75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
import vectorbt as vbt
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import pandas as pd
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import numpy as np
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import datetime
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import talib
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from numba import njit
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end_time = datetime.datetime.now()
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start_time = end_time - datetime.timedelta(days=2)
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btc_price = pd.read_csv("data.csv")
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btc_price["Datetime"] = pd.to_datetime(btc_price["Datetime"])
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btc_price.set_index("Datetime", inplace=True)
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print(btc_price)
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RSI = vbt.IndicatorFactory.from_talib('RSI')
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@njit
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def produce_signal(rsi, entry, exit):
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trend = np.where( rsi > exit, -1, 0)
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trend = np.where( (rsi < entry) , 1, trend)
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return trend
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def custom_indicator(close, rsi_window = 14, entry = 30, exit = 70):
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rsi = RSI.run(close, rsi_window).real.to_numpy()
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return produce_signal(rsi, entry, exit)
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ind = vbt.IndicatorFactory(
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class_name = "Combination",
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short_name = "comb",
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input_names = ["close"],
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param_names = ["rsi_window","entry","exit"],
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output_names = ["value"]
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).from_apply_func(
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custom_indicator,
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rsi_window = 14,
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entry = 30,
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exit = 70,
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)
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rsi_windows = np.arange(10,40,step=1,dtype=int)
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entries = np.arange(10,40,step=1,dtype=int)
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master_returns = []
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for window in rsi_windows:
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res = ind.run(
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btc_price,
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rsi_window = window,
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entry = entry,
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exit = np.arange(60,85,step=1,dtype=int),
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param_product = True
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)
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entries = res.value == 1.0
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exits = res.value == -1.0
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pf = vbt.Portfolio.from_signals(btc_price, entries, exits)
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master_returns.append(pf.total_return())
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print(master_returns)
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returns = pd.concat(master_returns)
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#returns = returns[ returns.index.isin(["BTC-USD"], level="symbol")]
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#returns = returns.groupby(level=["comb_exit","comb_entry","symbol"]).mean()
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print(returns.to_string())
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print(returns.max())
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print(returns.idxmax())
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