 0.10396 1\n",
|
||
"group\n",
|
||
"second 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"second 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
" c\n",
|
||
"2020-01-01 1.0\n",
|
||
"2020-01-02 2.0\n",
|
||
"2020-01-03 3.0\n",
|
||
"2020-01-04 4.0\n",
|
||
"2020-01-05 NaN\n",
|
||
"group\n",
|
||
"second 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group second\n",
|
||
"2020-01-01 99.87990\n",
|
||
"2020-01-02 100.77588\n",
|
||
"2020-01-03 101.71618\n",
|
||
"2020-01-04 101.70822\n",
|
||
"2020-01-05 101.70822\n",
|
||
"group\n",
|
||
"second 101.70822\n",
|
||
"Name: final_value, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_grouped[['second']].orders.records)\n",
|
||
"print(portfolio_grouped[['second']].orders.count())\n",
|
||
"print(portfolio_grouped[['second']].logs.count())\n",
|
||
"print(portfolio_grouped[['second']].close)\n",
|
||
"print(portfolio_grouped[['second']].init_cash)\n",
|
||
"print(portfolio_grouped[['second']].value())\n",
|
||
"print(portfolio_grouped[['second']].final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 62,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"3.42 ms ± 283 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"The slowest run took 17.43 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
|
||
"111 ms ± 89.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"3.37 ms ± 46.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.3 ms ± 1.99 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"6.41 ms ± 139 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"18.1 ms ± 366 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.iloc[0]\n",
|
||
"%timeit big_portfolio.iloc[:]\n",
|
||
"%timeit big_portfolio_grouped.iloc[0]\n",
|
||
"%timeit big_portfolio_grouped.iloc[:]\n",
|
||
"%timeit big_portfolio_shared.iloc[0]\n",
|
||
"%timeit big_portfolio_shared.iloc[:]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 114,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"False\n",
|
||
"False\n",
|
||
"True\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.cash_sharing)\n",
|
||
"print(portfolio_grouped.cash_sharing)\n",
|
||
"print(portfolio_shared.cash_sharing)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 115,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0 0 0\n",
|
||
"2020-01-02 0 0 0\n",
|
||
"2020-01-03 0 0 0\n",
|
||
"2020-01-04 0 0 0\n",
|
||
"2020-01-05 0 0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 1 0 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n",
|
||
" a b c\n",
|
||
"2020-01-01 1 0 0\n",
|
||
"2020-01-02 1 0 0\n",
|
||
"2020-01-03 1 0 0\n",
|
||
"2020-01-04 1 0 0\n",
|
||
"2020-01-05 1 0 0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.call_seq)\n",
|
||
"print(portfolio_grouped.call_seq)\n",
|
||
"print(portfolio_shared.call_seq)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 116,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 3\n",
|
||
"b 4\n",
|
||
"c 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 3\n",
|
||
"b 4\n",
|
||
"c 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 3\n",
|
||
"b 4\n",
|
||
"c 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 7\n",
|
||
"second 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 7\n",
|
||
"second 4\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 7\n",
|
||
"second 4\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.orders.count())\n",
|
||
"print(portfolio_grouped.get_orders(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_orders(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_orders(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.orders.count())\n",
|
||
"print(portfolio_shared.orders.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 117,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 5\n",
|
||
"b 5\n",
|
||
"c 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 5\n",
|
||
"b 5\n",
|
||
"c 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 5\n",
|
||
"b 5\n",
|
||
"c 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 10\n",
|
||
"second 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 10\n",
|
||
"second 5\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 10\n",
|
||
"second 5\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.logs.count())\n",
|
||
"print(portfolio_grouped.get_logs(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_logs(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_logs(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.logs.count())\n",
|
||
"print(portfolio_shared.logs.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 2\n",
|
||
"b 3\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 3\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 3\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 5\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 5\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 5\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.entry_trades.count())\n",
|
||
"print(portfolio_grouped.get_entry_trades(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_entry_trades(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_entry_trades(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.entry_trades.count())\n",
|
||
"print(portfolio_shared.entry_trades.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"397 ms ± 3.87 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.entry_trades"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 2\n",
|
||
"b 2\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 2\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 2\n",
|
||
"c 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 4\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 4\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 4\n",
|
||
"second 2\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.exit_trades.count())\n",
|
||
"print(portfolio_grouped.get_exit_trades(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_exit_trades(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_exit_trades(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.exit_trades.count())\n",
|
||
"print(portfolio_shared.exit_trades.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"13.8 ms ± 607 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.exit_trades"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 2\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 2\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 3\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 3\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 3\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.positions.count())\n",
|
||
"print(portfolio_grouped.get_positions(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_positions(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_positions(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.positions.count())\n",
|
||
"print(portfolio_shared.positions.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"28.4 ms ± 3 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.positions"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 120,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 1\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 1\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"a 1\n",
|
||
"b 1\n",
|
||
"c 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 1\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 1\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n",
|
||
"group\n",
|
||
"first 1\n",
|
||
"second 1\n",
|
||
"Name: count, dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.drawdowns.count())\n",
|
||
"print(portfolio_grouped.get_drawdowns(group_by=False).count())\n",
|
||
"print(portfolio_shared.get_drawdowns(group_by=False).count())\n",
|
||
"\n",
|
||
"print(portfolio.get_drawdowns(group_by=group_by).count())\n",
|
||
"print(portfolio_grouped.drawdowns.count())\n",
|
||
"print(portfolio_shared.drawdowns.count())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 72,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"39.9 ms ± 907 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.drawdowns"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 121,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.close)\n",
|
||
"print(portfolio_grouped.close)\n",
|
||
"print(portfolio_shared.close)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 122,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 NaN 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
" a b c\n",
|
||
"2020-01-01 NaN 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 2.0 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 4.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 2.0 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 4.0 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 NaN\n",
|
||
" a b c\n",
|
||
"2020-01-01 2.0 1.0 1.0\n",
|
||
"2020-01-02 2.0 2.0 2.0\n",
|
||
"2020-01-03 3.0 2.0 3.0\n",
|
||
"2020-01-04 4.0 4.0 4.0\n",
|
||
"2020-01-05 5.0 5.0 4.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.fill_close(ffill=False, bfill=False))\n",
|
||
"print(portfolio.fill_close(ffill=True, bfill=False))\n",
|
||
"print(portfolio.fill_close(ffill=False, bfill=True))\n",
|
||
"print(portfolio.fill_close(ffill=True, bfill=True))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 75,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"67.6 µs ± 1.39 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.fill_close()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 123,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.0 0.0 1.0\n",
|
||
"2020-01-02 0.1 0.0 0.1\n",
|
||
"2020-01-03 -0.1 0.0 -1.0\n",
|
||
"2020-01-04 0.0 0.0 -0.1\n",
|
||
"2020-01-05 1.0 0.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 1.0 0.0\n",
|
||
"2020-01-02 0.0 0.1 0.0\n",
|
||
"2020-01-03 0.0 0.0 0.0\n",
|
||
"2020-01-04 0.0 -0.1 0.0\n",
|
||
"2020-01-05 0.0 1.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -0.1 0.1\n",
|
||
"2020-01-03 -0.1 0.0 -1.0\n",
|
||
"2020-01-04 0.0 0.1 -0.1\n",
|
||
"2020-01-05 1.0 -1.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -0.1 0.1\n",
|
||
"2020-01-03 -0.1 0.0 -1.0\n",
|
||
"2020-01-04 0.0 0.1 -0.1\n",
|
||
"2020-01-05 1.0 -1.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -0.1 0.1\n",
|
||
"2020-01-03 -0.1 0.0 -1.0\n",
|
||
"2020-01-04 0.0 0.1 -0.1\n",
|
||
"2020-01-05 1.0 -1.0 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.asset_flow(direction='longonly'))\n",
|
||
"print(portfolio.asset_flow(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.asset_flow())\n",
|
||
"print(portfolio_grouped.asset_flow())\n",
|
||
"print(portfolio_shared.asset_flow())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 77,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"11 ms ± 539 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"10.6 ms ± 276 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"10.5 ms ± 148 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.asset_flow()\n",
|
||
"%timeit big_portfolio_grouped.asset_flow()\n",
|
||
"%timeit big_portfolio_shared.asset_flow()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 124,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.0 0.0 1.0\n",
|
||
"2020-01-02 0.1 0.0 1.1\n",
|
||
"2020-01-03 0.0 0.0 0.1\n",
|
||
"2020-01-04 0.0 0.0 0.0\n",
|
||
"2020-01-05 1.0 0.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 1.0 0.0\n",
|
||
"2020-01-02 0.0 1.1 0.0\n",
|
||
"2020-01-03 0.0 1.1 0.0\n",
|
||
"2020-01-04 0.0 1.0 0.0\n",
|
||
"2020-01-05 0.0 2.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -1.1 1.1\n",
|
||
"2020-01-03 0.0 -1.1 0.1\n",
|
||
"2020-01-04 0.0 -1.0 0.0\n",
|
||
"2020-01-05 1.0 -2.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -1.1 1.1\n",
|
||
"2020-01-03 0.0 -1.1 0.1\n",
|
||
"2020-01-04 0.0 -1.0 0.0\n",
|
||
"2020-01-05 1.0 -2.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.1 -1.1 1.1\n",
|
||
"2020-01-03 0.0 -1.1 0.1\n",
|
||
"2020-01-04 0.0 -1.0 0.0\n",
|
||
"2020-01-05 1.0 -2.0 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.assets(direction='longonly'))\n",
|
||
"print(portfolio.assets(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.assets())\n",
|
||
"print(portfolio_grouped.assets())\n",
|
||
"print(portfolio_shared.assets())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 79,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"14.4 ms ± 539 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.6 ms ± 265 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14 ms ± 50.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.assets()\n",
|
||
"%timeit big_portfolio_grouped.assets()\n",
|
||
"%timeit big_portfolio_shared.assets()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 127,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 False False True\n",
|
||
"2020-01-02 True False True\n",
|
||
"2020-01-03 False False True\n",
|
||
"2020-01-04 False False False\n",
|
||
"2020-01-05 True False False\n",
|
||
" a b c\n",
|
||
"2020-01-01 False True False\n",
|
||
"2020-01-02 False True False\n",
|
||
"2020-01-03 False True False\n",
|
||
"2020-01-04 False True False\n",
|
||
"2020-01-05 False True False\n",
|
||
" a b c\n",
|
||
"2020-01-01 False True True\n",
|
||
"2020-01-02 True True True\n",
|
||
"2020-01-03 False True True\n",
|
||
"2020-01-04 False True False\n",
|
||
"2020-01-05 True True False\n",
|
||
" a b c\n",
|
||
"2020-01-01 False True True\n",
|
||
"2020-01-02 True True True\n",
|
||
"2020-01-03 False True True\n",
|
||
"2020-01-04 False True False\n",
|
||
"2020-01-05 True True False\n",
|
||
" a b c\n",
|
||
"2020-01-01 False True True\n",
|
||
"2020-01-02 True True True\n",
|
||
"2020-01-03 False True True\n",
|
||
"2020-01-04 False True False\n",
|
||
"2020-01-05 True True False\n",
|
||
"group first second\n",
|
||
"2020-01-01 True True\n",
|
||
"2020-01-02 True True\n",
|
||
"2020-01-03 True True\n",
|
||
"2020-01-04 True False\n",
|
||
"2020-01-05 True False\n",
|
||
"group first second\n",
|
||
"2020-01-01 True True\n",
|
||
"2020-01-02 True True\n",
|
||
"2020-01-03 True True\n",
|
||
"2020-01-04 True False\n",
|
||
"2020-01-05 True False\n",
|
||
"group first second\n",
|
||
"2020-01-01 True True\n",
|
||
"2020-01-02 True True\n",
|
||
"2020-01-03 True True\n",
|
||
"2020-01-04 True False\n",
|
||
"2020-01-05 True False\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.position_mask(direction='longonly'))\n",
|
||
"print(portfolio.position_mask(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.position_mask())\n",
|
||
"print(portfolio_grouped.position_mask(group_by=False))\n",
|
||
"print(portfolio_shared.position_mask(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.position_mask(group_by=group_by))\n",
|
||
"print(portfolio_grouped.position_mask())\n",
|
||
"print(portfolio_shared.position_mask())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 81,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"14.8 ms ± 113 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"15.1 ms ± 462 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"15.6 ms ± 299 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"31.4 ms ± 275 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"31 ms ± 198 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"32 ms ± 208 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.position_mask()\n",
|
||
"%timeit big_portfolio_grouped.position_mask(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.position_mask(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.position_mask(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.position_mask()\n",
|
||
"%timeit big_portfolio_shared.position_mask()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 128,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 0.4\n",
|
||
"b 0.0\n",
|
||
"c 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"a 0.0\n",
|
||
"b 1.0\n",
|
||
"c 0.0\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"a 0.4\n",
|
||
"b 1.0\n",
|
||
"c 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"a 0.4\n",
|
||
"b 1.0\n",
|
||
"c 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"a 0.4\n",
|
||
"b 1.0\n",
|
||
"c 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"group\n",
|
||
"first 0.7\n",
|
||
"second 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"group\n",
|
||
"first 0.7\n",
|
||
"second 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n",
|
||
"group\n",
|
||
"first 0.7\n",
|
||
"second 0.6\n",
|
||
"Name: position_coverage, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.position_coverage(direction='longonly'))\n",
|
||
"print(portfolio.position_coverage(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.position_coverage())\n",
|
||
"print(portfolio_grouped.position_coverage(group_by=False))\n",
|
||
"print(portfolio_shared.position_coverage(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.position_coverage(group_by=group_by))\n",
|
||
"print(portfolio_grouped.position_coverage())\n",
|
||
"print(portfolio_shared.position_coverage())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 83,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"16.6 ms ± 1.51 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.8 ms ± 104 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"15 ms ± 116 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"34.1 ms ± 1.49 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"32.2 ms ± 1.15 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"33.4 ms ± 1.19 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.position_coverage()\n",
|
||
"%timeit big_portfolio_grouped.position_coverage(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.position_coverage(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.position_coverage(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.position_coverage()\n",
|
||
"%timeit big_portfolio_shared.position_coverage()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 129,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 -1.09990 -1.12010\n",
|
||
"2020-01-02 -0.30402 -0.29998 -0.30402\n",
|
||
"2020-01-03 0.19403 0.00000 2.84030\n",
|
||
"2020-01-04 0.00000 -0.29204 0.29204\n",
|
||
"2020-01-05 -5.20050 -5.09950 0.00000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.30402 0.09602 -0.30402\n",
|
||
"2020-01-03 0.19403 0.00000 2.84030\n",
|
||
"2020-01-04 0.00000 -0.50804 0.29204\n",
|
||
"2020-01-05 -5.20050 4.80050 0.00000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.30402 0.09602 -0.30402\n",
|
||
"2020-01-03 0.19403 0.00000 2.84030\n",
|
||
"2020-01-04 0.00000 -0.50804 0.29204\n",
|
||
"2020-01-05 -5.20050 4.80050 0.00000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.30402 0.09602 -0.30402\n",
|
||
"2020-01-03 0.19403 0.00000 2.84030\n",
|
||
"2020-01-04 0.00000 -0.50804 0.29204\n",
|
||
"2020-01-05 -5.20050 4.80050 0.00000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.20800 -0.30402\n",
|
||
"2020-01-03 0.19403 2.84030\n",
|
||
"2020-01-04 -0.50804 0.29204\n",
|
||
"2020-01-05 -0.40000 0.00000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.20800 -0.30402\n",
|
||
"2020-01-03 0.19403 2.84030\n",
|
||
"2020-01-04 -0.50804 0.29204\n",
|
||
"2020-01-05 -0.40000 0.00000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.88010 -1.12010\n",
|
||
"2020-01-02 -0.20800 -0.30402\n",
|
||
"2020-01-03 0.19403 2.84030\n",
|
||
"2020-01-04 -0.50804 0.29204\n",
|
||
"2020-01-05 -0.40000 0.00000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.cash_flow(free=True))\n",
|
||
"print(portfolio.cash_flow())\n",
|
||
"print(portfolio_grouped.cash_flow(group_by=False))\n",
|
||
"print(portfolio_shared.cash_flow(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.cash_flow(group_by=group_by))\n",
|
||
"print(portfolio_grouped.cash_flow())\n",
|
||
"print(portfolio_shared.cash_flow())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 122,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"14.4 ms ± 912 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"20.4 ms ± 144 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"14.6 ms ± 88.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"16.3 ms ± 81.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"17.9 ms ± 126 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"16.7 ms ± 118 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"20.1 ms ± 155 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.cash_flow()\n",
|
||
"%timeit big_portfolio.cash_flow(free=True)\n",
|
||
"%timeit big_portfolio_grouped.cash_flow(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.cash_flow(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.cash_flow(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.cash_flow()\n",
|
||
"%timeit big_portfolio_shared.cash_flow()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 130,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 100.0\n",
|
||
"b 100.0\n",
|
||
"c 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"a 100.0\n",
|
||
"b 100.0\n",
|
||
"c 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"a 200.0\n",
|
||
"b 200.0\n",
|
||
"c 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 200.0\n",
|
||
"second 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 200.0\n",
|
||
"second 100.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 200.0\n",
|
||
"second 100.0\n",
|
||
"Name: init_cash, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.get_init_cash())\n",
|
||
"print(portfolio_grouped.get_init_cash(group_by=False))\n",
|
||
"print(portfolio_shared.get_init_cash(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.get_init_cash(group_by=group_by))\n",
|
||
"print(portfolio_grouped.get_init_cash())\n",
|
||
"print(portfolio_shared.get_init_cash())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"53.9 µs ± 387 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"53.6 µs ± 187 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"870 µs ± 2.61 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"912 µs ± 2.62 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"57.9 µs ± 1.76 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"1.26 ms ± 20.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.get_init_cash()\n",
|
||
"%timeit big_portfolio_grouped.get_init_cash(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.get_init_cash(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.get_init_cash(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.get_init_cash()\n",
|
||
"%timeit big_portfolio_shared.get_init_cash()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 87,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"43.2 µs ± 125 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"42.9 µs ± 611 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"533 µs ± 13.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"737 µs ± 44.3 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"46.6 µs ± 617 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
|
||
"850 µs ± 37.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.get_init_cash()\n",
|
||
"%timeit big_portfolio_grouped.get_init_cash(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.get_init_cash(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.get_init_cash(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.get_init_cash()\n",
|
||
"%timeit big_portfolio_shared.get_init_cash()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 131,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 14000.0\n",
|
||
"b 12000.0\n",
|
||
"c 10000.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 26000.0\n",
|
||
"second 10000.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 26000.0\n",
|
||
"second 10000.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"a 14000.0\n",
|
||
"b 14000.0\n",
|
||
"c 14000.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 26000.0\n",
|
||
"second 26000.0\n",
|
||
"Name: init_cash, dtype: float64\n",
|
||
"group\n",
|
||
"first 26000.0\n",
|
||
"second 26000.0\n",
|
||
"Name: init_cash, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.Auto, group_by=None).init_cash)\n",
|
||
"\n",
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.Auto, group_by=group_by).init_cash)\n",
|
||
"\n",
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.Auto, group_by=group_by, cash_sharing=True).init_cash)\n",
|
||
"\n",
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.AutoAlign, group_by=None).init_cash)\n",
|
||
"\n",
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.AutoAlign, group_by=group_by).init_cash)\n",
|
||
"\n",
|
||
"print(vbt.Portfolio.from_orders(\n",
|
||
" price_na, 1000., init_cash=InitCashMode.AutoAlign, group_by=group_by, cash_sharing=True).init_cash)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 132,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 98.90010 98.87990\n",
|
||
"2020-01-02 99.69598 98.60012 98.57588\n",
|
||
"2020-01-03 99.89001 98.60012 101.41618\n",
|
||
"2020-01-04 99.89001 98.30808 101.70822\n",
|
||
"2020-01-05 94.68951 93.20858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 100.88010 98.87990\n",
|
||
"2020-01-02 99.69598 100.97612 98.57588\n",
|
||
"2020-01-03 99.89001 100.97612 101.41618\n",
|
||
"2020-01-04 99.89001 100.46808 101.70822\n",
|
||
"2020-01-05 94.68951 105.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 100.88010 98.87990\n",
|
||
"2020-01-02 99.69598 100.97612 98.57588\n",
|
||
"2020-01-03 99.89001 100.97612 101.41618\n",
|
||
"2020-01-04 99.89001 100.46808 101.70822\n",
|
||
"2020-01-05 94.68951 105.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 200.00000 200.88010 98.87990\n",
|
||
"2020-01-02 199.69598 200.97612 98.57588\n",
|
||
"2020-01-03 199.89001 200.97612 101.41618\n",
|
||
"2020-01-04 199.89001 200.46808 101.70822\n",
|
||
"2020-01-05 194.68951 205.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 200.88010 200.88010 98.87990\n",
|
||
"2020-01-02 200.67210 200.97612 98.57588\n",
|
||
"2020-01-03 200.86613 200.67210 101.41618\n",
|
||
"2020-01-04 200.35809 200.35809 101.70822\n",
|
||
"2020-01-05 199.95809 205.15859 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.88010 98.87990\n",
|
||
"2020-01-02 200.67210 98.57588\n",
|
||
"2020-01-03 200.86613 101.41618\n",
|
||
"2020-01-04 200.35809 101.70822\n",
|
||
"2020-01-05 199.95809 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.88010 98.87990\n",
|
||
"2020-01-02 200.67210 98.57588\n",
|
||
"2020-01-03 200.86613 101.41618\n",
|
||
"2020-01-04 200.35809 101.70822\n",
|
||
"2020-01-05 199.95809 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.88010 98.87990\n",
|
||
"2020-01-02 200.67210 98.57588\n",
|
||
"2020-01-03 200.86613 101.41618\n",
|
||
"2020-01-04 200.35809 101.70822\n",
|
||
"2020-01-05 199.95809 101.70822\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.cash(free=True))\n",
|
||
"print(portfolio.cash())\n",
|
||
"print(portfolio_grouped.cash(group_by=False))\n",
|
||
"print(portfolio_shared.cash(group_by=False))\n",
|
||
"print(portfolio_shared.cash(group_by=False, in_sim_order=True))\n",
|
||
"\n",
|
||
"print(portfolio.cash(group_by=group_by))\n",
|
||
"print(portfolio_grouped.cash())\n",
|
||
"print(portfolio_shared.cash())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 90,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"19.4 ms ± 920 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"18.3 ms ± 470 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"18.4 ms ± 2.12 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"17.6 ms ± 201 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"18.7 ms ± 303 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"18.3 ms ± 292 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"19.6 ms ± 1.75 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"21.7 ms ± 1.76 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.cash()\n",
|
||
"%timeit big_portfolio.cash(free=True)\n",
|
||
"%timeit big_portfolio_grouped.cash(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.cash(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.cash(group_by=False, in_sim_order=True)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.cash(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.cash()\n",
|
||
"%timeit big_portfolio_shared.cash()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 133,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.0 0.0 1.0\n",
|
||
"2020-01-02 0.2 0.0 2.2\n",
|
||
"2020-01-03 0.0 0.0 0.3\n",
|
||
"2020-01-04 0.0 0.0 0.0\n",
|
||
"2020-01-05 5.0 0.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 1.0 0.0\n",
|
||
"2020-01-02 0.0 2.2 0.0\n",
|
||
"2020-01-03 0.0 2.2 0.0\n",
|
||
"2020-01-04 0.0 4.0 0.0\n",
|
||
"2020-01-05 0.0 10.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.2 -2.2 2.2\n",
|
||
"2020-01-03 0.0 -2.2 0.3\n",
|
||
"2020-01-04 0.0 -4.0 0.0\n",
|
||
"2020-01-05 5.0 -10.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.2 -2.2 2.2\n",
|
||
"2020-01-03 0.0 -2.2 0.3\n",
|
||
"2020-01-04 0.0 -4.0 0.0\n",
|
||
"2020-01-05 5.0 -10.0 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 -1.0 1.0\n",
|
||
"2020-01-02 0.2 -2.2 2.2\n",
|
||
"2020-01-03 0.0 -2.2 0.3\n",
|
||
"2020-01-04 0.0 -4.0 0.0\n",
|
||
"2020-01-05 5.0 -10.0 0.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 -1.0 1.0\n",
|
||
"2020-01-02 -2.0 2.2\n",
|
||
"2020-01-03 -2.2 0.3\n",
|
||
"2020-01-04 -4.0 0.0\n",
|
||
"2020-01-05 -5.0 0.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 -1.0 1.0\n",
|
||
"2020-01-02 -2.0 2.2\n",
|
||
"2020-01-03 -2.2 0.3\n",
|
||
"2020-01-04 -4.0 0.0\n",
|
||
"2020-01-05 -5.0 0.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 -1.0 1.0\n",
|
||
"2020-01-02 -2.0 2.2\n",
|
||
"2020-01-03 -2.2 0.3\n",
|
||
"2020-01-04 -4.0 0.0\n",
|
||
"2020-01-05 -5.0 0.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.asset_value(direction='longonly'))\n",
|
||
"print(portfolio.asset_value(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.asset_value())\n",
|
||
"print(portfolio_grouped.asset_value(group_by=False))\n",
|
||
"print(portfolio_shared.asset_value(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.asset_value(group_by=group_by))\n",
|
||
"print(portfolio_grouped.asset_value())\n",
|
||
"print(portfolio_shared.asset_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 92,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"16.7 ms ± 331 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"19.4 ms ± 2.51 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"18.4 ms ± 1.48 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"34.4 ms ± 308 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"33.6 ms ± 428 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"34.7 ms ± 213 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.asset_value()\n",
|
||
"%timeit big_portfolio_grouped.asset_value(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.asset_value(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.asset_value(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.asset_value()\n",
|
||
"%timeit big_portfolio_shared.asset_value()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 134,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 0.0 0.010012\n",
|
||
"2020-01-02 0.002002 0.0 0.021831\n",
|
||
"2020-01-03 0.000000 0.0 0.002949\n",
|
||
"2020-01-04 0.000000 0.0 0.000000\n",
|
||
"2020-01-05 0.050156 0.0 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.0 0.010010 0.0\n",
|
||
"2020-01-02 0.0 0.021825 0.0\n",
|
||
"2020-01-03 0.0 0.021825 0.0\n",
|
||
"2020-01-04 0.0 0.039098 0.0\n",
|
||
"2020-01-05 0.0 0.096891 0.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.010214 0.010012\n",
|
||
"2020-01-02 0.002002 -0.022822 0.021831\n",
|
||
"2020-01-03 0.000000 -0.022822 0.002949\n",
|
||
"2020-01-04 0.000000 -0.042414 0.000000\n",
|
||
"2020-01-05 0.050156 -0.120180 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.010214 0.010012\n",
|
||
"2020-01-02 0.002002 -0.022822 0.021831\n",
|
||
"2020-01-03 0.000000 -0.022822 0.002949\n",
|
||
"2020-01-04 0.000000 -0.042414 0.000000\n",
|
||
"2020-01-05 0.050156 -0.120180 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.005053 0.010012\n",
|
||
"2020-01-02 0.001001 -0.011202 0.021831\n",
|
||
"2020-01-03 0.000000 -0.011202 0.002949\n",
|
||
"2020-01-04 0.000000 -0.020586 0.000000\n",
|
||
"2020-01-05 0.025039 -0.054583 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005053 0.010012\n",
|
||
"2020-01-02 -0.010189 0.021831\n",
|
||
"2020-01-03 -0.011208 0.002949\n",
|
||
"2020-01-04 -0.020598 0.000000\n",
|
||
"2020-01-05 -0.027338 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005053 0.010012\n",
|
||
"2020-01-02 -0.010189 0.021831\n",
|
||
"2020-01-03 -0.011208 0.002949\n",
|
||
"2020-01-04 -0.020598 0.000000\n",
|
||
"2020-01-05 -0.027338 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005053 0.010012\n",
|
||
"2020-01-02 -0.010189 0.021831\n",
|
||
"2020-01-03 -0.011208 0.002949\n",
|
||
"2020-01-04 -0.020598 0.000000\n",
|
||
"2020-01-05 -0.027338 0.000000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.gross_exposure(direction='longonly'))\n",
|
||
"print(portfolio.gross_exposure(direction='shortonly'))\n",
|
||
"\n",
|
||
"print(portfolio.gross_exposure())\n",
|
||
"print(portfolio_grouped.gross_exposure(group_by=False))\n",
|
||
"print(portfolio_shared.gross_exposure(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.gross_exposure(group_by=group_by))\n",
|
||
"print(portfolio_grouped.gross_exposure())\n",
|
||
"print(portfolio_shared.gross_exposure())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"54.6 ms ± 5.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"44.3 ms ± 1.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"44.2 ms ± 1.07 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"58.8 ms ± 2.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"55 ms ± 1.09 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"60.9 ms ± 1.87 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.gross_exposure()\n",
|
||
"%timeit big_portfolio_grouped.gross_exposure(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.gross_exposure(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.gross_exposure(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.gross_exposure()\n",
|
||
"%timeit big_portfolio_shared.gross_exposure()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 135,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.010010 0.010012\n",
|
||
"2020-01-02 0.002002 -0.021825 0.021831\n",
|
||
"2020-01-03 0.000000 -0.021825 0.002949\n",
|
||
"2020-01-04 0.000000 -0.039098 0.000000\n",
|
||
"2020-01-05 0.050156 -0.096891 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.010010 0.010012\n",
|
||
"2020-01-02 0.002002 -0.021825 0.021831\n",
|
||
"2020-01-03 0.000000 -0.021825 0.002949\n",
|
||
"2020-01-04 0.000000 -0.039098 0.000000\n",
|
||
"2020-01-05 0.050156 -0.096891 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.005002 0.010012\n",
|
||
"2020-01-02 0.001001 -0.010956 0.021831\n",
|
||
"2020-01-03 0.000000 -0.010956 0.002949\n",
|
||
"2020-01-04 0.000000 -0.019772 0.000000\n",
|
||
"2020-01-05 0.025039 -0.049211 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005002 0.010012\n",
|
||
"2020-01-02 -0.009965 0.021831\n",
|
||
"2020-01-03 -0.010962 0.002949\n",
|
||
"2020-01-04 -0.019783 0.000000\n",
|
||
"2020-01-05 -0.024611 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005002 0.010012\n",
|
||
"2020-01-02 -0.009965 0.021831\n",
|
||
"2020-01-03 -0.010962 0.002949\n",
|
||
"2020-01-04 -0.019783 0.000000\n",
|
||
"2020-01-05 -0.024611 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.005002 0.010012\n",
|
||
"2020-01-02 -0.009965 0.021831\n",
|
||
"2020-01-03 -0.010962 0.002949\n",
|
||
"2020-01-04 -0.019783 0.000000\n",
|
||
"2020-01-05 -0.024611 0.000000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.net_exposure())\n",
|
||
"print(portfolio_grouped.net_exposure(group_by=False))\n",
|
||
"print(portfolio_shared.net_exposure(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.net_exposure(group_by=group_by))\n",
|
||
"print(portfolio_grouped.net_exposure())\n",
|
||
"print(portfolio_shared.net_exposure())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"91.5 ms ± 1.76 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"90.4 ms ± 1.52 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"95.4 ms ± 4.26 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"129 ms ± 3.21 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"119 ms ± 1.51 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"127 ms ± 1.85 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.net_exposure()\n",
|
||
"%timeit big_portfolio_grouped.net_exposure(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.net_exposure(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.net_exposure(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.net_exposure()\n",
|
||
"%timeit big_portfolio_shared.net_exposure()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 136,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 99.88010 99.87990\n",
|
||
"2020-01-02 99.89598 98.77612 100.77588\n",
|
||
"2020-01-03 99.89001 98.77612 101.71618\n",
|
||
"2020-01-04 99.89001 96.46808 101.70822\n",
|
||
"2020-01-05 99.68951 95.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 100.00000 99.88010 99.87990\n",
|
||
"2020-01-02 99.89598 98.77612 100.77588\n",
|
||
"2020-01-03 99.89001 98.77612 101.71618\n",
|
||
"2020-01-04 99.89001 96.46808 101.70822\n",
|
||
"2020-01-05 99.68951 95.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 200.00000 199.88010 99.87990\n",
|
||
"2020-01-02 199.89598 198.77612 100.77588\n",
|
||
"2020-01-03 199.89001 198.77612 101.71618\n",
|
||
"2020-01-04 199.89001 196.46808 101.70822\n",
|
||
"2020-01-05 199.68951 195.26858 101.70822\n",
|
||
" a b c\n",
|
||
"2020-01-01 199.88010 199.88010 99.87990\n",
|
||
"2020-01-02 198.67210 198.77612 100.77588\n",
|
||
"2020-01-03 198.66613 198.67210 101.71618\n",
|
||
"2020-01-04 196.35809 196.35809 101.70822\n",
|
||
"2020-01-05 194.95809 195.15859 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 199.88010 99.87990\n",
|
||
"2020-01-02 198.67210 100.77588\n",
|
||
"2020-01-03 198.66613 101.71618\n",
|
||
"2020-01-04 196.35809 101.70822\n",
|
||
"2020-01-05 194.95809 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 199.88010 99.87990\n",
|
||
"2020-01-02 198.67210 100.77588\n",
|
||
"2020-01-03 198.66613 101.71618\n",
|
||
"2020-01-04 196.35809 101.70822\n",
|
||
"2020-01-05 194.95809 101.70822\n",
|
||
"group first second\n",
|
||
"2020-01-01 199.88010 99.87990\n",
|
||
"2020-01-02 198.67210 100.77588\n",
|
||
"2020-01-03 198.66613 101.71618\n",
|
||
"2020-01-04 196.35809 101.70822\n",
|
||
"2020-01-05 194.95809 101.70822\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.value())\n",
|
||
"print(portfolio_grouped.value(group_by=False))\n",
|
||
"print(portfolio_shared.value(group_by=False))\n",
|
||
"print(portfolio_shared.value(group_by=False, in_sim_order=True))\n",
|
||
"\n",
|
||
"print(portfolio.value(group_by=group_by))\n",
|
||
"print(portfolio_grouped.value())\n",
|
||
"print(portfolio_shared.value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"36.9 ms ± 1.21 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"35 ms ± 210 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"35.8 ms ± 81.1 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"46 ms ± 152 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"53.9 ms ± 626 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"50.4 ms ± 722 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"55.3 ms ± 941 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.value()\n",
|
||
"%timeit big_portfolio_grouped.value(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.value(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.value(group_by=False, in_sim_order=True)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.value(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.value()\n",
|
||
"%timeit big_portfolio_shared.value()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 137,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a -0.31049\n",
|
||
"b -4.73142\n",
|
||
"c 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n",
|
||
"a -0.31049\n",
|
||
"b -4.73142\n",
|
||
"c 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n",
|
||
"a -0.31049\n",
|
||
"b -4.73142\n",
|
||
"c 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n",
|
||
"group\n",
|
||
"first -5.04191\n",
|
||
"second 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n",
|
||
"group\n",
|
||
"first -5.04191\n",
|
||
"second 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n",
|
||
"group\n",
|
||
"first -5.04191\n",
|
||
"second 1.70822\n",
|
||
"Name: total_profit, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.total_profit())\n",
|
||
"print(portfolio_grouped.total_profit(group_by=False))\n",
|
||
"print(portfolio_shared.total_profit(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.total_profit(group_by=group_by))\n",
|
||
"print(portfolio_grouped.total_profit())\n",
|
||
"print(portfolio_shared.total_profit())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"12.3 ms ± 79.7 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"12.5 ms ± 190 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.5 ms ± 225 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"13.2 ms ± 224 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.6 ms ± 176 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"13.4 ms ± 217 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.total_profit()\n",
|
||
"%timeit big_portfolio_grouped.total_profit(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.total_profit(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.total_profit(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.total_profit()\n",
|
||
"%timeit big_portfolio_shared.total_profit()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 138,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 99.68951\n",
|
||
"b 95.26858\n",
|
||
"c 101.70822\n",
|
||
"Name: final_value, dtype: float64\n",
|
||
"a 99.68951\n",
|
||
"b 95.26858\n",
|
||
"c 101.70822\n",
|
||
"Name: final_value, dtype: float64\n",
|
||
"a 199.68951\n",
|
||
"b 195.26858\n",
|
||
"c 101.70822\n",
|
||
"Name: final_value, dtype: float64\n",
|
||
"group\n",
|
||
"first 194.95809\n",
|
||
"second 101.70822\n",
|
||
"Name: final_value, dtype: float64\n",
|
||
"group\n",
|
||
"first 194.95809\n",
|
||
"second 101.70822\n",
|
||
"Name: final_value, dtype: float64\n",
|
||
"group\n",
|
||
"first 194.95809\n",
|
||
"second 101.70822\n",
|
||
"Name: final_value, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.final_value())\n",
|
||
"print(portfolio_grouped.final_value(group_by=False))\n",
|
||
"print(portfolio_shared.final_value(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.final_value(group_by=group_by))\n",
|
||
"print(portfolio_grouped.final_value())\n",
|
||
"print(portfolio_shared.final_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"12.3 ms ± 159 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.2 ms ± 122 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.9 ms ± 128 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.1 ms ± 280 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12 ms ± 145 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.1 ms ± 231 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.final_value()\n",
|
||
"%timeit big_portfolio_grouped.final_value(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.final_value(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.final_value(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.final_value()\n",
|
||
"%timeit big_portfolio_shared.final_value()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 139,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a -0.003105\n",
|
||
"b -0.047314\n",
|
||
"c 0.017082\n",
|
||
"Name: total_return, dtype: float64\n",
|
||
"a -0.003105\n",
|
||
"b -0.047314\n",
|
||
"c 0.017082\n",
|
||
"Name: total_return, dtype: float64\n",
|
||
"a -0.001552\n",
|
||
"b -0.023657\n",
|
||
"c 0.017082\n",
|
||
"Name: total_return, dtype: float64\n",
|
||
"group\n",
|
||
"first -0.025210\n",
|
||
"second 0.017082\n",
|
||
"Name: total_return, dtype: float64\n",
|
||
"group\n",
|
||
"first -0.025210\n",
|
||
"second 0.017082\n",
|
||
"Name: total_return, dtype: float64\n",
|
||
"group\n",
|
||
"first -0.025210\n",
|
||
"second 0.017082\n",
|
||
"Name: total_return, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.total_return())\n",
|
||
"print(portfolio_grouped.total_return(group_by=False))\n",
|
||
"print(portfolio_shared.total_return(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.total_return(group_by=group_by))\n",
|
||
"print(portfolio_grouped.total_return())\n",
|
||
"print(portfolio_shared.total_return())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"12.5 ms ± 200 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.4 ms ± 207 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.8 ms ± 151 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14 ms ± 178 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"12.6 ms ± 199 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"14.2 ms ± 122 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.total_return()\n",
|
||
"%timeit big_portfolio_grouped.total_return(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.total_return(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.total_return(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.total_return()\n",
|
||
"%timeit big_portfolio_shared.total_return()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 140,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.001199 -0.001201\n",
|
||
"2020-01-02 -0.001040 -0.011053 0.008971\n",
|
||
"2020-01-03 -0.000060 0.000000 0.009331\n",
|
||
"2020-01-04 0.000000 -0.023366 -0.000078\n",
|
||
"2020-01-05 -0.002007 -0.012434 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.001199 -0.001201\n",
|
||
"2020-01-02 -0.001040 -0.011053 0.008971\n",
|
||
"2020-01-03 -0.000060 0.000000 0.009331\n",
|
||
"2020-01-04 0.000000 -0.023366 -0.000078\n",
|
||
"2020-01-05 -0.002007 -0.012434 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.000600 -0.001201\n",
|
||
"2020-01-02 -0.000520 -0.005523 0.008971\n",
|
||
"2020-01-03 -0.000030 0.000000 0.009331\n",
|
||
"2020-01-04 0.000000 -0.011611 -0.000078\n",
|
||
"2020-01-05 -0.001003 -0.006105 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.000600 -0.001201\n",
|
||
"2020-01-02 -0.000523 -0.005523 0.008971\n",
|
||
"2020-01-03 -0.000030 0.000000 0.009331\n",
|
||
"2020-01-04 0.000000 -0.011618 -0.000078\n",
|
||
"2020-01-05 -0.001027 -0.006109 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.000600 -0.001201\n",
|
||
"2020-01-02 -0.006044 0.008971\n",
|
||
"2020-01-03 -0.000030 0.009331\n",
|
||
"2020-01-04 -0.011618 -0.000078\n",
|
||
"2020-01-05 -0.007130 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.000600 -0.001201\n",
|
||
"2020-01-02 -0.006044 0.008971\n",
|
||
"2020-01-03 -0.000030 0.009331\n",
|
||
"2020-01-04 -0.011618 -0.000078\n",
|
||
"2020-01-05 -0.007130 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -0.000600 -0.001201\n",
|
||
"2020-01-02 -0.006044 0.008971\n",
|
||
"2020-01-03 -0.000030 0.009331\n",
|
||
"2020-01-04 -0.011618 -0.000078\n",
|
||
"2020-01-05 -0.007130 0.000000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.returns())\n",
|
||
"print(portfolio_grouped.returns(group_by=False))\n",
|
||
"print(portfolio_shared.returns(group_by=False))\n",
|
||
"print(portfolio_shared.returns(group_by=False, in_sim_order=True))\n",
|
||
"\n",
|
||
"print(portfolio.returns(group_by=group_by))\n",
|
||
"print(portfolio_grouped.returns())\n",
|
||
"print(portfolio_shared.returns())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"39.5 ms ± 2.59 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"37.4 ms ± 313 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"39.4 ms ± 226 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"52.3 ms ± 149 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"55.6 ms ± 310 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"50.9 ms ± 276 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"63.5 ms ± 4.23 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.returns()\n",
|
||
"%timeit big_portfolio_grouped.returns(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.returns(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.returns(group_by=False, in_sim_order=True)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.returns(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.returns()\n",
|
||
"%timeit big_portfolio_shared.returns()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 141,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 -inf -inf\n",
|
||
"2020-01-02 -inf -1.103980 0.895980\n",
|
||
"2020-01-03 -0.02985 0.000000 0.427409\n",
|
||
"2020-01-04 0.00000 -1.049109 -0.026533\n",
|
||
"2020-01-05 -inf -0.299875 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 -inf -inf\n",
|
||
"2020-01-02 -inf -1.103980 0.895980\n",
|
||
"2020-01-03 -0.02985 0.000000 0.427409\n",
|
||
"2020-01-04 0.00000 -1.049109 -0.026533\n",
|
||
"2020-01-05 -inf -0.299875 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.00000 -inf -inf\n",
|
||
"2020-01-02 -inf -1.103980 0.895980\n",
|
||
"2020-01-03 -0.02985 0.000000 0.427409\n",
|
||
"2020-01-04 0.00000 -1.049109 -0.026533\n",
|
||
"2020-01-05 -inf -0.299875 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -inf -inf\n",
|
||
"2020-01-02 -1.208000 0.895980\n",
|
||
"2020-01-03 -0.002985 0.427409\n",
|
||
"2020-01-04 -1.049109 -0.026533\n",
|
||
"2020-01-05 -0.350000 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -inf -inf\n",
|
||
"2020-01-02 -1.208000 0.895980\n",
|
||
"2020-01-03 -0.002985 0.427409\n",
|
||
"2020-01-04 -1.049109 -0.026533\n",
|
||
"2020-01-05 -0.350000 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 -inf -inf\n",
|
||
"2020-01-02 -1.208000 0.895980\n",
|
||
"2020-01-03 -0.002985 0.427409\n",
|
||
"2020-01-04 -1.049109 -0.026533\n",
|
||
"2020-01-05 -0.350000 0.000000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.active_returns())\n",
|
||
"print(portfolio_grouped.active_returns(group_by=False))\n",
|
||
"print(portfolio_shared.active_returns(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.active_returns(group_by=group_by))\n",
|
||
"print(portfolio_grouped.active_returns())\n",
|
||
"print(portfolio_shared.active_returns())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"40.2 ms ± 5.18 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"36.9 ms ± 235 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"37.4 ms ± 193 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"51.7 ms ± 195 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"49.8 ms ± 220 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"52.4 ms ± 264 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.active_returns()\n",
|
||
"%timeit big_portfolio_grouped.active_returns(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.active_returns(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.active_returns(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.active_returns()\n",
|
||
"%timeit big_portfolio_shared.active_returns()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 142,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 100.0 100.0 100.0\n",
|
||
"2020-01-02 100.0 200.0 200.0\n",
|
||
"2020-01-03 150.0 200.0 300.0\n",
|
||
"2020-01-04 200.0 400.0 400.0\n",
|
||
"2020-01-05 250.0 500.0 400.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 100.0 100.0 100.0\n",
|
||
"2020-01-02 100.0 200.0 200.0\n",
|
||
"2020-01-03 150.0 200.0 300.0\n",
|
||
"2020-01-04 200.0 400.0 400.0\n",
|
||
"2020-01-05 250.0 500.0 400.0\n",
|
||
" a b c\n",
|
||
"2020-01-01 200.0 200.0 100.0\n",
|
||
"2020-01-02 200.0 400.0 200.0\n",
|
||
"2020-01-03 300.0 400.0 300.0\n",
|
||
"2020-01-04 400.0 800.0 400.0\n",
|
||
"2020-01-05 500.0 1000.0 400.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.0 100.0\n",
|
||
"2020-01-02 300.0 200.0\n",
|
||
"2020-01-03 350.0 300.0\n",
|
||
"2020-01-04 600.0 400.0\n",
|
||
"2020-01-05 750.0 400.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.0 100.0\n",
|
||
"2020-01-02 300.0 200.0\n",
|
||
"2020-01-03 350.0 300.0\n",
|
||
"2020-01-04 600.0 400.0\n",
|
||
"2020-01-05 750.0 400.0\n",
|
||
"group first second\n",
|
||
"2020-01-01 200.0 100.0\n",
|
||
"2020-01-02 300.0 200.0\n",
|
||
"2020-01-03 350.0 300.0\n",
|
||
"2020-01-04 600.0 400.0\n",
|
||
"2020-01-05 750.0 400.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.market_value())\n",
|
||
"print(portfolio_grouped.market_value(group_by=False))\n",
|
||
"print(portfolio_shared.market_value(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.market_value(group_by=group_by))\n",
|
||
"print(portfolio_grouped.market_value())\n",
|
||
"print(portfolio_shared.market_value())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"909 µs ± 51.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"967 µs ± 34.4 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"1.81 ms ± 111 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"4.86 ms ± 415 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"2.82 ms ± 35.5 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"5.2 ms ± 387 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.market_value()\n",
|
||
"%timeit big_portfolio_grouped.market_value(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.market_value(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.market_value(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.market_value()\n",
|
||
"%timeit big_portfolio_shared.market_value()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 143,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 0.00 0.000000\n",
|
||
"2020-01-02 0.000000 1.00 1.000000\n",
|
||
"2020-01-03 0.500000 0.00 0.500000\n",
|
||
"2020-01-04 0.333333 1.00 0.333333\n",
|
||
"2020-01-05 0.250000 0.25 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 0.00 0.000000\n",
|
||
"2020-01-02 0.000000 1.00 1.000000\n",
|
||
"2020-01-03 0.500000 0.00 0.500000\n",
|
||
"2020-01-04 0.333333 1.00 0.333333\n",
|
||
"2020-01-05 0.250000 0.25 0.000000\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 0.00 0.000000\n",
|
||
"2020-01-02 0.000000 1.00 1.000000\n",
|
||
"2020-01-03 0.500000 0.00 0.500000\n",
|
||
"2020-01-04 0.333333 1.00 0.333333\n",
|
||
"2020-01-05 0.250000 0.25 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.000000 0.000000\n",
|
||
"2020-01-02 0.500000 1.000000\n",
|
||
"2020-01-03 0.166667 0.500000\n",
|
||
"2020-01-04 0.714286 0.333333\n",
|
||
"2020-01-05 0.250000 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.000000 0.000000\n",
|
||
"2020-01-02 0.500000 1.000000\n",
|
||
"2020-01-03 0.166667 0.500000\n",
|
||
"2020-01-04 0.714286 0.333333\n",
|
||
"2020-01-05 0.250000 0.000000\n",
|
||
"group first second\n",
|
||
"2020-01-01 0.000000 0.000000\n",
|
||
"2020-01-02 0.500000 1.000000\n",
|
||
"2020-01-03 0.166667 0.500000\n",
|
||
"2020-01-04 0.714286 0.333333\n",
|
||
"2020-01-05 0.250000 0.000000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.market_returns())\n",
|
||
"print(portfolio_grouped.market_returns(group_by=False))\n",
|
||
"print(portfolio_shared.market_returns(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.market_returns(group_by=group_by))\n",
|
||
"print(portfolio_grouped.market_returns())\n",
|
||
"print(portfolio_shared.market_returns())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"3.7 ms ± 67.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"3.72 ms ± 66.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"5.11 ms ± 5.82 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"7.2 ms ± 618 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"4.1 ms ± 52.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"7.28 ms ± 40.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.market_returns()\n",
|
||
"%timeit big_portfolio_grouped.market_returns(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.market_returns(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.market_returns(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.market_returns()\n",
|
||
"%timeit big_portfolio_shared.market_returns()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 144,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"a 1.5\n",
|
||
"b 4.0\n",
|
||
"c 3.0\n",
|
||
"Name: total_market_return, dtype: float64\n",
|
||
"a 1.5\n",
|
||
"b 4.0\n",
|
||
"c 3.0\n",
|
||
"Name: total_market_return, dtype: float64\n",
|
||
"a 1.5\n",
|
||
"b 4.0\n",
|
||
"c 3.0\n",
|
||
"Name: total_market_return, dtype: float64\n",
|
||
"group\n",
|
||
"first 2.75\n",
|
||
"second 3.00\n",
|
||
"Name: total_market_return, dtype: float64\n",
|
||
"group\n",
|
||
"first 2.75\n",
|
||
"second 3.00\n",
|
||
"Name: total_market_return, dtype: float64\n",
|
||
"group\n",
|
||
"first 2.75\n",
|
||
"second 3.00\n",
|
||
"Name: total_market_return, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.total_market_return())\n",
|
||
"print(portfolio_grouped.total_market_return(group_by=False))\n",
|
||
"print(portfolio_shared.total_market_return(group_by=False))\n",
|
||
"\n",
|
||
"print(portfolio.total_market_return(group_by=group_by))\n",
|
||
"print(portfolio_grouped.total_market_return())\n",
|
||
"print(portfolio_shared.total_market_return())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"975 µs ± 61.3 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"937 µs ± 10.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"1.83 ms ± 7.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n",
|
||
"4.77 ms ± 30 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"2.85 ms ± 11.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
||
"5.21 ms ± 79.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"%timeit big_portfolio.total_market_return()\n",
|
||
"%timeit big_portfolio_grouped.total_market_return(group_by=False)\n",
|
||
"%timeit big_portfolio_shared.total_market_return(group_by=False)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.total_market_return(group_by=big_group_by)\n",
|
||
"%timeit big_portfolio_grouped.total_market_return()\n",
|
||
"%timeit big_portfolio_shared.total_market_return()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 145,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"group first second\n",
|
||
"2020-01-01 -0.000599 -0.001201\n",
|
||
"2020-01-02 -0.006639 0.007759\n",
|
||
"2020-01-03 -0.006669 0.017162\n",
|
||
"2020-01-04 -0.018210 0.017082\n",
|
||
"2020-01-05 -0.025210 0.017082\n",
|
||
" a b c\n",
|
||
"2020-01-01 0.000000 -0.000599 -0.001201\n",
|
||
"2020-01-02 -0.000520 -0.006119 0.007759\n",
|
||
"2020-01-03 -0.000550 -0.006119 0.017162\n",
|
||
"2020-01-04 -0.000550 -0.017660 0.017082\n",
|
||
"2020-01-05 -0.001552 -0.023657 0.017082\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_shared.cumulative_returns())\n",
|
||
"print(portfolio_shared.cumulative_returns(group_by=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"group\n",
|
||
"first -20.095907\n",
|
||
"second 12.345065\n",
|
||
"Name: sharpe_ratio, dtype: float64\n",
|
||
"group\n",
|
||
"first -59.622588\n",
|
||
"second -23.917188\n",
|
||
"Name: sharpe_ratio, dtype: float64\n",
|
||
"group\n",
|
||
"first -16.697884\n",
|
||
"second 10.257635\n",
|
||
"Name: sharpe_ratio, dtype: float64\n",
|
||
"a -13.309506\n",
|
||
"b -19.278625\n",
|
||
"c 12.345065\n",
|
||
"Name: sharpe_ratio, dtype: float64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio_shared.sharpe_ratio())\n",
|
||
"print(portfolio_shared.sharpe_ratio(risk_free=0.01))\n",
|
||
"print(portfolio_shared.sharpe_ratio(year_freq='252D'))\n",
|
||
"print(portfolio_shared.sharpe_ratio(group_by=False))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Start Value 100.0\n",
|
||
"End Value 98.88877\n",
|
||
"Total Return [%] -1.11123\n",
|
||
"Benchmark Return [%] 283.333333\n",
|
||
"Max Gross Exposure [%] 2.059062\n",
|
||
"Total Fees Paid 0.42223\n",
|
||
"Max Drawdown [%] 1.645124\n",
|
||
"Max Drawdown Duration 3 days 08:00:00\n",
|
||
"Total Trades 2.0\n",
|
||
"Total Closed Trades 1.333333\n",
|
||
"Total Open Trades 0.666667\n",
|
||
"Open Trade PnL -1.504206\n",
|
||
"Win Rate [%] 33.333333\n",
|
||
"Best Trade [%] -98.380588\n",
|
||
"Worst Trade [%] -100.803855\n",
|
||
"Avg Winning Trade [%] 143.916254\n",
|
||
"Avg Losing Trade [%] -221.34646\n",
|
||
"Avg Winning Trade Duration 2 days 12:00:00\n",
|
||
"Avg Losing Trade Duration 2 days 00:00:00\n",
|
||
"Profit Factor inf\n",
|
||
"Expectancy 0.108273\n",
|
||
"Sharpe Ratio -6.751008\n",
|
||
"Calmar Ratio 10378.930331\n",
|
||
"Omega Ratio 4.7687\n",
|
||
"Sortino Ratio 31.599761\n",
|
||
"Name: agg_func_mean, dtype: object\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/Users/olegpolakow/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: Object has multiple columns. Aggregating using <function mean at 0x7ff110b83620>. Pass column to select a single column/group.\n",
|
||
" \"\"\"Entry point for launching an IPython kernel.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio.stats()) # mean statistics"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Start Value 100.0\n",
|
||
"End Value 99.68951\n",
|
||
"Total Return [%] -0.31049\n",
|
||
"Benchmark Return [%] 150.0\n",
|
||
"Max Gross Exposure [%] 5.015573\n",
|
||
"Total Fees Paid 0.35549\n",
|
||
"Max Drawdown [%] 0.31049\n",
|
||
"Max Drawdown Duration 4 days 00:00:00\n",
|
||
"Total Trades 2\n",
|
||
"Total Closed Trades 1\n",
|
||
"Total Open Trades 1\n",
|
||
"Open Trade PnL -0.2005\n",
|
||
"Win Rate [%] 0.0\n",
|
||
"Best Trade [%] -54.450495\n",
|
||
"Worst Trade [%] -54.450495\n",
|
||
"Avg Winning Trade [%] NaN\n",
|
||
"Avg Losing Trade [%] -54.450495\n",
|
||
"Avg Winning Trade Duration NaT\n",
|
||
"Avg Losing Trade Duration 1 days 00:00:00\n",
|
||
"Profit Factor 0.0\n",
|
||
"Expectancy -0.10999\n",
|
||
"Sharpe Ratio -13.308045\n",
|
||
"Calmar Ratio -65.408686\n",
|
||
"Omega Ratio 0.0\n",
|
||
"Sortino Ratio -11.738865\n",
|
||
"Name: a, dtype: object\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio['a'].stats())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Start Value 100.0\n",
|
||
"End Value 99.68951\n",
|
||
"Total Return [%] -0.31049\n",
|
||
"Benchmark Return [%] 150.0\n",
|
||
"Max Gross Exposure [%] 5.015573\n",
|
||
"Total Fees Paid 0.35549\n",
|
||
"Max Drawdown [%] 0.31049\n",
|
||
"Max Drawdown Duration 4 days 00:00:00\n",
|
||
"Total Trades 2\n",
|
||
"Total Closed Trades 1\n",
|
||
"Total Open Trades 1\n",
|
||
"Open Trade PnL -0.2005\n",
|
||
"Win Rate [%] 0.0\n",
|
||
"Best Trade [%] -54.450495\n",
|
||
"Worst Trade [%] -54.450495\n",
|
||
"Avg Winning Trade [%] NaN\n",
|
||
"Avg Losing Trade [%] -54.450495\n",
|
||
"Avg Winning Trade Duration NaT\n",
|
||
"Avg Losing Trade Duration 1 days 00:00:00\n",
|
||
"Profit Factor 0.0\n",
|
||
"Expectancy -0.10999\n",
|
||
"Sharpe Ratio -227.458628\n",
|
||
"Calmar Ratio -65.408686\n",
|
||
"Omega Ratio 0.0\n",
|
||
"Sortino Ratio -19.104372\n",
|
||
"Name: a, dtype: object\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio['a'].stats(settings=dict(required_return=0.1, risk_free=0.01))) # test kwargs"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Start Value 100.0\n",
|
||
"End Value 99.68951\n",
|
||
"Total Return [%] -0.31049\n",
|
||
"Benchmark Return [%] 150.0\n",
|
||
"Max Gross Exposure [%] 5.015573\n",
|
||
"Total Fees Paid 0.35549\n",
|
||
"Max Drawdown [%] 0.31049\n",
|
||
"Max Drawdown Duration 4 days 00:00:00\n",
|
||
"Total Trades 2\n",
|
||
"Total Closed Trades 1\n",
|
||
"Total Open Trades 1\n",
|
||
"Open Trade PnL -0.2005\n",
|
||
"Win Rate [%] 0.0\n",
|
||
"Best Trade [%] -3.970297\n",
|
||
"Worst Trade [%] -54.450495\n",
|
||
"Avg Winning Trade [%] NaN\n",
|
||
"Avg Losing Trade [%] -29.210396\n",
|
||
"Avg Winning Trade Duration NaT\n",
|
||
"Avg Losing Trade Duration 1 days 00:00:00\n",
|
||
"Profit Factor 0.0\n",
|
||
"Expectancy -0.155245\n",
|
||
"Sharpe Ratio -13.308045\n",
|
||
"Calmar Ratio -65.408686\n",
|
||
"Omega Ratio 0.0\n",
|
||
"Sortino Ratio -11.738865\n",
|
||
"Name: a, dtype: object\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(portfolio['a'].stats(settings=dict(incl_open=True))) # test incl_open"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Start Value 200.0\n",
|
||
"End Value 194.95809\n",
|
||
"Total Return [%] -2.520955\n",
|
||
"Benchmark Return [%] 275.0\n",
|
||
"Max Gross Exposure [%] -0.505305\n",
|
||
"Total Fees Paid 0.82091\n",
|
||
"Max Drawdown [%] 2.462481\n",
|
||
"Max Drawdown Duration 4 days 00:00:00\n",
|
||
"Total Trades 4\n",
|
||
"Total Closed Trades 2\n",
|
||
"Total Open Trades 2\n",
|
||
"Open Trade PnL -4.512618\n",
|
||
"Win Rate [%] 0.0\n",
|
||
"Best Trade [%] -54.450495\n",
|
||
"Worst Trade [%] -388.242424\n",
|
||
"Avg Winning Trade [%] NaN\n",
|
||
"Avg Losing Trade [%] -221.34646\n",
|
||
"Avg Winning Trade Duration NaT\n",
|
||
"Avg Losing Trade Duration 2 days 00:00:00\n",
|
||
"Profit Factor 0.0\n",
|
||
"Expectancy -0.264646\n",
|
||
"Sharpe Ratio -20.095907\n",
|
||
"Calmar Ratio -34.312217\n",
|
||
"Omega Ratio 0.0\n",
|
||
"Sortino Ratio -14.554512\n",
|
||
"Name: first, dtype: object"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"portfolio_grouped['first'].stats()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"pd.testing.assert_series_equal(portfolio['c'].stats(), portfolio.stats(column='c'))\n",
|
||
"pd.testing.assert_series_equal(portfolio['c'].stats(), portfolio_grouped.stats(column='c', group_by=False))\n",
|
||
"pd.testing.assert_series_equal(portfolio_grouped['second'].stats(), portfolio_grouped.stats(column='second'))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"64.9 ms ± 525 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"76 ms ± 478 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"145 ms ± 588 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"101 ms ± 87.9 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"72.4 ms ± 151 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"158 ms ± 1.02 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Calculates stats for one column\n",
|
||
"%timeit big_portfolio.iloc[0].stats()\n",
|
||
"%timeit big_portfolio_grouped.iloc[0].stats(group_by=False, column=0)\n",
|
||
"%timeit big_portfolio_shared.iloc[0].stats(group_by=False, column=0)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.iloc[0].stats(group_by=np.array([0]))\n",
|
||
"%timeit big_portfolio_grouped.iloc[0].stats()\n",
|
||
"%timeit big_portfolio_shared.iloc[0].stats()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"big_portfolio_one = big_portfolio.iloc[0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"start\n",
|
||
"1.72 ms ± 643 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"end\n",
|
||
"1.17 ms ± 25.3 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"period\n",
|
||
"1.18 ms ± 33.2 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"start_value\n",
|
||
"1.23 ms ± 51.1 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"end_value\n",
|
||
"2.43 ms ± 126 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_return\n",
|
||
"2.38 ms ± 7.53 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"benchmark_return\n",
|
||
"1.56 ms ± 12.2 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_gross_exposure\n",
|
||
"5.51 ms ± 22.4 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_fees_paid\n",
|
||
"2.11 ms ± 132 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_dd\n",
|
||
"5.3 ms ± 22.5 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_dd_duration\n",
|
||
"5.39 ms ± 49.2 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_trades\n",
|
||
"2.68 ms ± 320 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_closed_trades\n",
|
||
"4.07 ms ± 111 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_open_trades\n",
|
||
"3.24 ms ± 28.8 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"open_trade_pnl\n",
|
||
"3.72 ms ± 136 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"win_rate\n",
|
||
"4.19 ms ± 128 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"best_trade\n",
|
||
"3.62 ms ± 44.6 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"worst_trade\n",
|
||
"3.71 ms ± 178 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_winning_trade\n",
|
||
"4.54 ms ± 161 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_losing_trade\n",
|
||
"4.46 ms ± 122 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_winning_trade_duration\n",
|
||
"4.5 ms ± 140 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_losing_trade_duration\n",
|
||
"4.99 ms ± 224 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"profit_factor\n",
|
||
"5.82 ms ± 86.1 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"expectancy\n",
|
||
"7.09 ms ± 288 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"sharpe_ratio\n",
|
||
"8.79 ms ± 613 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"calmar_ratio\n",
|
||
"8.56 ms ± 527 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"omega_ratio\n",
|
||
"8.38 ms ± 215 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"sortino_ratio\n",
|
||
"8.15 ms ± 101 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for metric in big_portfolio_one.metrics:\n",
|
||
" print(metric)\n",
|
||
" %timeit -n 10 big_portfolio_one.stats(metrics=metric)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"start\n",
|
||
"1.51 ms ± 362 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"end\n",
|
||
"1.54 ms ± 74 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"period\n",
|
||
"1.92 ms ± 19.8 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"start_value\n",
|
||
"2.46 ms ± 117 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"end_value\n",
|
||
"4.1 ms ± 117 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_return\n",
|
||
"5.67 ms ± 12.9 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"benchmark_return\n",
|
||
"6.59 ms ± 46.7 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_gross_exposure\n",
|
||
"11.4 ms ± 33.9 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_fees_paid\n",
|
||
"12.8 ms ± 232 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_dd\n",
|
||
"17.6 ms ± 281 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"max_dd_duration\n",
|
||
"19.1 ms ± 833 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_trades\n",
|
||
"20.6 ms ± 434 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_closed_trades\n",
|
||
"22.5 ms ± 234 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"total_open_trades\n",
|
||
"23.9 ms ± 228 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"open_trade_pnl\n",
|
||
"25.7 ms ± 140 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"win_rate\n",
|
||
"28 ms ± 246 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"best_trade\n",
|
||
"30.3 ms ± 710 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"worst_trade\n",
|
||
"31.9 ms ± 606 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_winning_trade\n",
|
||
"35.8 ms ± 1.27 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_losing_trade\n",
|
||
"36.8 ms ± 183 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_winning_trade_duration\n",
|
||
"39.5 ms ± 140 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"avg_losing_trade_duration\n",
|
||
"41.7 ms ± 235 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"profit_factor\n",
|
||
"45.8 ms ± 240 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"expectancy\n",
|
||
"50.6 ms ± 425 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"sharpe_ratio\n",
|
||
"58 ms ± 176 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"calmar_ratio\n",
|
||
"58.5 ms ± 182 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"omega_ratio\n",
|
||
"59.1 ms ± 227 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"sortino_ratio\n",
|
||
"60 ms ± 144 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"metrics = []\n",
|
||
"for metric in big_portfolio_one.metrics:\n",
|
||
" print(metric)\n",
|
||
" metrics.append(metric)\n",
|
||
" %timeit -n 10 big_portfolio_one.stats(metrics=metrics)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"38 ms ± 179 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"47.3 ms ± 852 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"94.6 ms ± 237 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"68.4 ms ± 511 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"40.1 ms ± 161 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
|
||
"90.3 ms ± 1.48 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Calculates stats for one column with caching enabled\n",
|
||
"vbt.settings.caching.enabled = True\n",
|
||
"%timeit big_portfolio.iloc[0].stats()\n",
|
||
"%timeit big_portfolio_grouped.iloc[0].stats(group_by=False, column=0)\n",
|
||
"%timeit big_portfolio_shared.iloc[0].stats(group_by=False, column=0)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.iloc[0].stats(group_by=np.array([0]))\n",
|
||
"%timeit big_portfolio_grouped.iloc[0].stats()\n",
|
||
"%timeit big_portfolio_shared.iloc[0].stats()\n",
|
||
"vbt.settings.caching.enabled = False"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"560 ms ± 29.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"554 ms ± 13.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"609 ms ± 4.04 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"676 ms ± 10.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"635 ms ± 12.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
||
"741 ms ± 14.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Calculates stats for all columns and selects one, takes advantage of caching (which is disabled here)\n",
|
||
"# Thus some series are re-calculated multiple times, such as records and returns\n",
|
||
"%timeit big_portfolio.stats(column=0)\n",
|
||
"%timeit big_portfolio_grouped.stats(group_by=False, column=0)\n",
|
||
"%timeit big_portfolio_shared.stats(group_by=False, column=0)\n",
|
||
"\n",
|
||
"%timeit big_portfolio.stats(group_by=big_group_by, column=0)\n",
|
||
"%timeit big_portfolio_grouped.stats(column=0)\n",
|
||
"%timeit big_portfolio_shared.stats(column=0)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Start 2020-01-01 00:00:00\n",
|
||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Total Return [%] -1.11123\n",
|
||
"Benchmark Return [%] 283.333333\n",
|
||
"Annualized Return [%] 42.313666\n",
|
||
"Annualized Volatility [%] 9.984895\n",
|
||
"Max Drawdown [%] 1.645124\n",
|
||
"Max Drawdown Duration 3 days 08:00:00\n",
|
||
"Sharpe Ratio -6.751008\n",
|
||
"Calmar Ratio 10378.930331\n",
|
||
"Omega Ratio 4.7687\n",
|
||
"Sortino Ratio 31.599761\n",
|
||
"Skew -0.399797\n",
|
||
"Kurtosis -1.202541\n",
|
||
"Tail Ratio 3.164402\n",
|
||
"Common Sense Ratio 10.883528\n",
|
||
"Value at Risk -0.00799\n",
|
||
"Alpha -0.35365\n",
|
||
"Beta -0.001234\n",
|
||
"Name: agg_func_mean, dtype: object\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/portfolio/base.py:4618: UserWarning: Object has multiple columns. Aggregating using <function mean at 0x7ffd1144a620>. Pass column to select a single column/group.\n",
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" return getattr(returns_acc, 'stats')(settings=settings, **kwargs)\n"
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]
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}
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],
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"source": [
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"print(portfolio.returns_stats()) # mean statistics"
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]
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},
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Start 2020-01-01 00:00:00\n",
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||
"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Total Return [%] -0.31049\n",
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||
"Benchmark Return [%] 150.0\n",
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||
"Annualized Return [%] -20.308743\n",
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||
"Annualized Volatility [%] 1.704408\n",
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||
"Max Drawdown [%] 0.31049\n",
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||
"Max Drawdown Duration 4 days 00:00:00\n",
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||
"Sharpe Ratio -13.308045\n",
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"Calmar Ratio -65.408686\n",
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"Omega Ratio 0.0\n",
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"Sortino Ratio -11.738865\n",
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"Skew -1.219107\n",
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"Kurtosis 0.122976\n",
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"Tail Ratio 0.0\n",
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"Common Sense Ratio 0.0\n",
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"Value at Risk -0.001814\n",
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"Alpha -0.248883\n",
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"Beta 0.000749\n",
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"Name: a, dtype: object\n"
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]
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}
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],
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"source": [
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"print(portfolio['a'].returns_stats())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"text": [
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"Start 2020-01-01 00:00:00\n",
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"End 2020-01-05 00:00:00\n",
|
||
"Period 5 days 00:00:00\n",
|
||
"Total Return [%] -2.520955\n",
|
||
"Benchmark Return [%] 275.0\n",
|
||
"Annualized Return [%] -84.493192\n",
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||
"Annualized Volatility [%] 9.234269\n",
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||
"Max Drawdown [%] 2.462481\n",
|
||
"Max Drawdown Duration 4 days 00:00:00\n",
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"Sharpe Ratio -20.095907\n",
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"Calmar Ratio -34.312217\n",
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||
"Omega Ratio 0.0\n",
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"Sortino Ratio -14.554512\n",
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"Skew -0.254782\n",
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"Kurtosis -1.363876\n",
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"Tail Ratio 0.013427\n",
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||
"Common Sense Ratio 0.002082\n",
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||
"Value at Risk -0.01072\n",
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||
"Alpha -0.053947\n",
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||
"Beta -0.015121\n",
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||
"Name: first, dtype: object\n"
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]
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}
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],
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"source": [
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"print(portfolio_grouped['first'].returns_stats())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"pd.testing.assert_series_equal(\n",
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||
" portfolio['c'].returns_stats(), \n",
|
||
" portfolio.returns_stats(column='c'))\n",
|
||
"pd.testing.assert_series_equal(\n",
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||
" portfolio['c'].returns_stats(), \n",
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||
" portfolio_grouped.returns_stats(column='c', group_by=False))\n",
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"pd.testing.assert_series_equal(\n",
|
||
" portfolio_grouped['second'].returns_stats(), \n",
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" portfolio_grouped.returns_stats(column='second'))"
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]
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},
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{
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stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(545.31,0)\" d=\"M0,642.3611111111111v249.63888888888886\" style=\"stroke: rgb(255, 255, 255); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"x3grid crisp\" transform=\"translate(683.75,0)\" d=\"M0,642.3611111111111v249.63888888888886\" style=\"stroke: rgb(255, 255, 255); stroke-opacity: 1; stroke-width: 1px;\"/></g><g class=\"y3\"><path class=\"y3grid crisp\" transform=\"translate(0,875.3211111111111)\" d=\"M95,0h625\" style=\"stroke: rgb(255, 255, 255); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3grid crisp\" transform=\"translate(0,803.0811111111111)\" d=\"M95,0h625\" style=\"stroke: rgb(255, 255, 255); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3grid crisp\" transform=\"translate(0,730.8311111111111)\" d=\"M95,0h625\" style=\"stroke: rgb(255, 255, 255); stroke-opacity: 1; stroke-width: 1px;\"/><path class=\"y3grid crisp\" transform=\"translate(0,658.5911111111111)\" d=\"M95,0h625\" style=\"stroke: rgb(255, 255, 255); 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fill: none; stroke: rgb(0, 0, 0); stroke-opacity: 0; stroke-width: 0px; opacity: 1;\"/></g><g class=\"points\"><path class=\"point\" transform=\"translate(35,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(173.44,233.11)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(311.87,233.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(450.31,233.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(588.75,233.41)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"text\"/></g><g class=\"trace scatter trace9762176e-c891-4137-925b-8407d7ad9122\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M35,232.96L588.75,233.41\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(148, 103, 189); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"><path class=\"point\" transform=\"translate(35,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.44,233.11)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(311.87,233.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(450.31,233.12)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(588.75,233.41)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/></g><g class=\"text\"/></g><g class=\"trace scatter trace58b27d0d-deb0-40b5-9b0b-a8fc434e5e49\" style=\"stroke-miterlimit: 2; opacity: 0;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M35,232.96L588.75,232.96\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(0, 0, 0); stroke-opacity: 0; stroke-width: 0px; opacity: 1;\"/></g><g class=\"points\"><path class=\"point\" transform=\"translate(35,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(173.44,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(311.87,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(450.31,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(588.75,232.96)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><path class=\"ylines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><g class=\"x3tick\"><text text-anchor=\"middle\" x=\"0\" y=\"905\" transform=\"translate(130,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"905\">Jan 1</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"905\">2020</tspan></text></g><g class=\"x3tick\"><text text-anchor=\"middle\" x=\"0\" y=\"905\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(268.44,0)\">Jan 2</text></g><g class=\"x3tick\"><text text-anchor=\"middle\" x=\"0\" y=\"905\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(406.87,0)\">Jan 3</text></g><g class=\"x3tick\"><text text-anchor=\"middle\" x=\"0\" y=\"905\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(545.31,0)\">Jan 4</text></g><g class=\"x3tick\"><text text-anchor=\"middle\" x=\"0\" y=\"905\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(683.75,0)\">Jan 5</text></g></g><g class=\"yaxislayer-above\"><g class=\"y3tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" transform=\"translate(0,875.3211111111111)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\">1</text></g><g class=\"y3tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,803.0811111111111)\">1.5</text></g><g class=\"y3tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,730.8311111111111)\">2</text></g><g class=\"y3tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,658.5911111111111)\">2.5</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-b6a393\"><g class=\"clips\"/><clipPath id=\"legendb6a393\"><rect width=\"606\" height=\"29\" x=\"0\" y=\"0\"/></clipPath></defs><g class=\"layer-above\"><g class=\"imagelayer\"/><g class=\"shapelayer\"><path data-index=\"0\" fill-rule=\"evenodd\" d=\"M95,359.68055555555566L720,359.68055555555566\" clip-path=\"url(#clipb6a393y2)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"1\" fill-rule=\"evenodd\" d=\"M95,875.3211111111111L720,875.3211111111111\" clip-path=\"url(#clipb6a393y3)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/></g></g><g class=\"infolayer\"><g class=\"legend\" pointer-events=\"all\" transform=\"translate(114,11.958333333333272)\"><rect class=\"bg\" shape-rendering=\"crispEdges\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; fill: rgb(255, 255, 255); fill-opacity: 1; stroke-width: 0px;\" width=\"606\" height=\"29\" x=\"0\" y=\"0\"/><g class=\"scrollbox\" transform=\"\" clip-path=\"url(#legendb6a393)\"><g class=\"groups\"><g class=\"traces\" transform=\"translate(0,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Close</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(31, 119, 180); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.859375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(77.359375,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Buy</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M-4.62,2H4.62L0,-4Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(55, 177, 63); fill-opacity: 1; stroke: rgb(38, 123, 44); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"65.421875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(145.28125,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Sell</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M-4.62,-2H4.62L0,4Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"64.4375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(212.21875,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Closed - Loss</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M7,0A7,7 0 1,1 0,-7A7,7 0 0,1 7,0Z\" style=\"opacity: 0.9; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"122.6875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(337.40625,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; 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"\n",
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"Subplot 'orders' does not support grouped data\n",
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"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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||
"portfolio_shared['first'].plot().show_svg()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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text-anchor=\"middle\" x=\"0\" y=\"4095\" transform=\"translate(130.21,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"4095\">Jan 1</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"4095\">2020</tspan></text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(268.6,0)\">Jan 2</text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(406.98,0)\">Jan 3</text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 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style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Entry</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.640625\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Exit - Loss</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"105.578125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Closed - Loss</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M7,0A7,7 0 1,1 0,-7A7,7 0 0,1 7,0Z\" style=\"opacity: 0.9; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"122.6875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(250.375,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Open</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,0A3.5,3.5 0 1,1 0,-3.5A3.5,3.5 0 0,1 3.5,0Z\" style=\"opacity: 0.75; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.171875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(375.5625,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Assets</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(140, 86, 75); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(140, 86, 75); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"81.34375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Cash</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(44, 160, 44); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(44, 160, 44); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.9375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Asset Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(23, 190, 207); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(23, 190, 207); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"112.75\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(148, 103, 189); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"75.953125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(250.375,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Benchmark</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(127, 127, 127); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(127, 127, 127); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"110.421875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(375.5625,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Peak</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.203125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,71.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Drawdown</text><g class=\"layers\"><g class=\"legendfill\"><path class=\"js-fill\" d=\"M5,0h30v6h-30z\" style=\"stroke-width: 0; fill: rgb(220, 57, 18); fill-opacity: 0.3;\"/></g><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(220, 57, 18); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(220, 57, 18); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"106.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,71.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Exposure</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(227, 119, 194); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"98.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g></g></g><rect class=\"scrollbar\" rx=\"20\" ry=\"3\" width=\"0\" height=\"0\" style=\"fill: rgb(128, 139, 164); fill-opacity: 1;\" x=\"0\" y=\"0\"/></g><g class=\"g-gtitle\"/><g class=\"g-xtitle\"/><g class=\"g-x2title\"/><g class=\"g-x3title\"/><g class=\"g-x4title\"/><g class=\"g-x5title\"/><g class=\"g-x6title\"/><g class=\"g-x7title\"/><g class=\"g-x8title\"/><g class=\"g-x9title\"/><g class=\"g-x10title\"/><g class=\"g-x11title\"/><g class=\"g-x12title\"/><g class=\"g-x13title\"/><g class=\"g-x14title\"><text class=\"x14title\" x=\"407.5\" y=\"4137.909375\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Index</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,49.575,259.2700516351119)\" x=\"49.575\" y=\"259.2700516351119\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Price</text></g><g class=\"g-y2title\"><text class=\"y2title\" transform=\"rotate(-90,49.575,543.8438898450945)\" x=\"49.575\" y=\"543.8438898450945\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Price</text></g><g class=\"g-y3title\" transform=\"translate(2.4365234375,0)\"><text class=\"y3title\" transform=\"rotate(-90,11.575000000000003,828.4177280550771)\" x=\"11.575000000000003\" y=\"828.4177280550771\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Trade PnL</text></g><g class=\"g-y4title\"><text class=\"y4title\" transform=\"rotate(-90,49.575,1112.99156626506)\" x=\"49.575\" y=\"1112.99156626506\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Asset flow</text></g><g class=\"g-y5title\"><text class=\"y5title\" transform=\"rotate(-90,51.746875,1397.565404475043)\" x=\"51.746875\" y=\"1397.565404475043\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cash flow</text></g><g class=\"g-y6title\"><text class=\"y6title\" transform=\"rotate(-90,49.575,1682.139242685026)\" x=\"49.575\" y=\"1682.139242685026\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Assets</text></g><g class=\"g-y7title\"><text class=\"y7title\" transform=\"rotate(-90,46.309375,1966.7130808950085)\" x=\"46.309375\" y=\"1966.7130808950085\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cash</text></g><g class=\"g-y8title\"><text class=\"y8title\" transform=\"rotate(-90,61.559375,2251.286919104991)\" x=\"61.559375\" y=\"2251.286919104991\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Asset value</text></g><g class=\"g-y9title\"><text class=\"y9title\" transform=\"rotate(-90,34.309375,2535.8607573149743)\" x=\"34.309375\" y=\"2535.8607573149743\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Value</text></g><g class=\"g-y10title\"><text class=\"y10title\" transform=\"rotate(-90,49.575,2820.4345955249573)\" x=\"49.575\" y=\"2820.4345955249573\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cumulative returns</text></g><g class=\"g-y11title\"><text class=\"y11title\" transform=\"rotate(-90,41.934375,3105.00843373494)\" x=\"41.934375\" y=\"3105.00843373494\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Value</text></g><g class=\"g-y12title\"><text class=\"y12title\" transform=\"rotate(-90,38.825,3389.5822719449225)\" x=\"38.825\" y=\"3389.5822719449225\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Drawdown</text></g><g class=\"g-y13title\"><text class=\"y13title\" transform=\"rotate(-90,49.575,3674.156110154905)\" x=\"49.575\" y=\"3674.156110154905\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Gross exposure</text></g><g class=\"g-y14title\"><text class=\"y14title\" transform=\"rotate(-90,41.934375,3958.729948364888)\" x=\"41.934375\" y=\"3958.729948364888\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Net exposure</text></g><g class=\"annotation\" data-index=\"0\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,124)\"><g class=\"cursor-pointer\" transform=\"translate(379,112)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"57\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"29.046875\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Orders</text></g></g></g><g class=\"annotation\" data-index=\"1\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,408.5738382099826)\"><g class=\"cursor-pointer\" transform=\"translate(379,397)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"57\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"29.078125\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Trades</text></g></g></g><g class=\"annotation\" data-index=\"2\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,693.1476764199653)\"><g class=\"cursor-pointer\" transform=\"translate(366,681)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"83\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"42.0625\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Trade PnL</text></g></g></g><g class=\"annotation\" data-index=\"3\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,977.7215146299483)\"><g class=\"cursor-pointer\" transform=\"translate(363,966)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"88\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: 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},
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"metadata": {},
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}
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],
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"source": [
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||
"portfolio_shared['first'].plot(subplots='all').show_svg()"
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||
]
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||
},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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"\n",
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||
"Subplot 'orders' does not support grouped data\n",
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||
"\n",
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"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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||
"\n",
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||
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||
"\n",
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"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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||
"\n",
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||
"\n",
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"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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"\n",
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||
"Subplot 'asset_flow' does not support grouped data\n",
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"\n",
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||
"/Users/olegpolakow/Documents/SourceTree/vectorbt/vectorbt/generic/plots_builder.py:340: UserWarning:\n",
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"\n",
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"\n"
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stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><path class=\"ylines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><g class=\"x9tick\"><text text-anchor=\"middle\" x=\"0\" y=\"2645\" transform=\"translate(118.89,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"2645\">Jan 1</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"2645\">2020</tspan></text></g><g class=\"x9tick\"><text text-anchor=\"middle\" x=\"0\" y=\"2645\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(260.19,0)\">Jan 2</text></g><g 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1; white-space: pre;\">Asset Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(23, 190, 207); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(23, 190, 207); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"112.75\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(230.5,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(148, 103, 189); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"75.953125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(345.75,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Benchmark</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(127, 127, 127); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(127, 127, 127); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"110.421875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(461,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Peak</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.203125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(115.25,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Drawdown</text><g class=\"layers\"><g class=\"legendfill\"><path class=\"js-fill\" d=\"M5,0h30v6h-30z\" style=\"stroke-width: 0; fill: rgb(220, 57, 18); fill-opacity: 0.3;\"/></g><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(220, 57, 18); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(220, 57, 18); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"106.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(230.5,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Exposure</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(227, 119, 194); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"98.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g></g></g><rect class=\"scrollbar\" rx=\"20\" ry=\"3\" width=\"0\" height=\"0\" x=\"0\" y=\"0\" style=\"fill: rgb(128, 139, 164); fill-opacity: 1;\"/></g><g class=\"g-gtitle\"/><g class=\"g-xtitle\"/><g class=\"g-x2title\"/><g class=\"g-x3title\"/><g class=\"g-x4title\"/><g class=\"g-x5title\"/><g class=\"g-x6title\"/><g class=\"g-x7title\"/><g class=\"g-x8title\"/><g class=\"g-x9title\"><text class=\"x9title\" x=\"401.5\" y=\"2687.909375\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Index</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,27.746875000000003,222.09300411522625)\" x=\"27.746875000000003\" y=\"222.09300411522625\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"portfolio_shared.plot(subplots='all', column='first').show_svg()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(450.37,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(588.75,16.08)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"text\"/></g><g class=\"trace scatter trace54244182-0e80-4073-a540-bec3dfab0575\" style=\"stroke-miterlimit: 2; opacity: 1;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M35.21,230.46L173.6,221.9L311.98,230.46L450.37,230.46L588.75,16.08\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(227, 119, 194); stroke-opacity: 1; stroke-width: 2px; opacity: 1;\"/></g><g class=\"points\"><path class=\"point\" transform=\"translate(35.21,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(173.6,221.9)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(311.98,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(450.37,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/><path class=\"point\" transform=\"translate(588.75,16.08)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/></g><g class=\"text\"/></g><g class=\"trace scatter trace388dbeff-494c-40c7-84ca-7a22ee503aac\" style=\"stroke-miterlimit: 2; opacity: 0;\"><g class=\"fills\"/><g class=\"errorbars\"/><g class=\"lines\"><path class=\"js-line\" d=\"M35.21,230.46L588.75,230.46\" style=\"vector-effect: non-scaling-stroke; fill: none; stroke: rgb(0, 0, 0); stroke-opacity: 0; stroke-width: 0px; opacity: 1;\"/></g><g class=\"points\"><path class=\"point\" transform=\"translate(35.21,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(173.6,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(311.98,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(450.37,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><path class=\"point\" transform=\"translate(588.75,230.46)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"text\"/></g></g></g><g class=\"overplot\"/><path class=\"xlines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><path class=\"ylines-above crisp\" d=\"M0,0\" style=\"fill: none;\"/><g class=\"overlines-above\"/><g class=\"xaxislayer-above\"><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" transform=\"translate(130.21,0)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"4095\">Jan 1</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"4095\">2020</tspan></text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(268.6,0)\">Jan 2</text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(406.98,0)\">Jan 3</text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(545.37,0)\">Jan 4</text></g><g class=\"x14tick\"><text text-anchor=\"middle\" x=\"0\" y=\"4095\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(683.75,0)\">Jan 5</text></g></g><g class=\"yaxislayer-above\"><g class=\"y14tick\"><text text-anchor=\"end\" x=\"94\" 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fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,3937.4898967297763)\">0.015</text></g><g class=\"y14tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,3894.679896729776)\">0.02</text></g><g class=\"y14tick\"><text text-anchor=\"end\" x=\"94\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(0,3851.869896729776)\">0.025</text></g></g><g class=\"overaxes-above\"/></g></g><g class=\"polarlayer\"/><g class=\"ternarylayer\"/><g class=\"geolayer\"/><g class=\"funnelarealayer\"/><g class=\"pielayer\"/><g class=\"iciclelayer\"/><g class=\"treemaplayer\"/><g class=\"sunburstlayer\"/><g class=\"glimages\"/><defs id=\"topdefs-fa8056\"><g 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stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"5\" fill-rule=\"evenodd\" d=\"M95,1789.329191049914L720,1789.329191049914\" clip-path=\"url(#clipfa8056y6)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"6\" fill-rule=\"evenodd\" d=\"M95,1859.5230292598965L720,1859.5230292598965\" clip-path=\"url(#clipfa8056y7)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"7\" fill-rule=\"evenodd\" d=\"M95,2358.476867469879L720,2358.476867469879\" clip-path=\"url(#clipfa8056y8)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"8\" fill-rule=\"evenodd\" d=\"M95,2428.6707056798623L720,2428.6707056798623\" clip-path=\"url(#clipfa8056y9)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"9\" fill-rule=\"evenodd\" d=\"M95,2927.4045438898456L720,2927.4045438898456\" clip-path=\"url(#clipfa8056y10)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"11\" fill-rule=\"evenodd\" d=\"M95,3267.3122203098105L720,3267.3122203098105\" clip-path=\"url(#clipfa8056y12)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"12\" fill-rule=\"evenodd\" d=\"M95,3566.966058519793L720,3566.966058519793\" clip-path=\"url(#clipfa8056y13)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/><path data-index=\"13\" fill-rule=\"evenodd\" d=\"M95,4065.919896729776L720,4065.919896729776\" clip-path=\"url(#clipfa8056y14)\" style=\"opacity: 1; stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/></g></g><g class=\"infolayer\"><g class=\"legend\" pointer-events=\"all\" transform=\"translate(111,11.966265060240659)\"><rect class=\"bg\" shape-rendering=\"crispEdges\" width=\"609\" height=\"86\" x=\"0\" y=\"0\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; fill: rgb(255, 255, 255); fill-opacity: 1; stroke-width: 0px;\"/><g class=\"scrollbox\" transform=\"\" clip-path=\"url(#legendfa8056)\"><g class=\"groups\"><g class=\"traces\" transform=\"translate(0,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Close</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(31, 119, 180); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(31, 119, 180); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.859375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Buy</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M-4.62,2H4.62L0,-4Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(55, 177, 63); fill-opacity: 1; stroke: rgb(38, 123, 44); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"65.421875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(250.375,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Sell</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M-4.62,-2H4.62L0,4Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"64.4375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(375.5625,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Entry</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.640625\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Exit - Loss</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"105.578125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,3.5H-3.5V-3.5H3.5Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Closed - Loss</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M7,0A7,7 0 1,1 0,-7A7,7 0 0,1 7,0Z\" style=\"opacity: 0.9; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"122.6875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(250.375,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Open</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3.5,0A3.5,3.5 0 1,1 0,-3.5A3.5,3.5 0 0,1 3.5,0Z\" style=\"opacity: 0.75; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"74.171875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(375.5625,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Assets</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(140, 86, 75); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(140, 86, 75); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"81.34375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,33.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Cash</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(44, 160, 44); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(44, 160, 44); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.9375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Asset Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(23, 190, 207); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(23, 190, 207); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"112.75\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(148, 103, 189); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"75.953125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(250.375,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Benchmark</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(127, 127, 127); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(127, 127, 127); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"110.421875\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(375.5625,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Peak</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.203125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(500.75,52.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(0,71.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Drawdown</text><g class=\"layers\"><g class=\"legendfill\"><path class=\"js-fill\" d=\"M5,0h30v6h-30z\" style=\"stroke-width: 0; fill: rgb(220, 57, 18); fill-opacity: 0.3;\"/></g><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(220, 57, 18); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(220, 57, 18); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"106.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(125.1875,71.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Exposure</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(227, 119, 194); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(227, 119, 194); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"98.078125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g></g></g><rect class=\"scrollbar\" rx=\"20\" ry=\"3\" width=\"0\" height=\"0\" x=\"0\" y=\"0\" style=\"fill: rgb(128, 139, 164); fill-opacity: 1;\"/></g><g class=\"g-gtitle\"/><g class=\"g-xtitle\"/><g class=\"g-x2title\"/><g class=\"g-x3title\"/><g class=\"g-x4title\"/><g class=\"g-x5title\"/><g class=\"g-x6title\"/><g class=\"g-x7title\"/><g class=\"g-x8title\"/><g class=\"g-x9title\"/><g class=\"g-x10title\"/><g class=\"g-x11title\"/><g class=\"g-x12title\"/><g class=\"g-x13title\"/><g class=\"g-x14title\"><text class=\"x14title\" x=\"407.5\" y=\"4137.909375\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Index</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,49.575,259.2700516351119)\" x=\"49.575\" y=\"259.2700516351119\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Price</text></g><g class=\"g-y2title\"><text class=\"y2title\" transform=\"rotate(-90,49.575,543.8438898450945)\" x=\"49.575\" y=\"543.8438898450945\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Price</text></g><g class=\"g-y3title\" transform=\"translate(2.4365234375,0)\"><text class=\"y3title\" transform=\"rotate(-90,11.575000000000003,828.4177280550771)\" x=\"11.575000000000003\" y=\"828.4177280550771\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Trade PnL</text></g><g class=\"g-y4title\"><text class=\"y4title\" transform=\"rotate(-90,49.575,1112.99156626506)\" x=\"49.575\" y=\"1112.99156626506\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Asset flow</text></g><g class=\"g-y5title\"><text class=\"y5title\" transform=\"rotate(-90,51.746875,1397.565404475043)\" x=\"51.746875\" y=\"1397.565404475043\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cash flow</text></g><g class=\"g-y6title\"><text class=\"y6title\" transform=\"rotate(-90,49.575,1682.139242685026)\" x=\"49.575\" y=\"1682.139242685026\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Assets</text></g><g class=\"g-y7title\"><text class=\"y7title\" transform=\"rotate(-90,46.309375,1966.7130808950085)\" x=\"46.309375\" y=\"1966.7130808950085\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cash</text></g><g class=\"g-y8title\"><text class=\"y8title\" transform=\"rotate(-90,61.559375,2251.286919104991)\" x=\"61.559375\" y=\"2251.286919104991\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Asset value</text></g><g class=\"g-y9title\"><text class=\"y9title\" transform=\"rotate(-90,26.684375000000003,2535.8607573149743)\" x=\"26.684375000000003\" y=\"2535.8607573149743\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Value</text></g><g class=\"g-y10title\"><text class=\"y10title\" transform=\"rotate(-90,49.575,2820.4345955249573)\" x=\"49.575\" y=\"2820.4345955249573\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Cumulative returns</text></g><g class=\"g-y11title\"><text class=\"y11title\" transform=\"rotate(-90,34.309375,3105.00843373494)\" x=\"34.309375\" y=\"3105.00843373494\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Value</text></g><g class=\"g-y12title\"><text class=\"y12title\" transform=\"rotate(-90,38.825,3389.5822719449225)\" x=\"38.825\" y=\"3389.5822719449225\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Drawdown</text></g><g class=\"g-y13title\"><text class=\"y13title\" transform=\"rotate(-90,49.575,3674.156110154905)\" x=\"49.575\" y=\"3674.156110154905\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Gross exposure</text></g><g class=\"g-y14title\"><text class=\"y14title\" transform=\"rotate(-90,34.309375,3958.729948364888)\" x=\"34.309375\" y=\"3958.729948364888\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Net exposure</text></g><g class=\"annotation\" data-index=\"0\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,124)\"><g class=\"cursor-pointer\" transform=\"translate(379,112)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"57\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"29.046875\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Orders</text></g></g></g><g class=\"annotation\" data-index=\"1\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,408.5738382099826)\"><g class=\"cursor-pointer\" transform=\"translate(379,397)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"57\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"29.078125\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Trades</text></g></g></g><g class=\"annotation\" data-index=\"2\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,693.1476764199653)\"><g class=\"cursor-pointer\" transform=\"translate(366,681)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"83\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"42.0625\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Trade PnL</text></g></g></g><g class=\"annotation\" data-index=\"3\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,977.7215146299483)\"><g class=\"cursor-pointer\" transform=\"translate(363,966)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"88\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"44.734375\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Asset Flow</text></g></g></g><g class=\"annotation\" data-index=\"4\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,1262.295352839931)\"><g class=\"cursor-pointer\" transform=\"translate(365,1250)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"84\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"42.640625\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Cash Flow</text></g></g></g><g class=\"annotation\" data-index=\"5\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,1546.869191049914)\"><g class=\"cursor-pointer\" transform=\"translate(380,1535)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"55\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"27.890625\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Assets</text></g></g></g><g class=\"annotation\" data-index=\"6\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,1831.4430292598965)\"><g class=\"cursor-pointer\" transform=\"translate(386,1819)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"42\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"21.625\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Cash</text></g></g></g><g class=\"annotation\" data-index=\"7\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,407.5,2116.016867469879)\"><g class=\"cursor-pointer\" transform=\"translate(359,2104)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"97\" height=\"23\" style=\"stroke-width: 1px; 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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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||
"source": [
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||
"portfolio_shared.plot(subplots='all', column='a', group_by=False).show_svg()"
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||
]
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||
},
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{
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||
"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(181.42000000000002,0)\">12:00</text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(253.11,0)\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"615\">00:00</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"615\">Jan 2, 2020</tspan></text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(324.81,0)\">12:00</text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(396.5,0)\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"615\">00:00</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"615\">Jan 3, 2020</tspan></text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(468.19,0)\">12:00</text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(539.89,0)\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"615\">00:00</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"615\">Jan 4, 2020</tspan></text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(611.58,0)\">12:00</text></g><g class=\"x2tick\"><text text-anchor=\"middle\" x=\"0\" y=\"615\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\" transform=\"translate(683.28,0)\"><tspan class=\"line\" dy=\"0em\" x=\"0\" y=\"615\">00:00</tspan><tspan class=\"line\" dy=\"1.3em\" x=\"0\" y=\"615\">Jan 5, 2020</tspan></text></g></g><g class=\"yaxislayer-above\"><g class=\"y2tick\"><text text-anchor=\"end\" x=\"72\" y=\"4.199999999999999\" transform=\"translate(0,577.9910447761195)\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre; opacity: 1;\">−0%</text></g><g class=\"y2tick\"><text text-anchor=\"end\" x=\"72\" y=\"4.199999999999999\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; 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stroke: rgb(128, 128, 128); stroke-opacity: 1; fill: rgb(0, 0, 0); fill-opacity: 0; stroke-dasharray: 9px, 9px; stroke-width: 2px;\"/></g></g><g class=\"infolayer\"><g class=\"legend\" pointer-events=\"all\" transform=\"translate(377,12.417910447761216)\"><rect class=\"bg\" shape-rendering=\"crispEdges\" width=\"343\" height=\"29\" x=\"0\" y=\"0\" style=\"stroke: rgb(68, 68, 68); stroke-opacity: 1; fill: rgb(255, 255, 255); fill-opacity: 1; stroke-width: 0px;\"/><g class=\"scrollbox\" transform=\"\" clip-path=\"url(#legend2941d7)\"><g class=\"groups\"><g class=\"traces\" transform=\"translate(0,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Value</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(148, 103, 189); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(148, 103, 189); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"75.953125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(78.453125,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Peak</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(66, 133, 244); fill-opacity: 1; stroke: rgb(11, 84, 205); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"71.203125\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(152.15625,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Active</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M4.55,0L0,4.55L-4.55,0L0,-4.55Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(255, 170, 0); fill-opacity: 1; stroke: rgb(178, 118, 0); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"79.234375\" height=\"19\" style=\"fill: rgb(0, 0, 0); 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||
]
|
||
},
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||
"metadata": {},
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||
"output_type": "display_data"
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||
}
|
||
],
|
||
"source": [
|
||
"from vectorbt.utils.colors import adjust_opacity\n",
|
||
"\n",
|
||
"portfolio['a'].plot(\n",
|
||
" subplots=['drawdowns', 'underwater'],\n",
|
||
" subplot_settings=dict(\n",
|
||
" drawdowns=dict(top_n=3),\n",
|
||
" underwater=dict(\n",
|
||
" trace_kwargs=dict(\n",
|
||
" line_color='#FF6F00',\n",
|
||
" fillcolor=adjust_opacity('#FF6F00', 0.3)\n",
|
||
" )\n",
|
||
" )\n",
|
||
" )\n",
|
||
").show_svg()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
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"image/svg+xml": [
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font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Sell</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"/><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M-4.62,-2H4.62L0,4Z\" style=\"opacity: 1; stroke-width: 1px; fill: rgb(234, 67, 53); fill-opacity: 1; stroke: rgb(181, 31, 18); stroke-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"64.4375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g><g class=\"traces\" transform=\"translate(212.21875,14.5)\" style=\"opacity: 1;\"><text class=\"legendtext\" text-anchor=\"start\" x=\"40\" y=\"4.680000000000001\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 12px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Order Size</text><g class=\"layers\" style=\"opacity: 1;\"><g class=\"legendfill\"/><g class=\"legendlines\"><path class=\"js-line\" d=\"M5,0h30\" style=\"fill: none; stroke: rgb(220, 57, 18); stroke-opacity: 1; stroke-width: 2px;\"/></g><g class=\"legendsymbols\"><g class=\"legendpoints\"><path class=\"scatterpts\" transform=\"translate(20,0)\" d=\"M3,0A3,3 0 1,1 0,-3A3,3 0 0,1 3,0Z\" style=\"opacity: 1; stroke-width: 0px; fill: rgb(220, 57, 18); fill-opacity: 1;\"/></g></g></g><rect class=\"legendtoggle\" x=\"0\" y=\"-9.5\" width=\"105.984375\" height=\"19\" style=\"fill: rgb(0, 0, 0); fill-opacity: 0;\"/></g></g></g><rect class=\"scrollbar\" rx=\"20\" ry=\"3\" width=\"0\" height=\"0\" style=\"fill: rgb(128, 139, 164); fill-opacity: 1;\" x=\"0\" y=\"0\"/></g><g class=\"g-gtitle\"/><g class=\"g-xtitle\"/><g class=\"g-x2title\"><text class=\"x2title\" x=\"388.5\" y=\"658.3\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Index</text></g><g class=\"g-ytitle\" transform=\"translate(2.431640625,0)\"><text class=\"ytitle\" transform=\"rotate(-90,11.575000000000003,201.11567164179104)\" x=\"11.575000000000003\" y=\"201.11567164179104\" text-anchor=\"middle\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); opacity: 1; font-weight: normal; white-space: pre;\">Price</text></g><g class=\"g-y2title\"/><g class=\"annotation\" data-index=\"0\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,388.5,61)\"><g class=\"cursor-pointer\" transform=\"translate(360,49)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"57\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"29.046875\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Orders</text></g></g></g><g class=\"annotation\" data-index=\"1\" style=\"opacity: 1;\"><g class=\"annotation-text-g\" transform=\"rotate(0,388.5,349.7686567164179)\"><g class=\"cursor-pointer\" transform=\"translate(344,338)\"><rect class=\"bg\" x=\"0.5\" y=\"0.5\" width=\"88\" height=\"23\" style=\"stroke-width: 1px; stroke: rgb(0, 0, 0); stroke-opacity: 0; fill: rgb(0, 0, 0); fill-opacity: 0;\"/><text class=\"annotation-text\" text-anchor=\"middle\" x=\"44.328125\" y=\"18\" style=\"font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 16px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Order Size</text></g></g></g></g></svg>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from vectorbt import settings\n",
|
||
"color_schema = settings['plotting']['color_schema']\n",
|
||
"\n",
|
||
"fig = portfolio['a'].plot(subplots=[\n",
|
||
" 'orders',\n",
|
||
" ('order_size', dict(title='Order Size', check_is_not_grouped=True)) # placeholder\n",
|
||
"])\n",
|
||
"\n",
|
||
"order_size.vbt.plot(trace_kwargs=dict(name='Order Size'), add_trace_kwargs=dict(row=2, col=1), fig=fig).show_svg()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
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||
"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
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"version": "3.7.3"
|
||
},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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||
}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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||
}
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