233 lines
8.9 KiB
Markdown
233 lines
8.9 KiB
Markdown
<div align="center">
|
|
<a href="https://vectorbt.pro/" alt="https://vectorbt.pro/">
|
|
<img src="https://raw.githubusercontent.com/polakowo/vectorbt/master/docs/docs/assets/logo/header-pro.svg" />
|
|
</a>
|
|
</div>
|
|
<div align="center">
|
|
<a href="https://vectorbt.dev/" alt="https://vectorbt.dev/">
|
|
<img src="https://raw.githubusercontent.com/polakowo/vectorbt/master/docs/docs/assets/logo/header.svg" />
|
|
</a>
|
|
</div>
|
|
<br>
|
|
<p align="center">
|
|
<a href="https://pepy.tech/project/vectorbt" alt="Downloads">
|
|
<img src="https://pepy.tech/badge/vectorbt" />
|
|
</a>
|
|
<a href="https://pypi.org/project/vectorbt" alt="PyPi">
|
|
<img src="https://img.shields.io/pypi/v/vectorbt?color=blueviolet" />
|
|
</a>
|
|
<a href="https://github.com/polakowo/vectorbt/blob/master/LICENSE.md" alt="License">
|
|
<img src="https://img.shields.io/badge/license-Fair%20Code-yellow" />
|
|
</a>
|
|
<a href="https://codecov.io/gh/polakowo/vectorbt" alt="codecov">
|
|
<img src="https://codecov.io/gh/polakowo/vectorbt/branch/master/graph/badge.svg?token=YTLNAI7PS3" />
|
|
</a>
|
|
<a href="https://vectorbt.dev/" alt="Website">
|
|
<img src="https://img.shields.io/website?url=https://vectorbt.dev/" />
|
|
</a>
|
|
<a href="https://mybinder.org/v2/gh/polakowo/vectorbt/HEAD?urlpath=lab" alt="Binder">
|
|
<img src="https://img.shields.io/badge/launch-binder-d6604a" />
|
|
</a>
|
|
<a href="https://gitter.im/vectorbt/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge" alt="Join the chat at https://gitter.im/vectorbt/community">
|
|
<img src="https://badges.gitter.im/vectorbt.svg" />
|
|
</a>
|
|
</p>
|
|
<p align="center">
|
|
<a href="https://pypi.org/project/vectorbt" alt="Python Versions">
|
|
<img src="https://img.shields.io/pypi/pyversions/vectorbt.svg?logo=python&logoColor=white" />
|
|
</a>
|
|
</p>
|
|
|
|
## :sparkles: Usage
|
|
|
|
vectorbt allows you to easily backtest strategies with a couple of lines of Python code.
|
|
|
|
* Here is how much profit we would have made if we invested $100 into Bitcoin in 2014:
|
|
|
|
```python
|
|
import vectorbt as vbt
|
|
|
|
price = vbt.YFData.download('BTC-USD').get('Close')
|
|
|
|
pf = vbt.Portfolio.from_holding(price, init_cash=100)
|
|
pf.total_profit()
|
|
```
|
|
|
|
```plaintext
|
|
8961.008555963961
|
|
```
|
|
|
|
* Buy whenever 10-day SMA crosses above 50-day SMA and sell when opposite:
|
|
|
|
```python
|
|
fast_ma = vbt.MA.run(price, 10)
|
|
slow_ma = vbt.MA.run(price, 50)
|
|
entries = fast_ma.ma_crossed_above(slow_ma)
|
|
exits = fast_ma.ma_crossed_below(slow_ma)
|
|
|
|
pf = vbt.Portfolio.from_signals(price, entries, exits, init_cash=100)
|
|
pf.total_profit()
|
|
```
|
|
|
|
```plaintext
|
|
16423.251963801864
|
|
```
|
|
|
|
* Generate 1,000 strategies with random signals and test them on BTC and ETH:
|
|
|
|
```python
|
|
import numpy as np
|
|
|
|
symbols = ["BTC-USD", "ETH-USD"]
|
|
price = vbt.YFData.download(symbols, missing_index='drop').get('Close')
|
|
|
|
n = np.random.randint(10, 101, size=1000).tolist()
|
|
pf = vbt.Portfolio.from_random_signals(price, n=n, init_cash=100, seed=42)
|
|
|
|
mean_expectancy = pf.trades.expectancy().groupby(['randnx_n', 'symbol']).mean()
|
|
fig = mean_expectancy.unstack().vbt.scatterplot(xaxis_title='randnx_n', yaxis_title='mean_expectancy')
|
|
fig.show()
|
|
```
|
|
|
|
|
|
|
|
* For fans of hyperparameter optimization: here is a snippet for testing 10,000 window combinations of a
|
|
dual SMA crossover strategy on BTC, USD, and LTC:
|
|
|
|
```python
|
|
symbols = ["BTC-USD", "ETH-USD", "LTC-USD"]
|
|
price = vbt.YFData.download(symbols, missing_index='drop').get('Close')
|
|
|
|
windows = np.arange(2, 101)
|
|
fast_ma, slow_ma = vbt.MA.run_combs(price, window=windows, r=2, short_names=['fast', 'slow'])
|
|
entries = fast_ma.ma_crossed_above(slow_ma)
|
|
exits = fast_ma.ma_crossed_below(slow_ma)
|
|
|
|
pf_kwargs = dict(size=np.inf, fees=0.001, freq='1D')
|
|
pf = vbt.Portfolio.from_signals(price, entries, exits, **pf_kwargs)
|
|
|
|
fig = pf.total_return().vbt.heatmap(
|
|
x_level='fast_window', y_level='slow_window', slider_level='symbol', symmetric=True,
|
|
trace_kwargs=dict(colorbar=dict(title='Total return', tickformat='%')))
|
|
fig.show()
|
|
```
|
|
|
|
<img width="650" src="https://raw.githubusercontent.com/polakowo/vectorbt/master/docs/docs/assets/images/usage_dmac_heatmap.gif">
|
|
|
|
Digging into each strategy configuration is as simple as indexing with pandas:
|
|
|
|
```python
|
|
pf[(10, 20, 'ETH-USD')].stats()
|
|
```
|
|
|
|
```plaintext
|
|
Start 2015-08-07 00:00:00+00:00
|
|
End 2021-08-01 00:00:00+00:00
|
|
Period 2183 days 00:00:00
|
|
Start Value 100.0
|
|
End Value 620402.791485
|
|
Total Return [%] 620302.791485
|
|
Benchmark Return [%] 92987.961948
|
|
Max Gross Exposure [%] 100.0
|
|
Total Fees Paid 10991.676981
|
|
Max Drawdown [%] 70.734951
|
|
Max Drawdown Duration 760 days 00:00:00
|
|
Total Trades 54
|
|
Total Closed Trades 53
|
|
Total Open Trades 1
|
|
Open Trade PnL 67287.940601
|
|
Win Rate [%] 52.830189
|
|
Best Trade [%] 1075.803607
|
|
Worst Trade [%] -29.593414
|
|
Avg Winning Trade [%] 95.695343
|
|
Avg Losing Trade [%] -11.890246
|
|
Avg Winning Trade Duration 35 days 23:08:34.285714286
|
|
Avg Losing Trade Duration 8 days 00:00:00
|
|
Profit Factor 2.651143
|
|
Expectancy 10434.24247
|
|
Sharpe Ratio 2.041211
|
|
Calmar Ratio 4.6747
|
|
Omega Ratio 1.547013
|
|
Sortino Ratio 3.519894
|
|
Name: (10, 20, ETH-USD), dtype: object
|
|
```
|
|
|
|
The same for plotting:
|
|
|
|
```python
|
|
pf[(10, 20, 'ETH-USD')].plot().show()
|
|
```
|
|
|
|
|
|
|
|
It's not all about backtesting - vectorbt can be used to facilitate financial data analysis and visualization.
|
|
|
|
* Let's generate a GIF that animates the %B and bandwidth of Bollinger Bands for different symbols:
|
|
|
|
```python
|
|
symbols = ["BTC-USD", "ETH-USD", "ADA-USD"]
|
|
price = vbt.YFData.download(symbols, period='6mo', missing_index='drop').get('Close')
|
|
bbands = vbt.BBANDS.run(price)
|
|
|
|
def plot(index, bbands):
|
|
bbands = bbands.loc[index]
|
|
fig = vbt.make_subplots(
|
|
rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.15,
|
|
subplot_titles=('%B', 'Bandwidth'))
|
|
fig.update_layout(template='vbt_dark', showlegend=False, width=750, height=400)
|
|
bbands.percent_b.vbt.ts_heatmap(
|
|
trace_kwargs=dict(zmin=0, zmid=0.5, zmax=1, colorscale='Spectral', colorbar=dict(
|
|
y=(fig.layout.yaxis.domain[0] + fig.layout.yaxis.domain[1]) / 2, len=0.5
|
|
)), add_trace_kwargs=dict(row=1, col=1), fig=fig)
|
|
bbands.bandwidth.vbt.ts_heatmap(
|
|
trace_kwargs=dict(colorbar=dict(
|
|
y=(fig.layout.yaxis2.domain[0] + fig.layout.yaxis2.domain[1]) / 2, len=0.5
|
|
)), add_trace_kwargs=dict(row=2, col=1), fig=fig)
|
|
return fig
|
|
|
|
vbt.save_animation('bbands.gif', bbands.wrapper.index, plot, bbands, delta=90, step=3, fps=3)
|
|
```
|
|
|
|
```plaintext
|
|
100%|██████████| 31/31 [00:21<00:00, 1.21it/s]
|
|
```
|
|
|
|
<img width="750" src="https://raw.githubusercontent.com/polakowo/vectorbt/master/docs/docs/assets/images/usage_bbands.gif">
|
|
|
|
And this is just the tip of the iceberg of what's possible. Check out the [website](https://vectorbt.dev/) to learn more.
|
|
|
|
## Installation
|
|
|
|
```sh
|
|
pip install -U vectorbt
|
|
```
|
|
|
|
To also install optional dependencies:
|
|
|
|
```sh
|
|
pip install -U "vectorbt[full]"
|
|
```
|
|
|
|
## Colab Notebook
|
|
|
|
[Google Colaboratory](https://colab.research.google.com/drive/1ibqyrf6LPFlzRb6mkPpl3hxqL6ryNBXI?usp=sharing)
|
|
|
|
## License
|
|
|
|
This work is [fair-code](http://faircode.io/) distributed under [Apache 2.0 with Commons Clause](https://github.com/polakowo/vectorbt/blob/master/LICENSE.md) license.
|
|
The source code is open and everyone (individuals and organizations) can use it for free.
|
|
However, it is not allowed to sell products and services that are mostly just this software.
|
|
|
|
If you have any questions about this or want to apply for a license exception, please [contact the author](mailto:olegpolakow@gmail.com).
|
|
|
|
Installing optional dependencies may be subject to a more restrictive license.
|
|
|
|
## Star History
|
|
|
|
[](https://star-history.com/#polakowo/vectorbt&Timeline)
|
|
|
|
## Disclaimer
|
|
|
|
This software is for educational purposes only. Do not risk money which you are afraid to lose.
|
|
USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
|