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DOC: Update docs and examples
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‎README.md

+25-22
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@@ -33,9 +33,9 @@ from backtesting.test import SMA, GOOG
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class SmaCross(Strategy):
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def init(self):
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Close = self.data.Close
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self.ma1 = self.I(SMA, Close, 10)
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self.ma2 = self.I(SMA, Close, 20)
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price = self.data.Close
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self.ma1 = self.I(SMA, price, 10)
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self.ma2 = self.I(SMA, price, 20)
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def next(self):
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if crossover(self.ma1, self.ma2):
@@ -44,8 +44,8 @@ class SmaCross(Strategy):
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self.sell()
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bt = Backtest(GOOG, SmaCross,
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cash=10000, commission=.002)
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bt = Backtest(GOOG, SmaCross, commission=.002,
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exclusive_orders=True)
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bt.run()
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bt.plot()
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```
@@ -56,30 +56,33 @@ Results in:
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Start 2004-08-19 00:00:00
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End 2013-03-01 00:00:00
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Duration 3116 days 00:00:00
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Exposure [%] 94.29
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Equity Final [$] 69665.12
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Equity Peak [$] 69722.15
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Return [%] 596.65
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Exposure Time [%] 94.27
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Equity Final [$] 68935.12
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Equity Peak [$] 68991.22
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Return [%] 589.35
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Buy & Hold Return [%] 703.46
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Max. Drawdown [%] -33.61
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Avg. Drawdown [%] -5.68
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Max. Drawdown Duration 689 days 00:00:00
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Max. Drawdown [%] -33.08
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Avg. Drawdown [%] -5.58
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Max. Drawdown Duration 688 days 00:00:00
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Avg. Drawdown Duration 41 days 00:00:00
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# Trades 93
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Win Rate [%] 53.76
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Best Trade [%] 56.98
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Worst Trade [%] -17.03
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Avg. Trade [%] 2.44
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Best Trade [%] 57.12
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Worst Trade [%] -16.63
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Avg. Trade [%] 1.96
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Max. Trade Duration 121 days 00:00:00
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Avg. Trade Duration 32 days 00:00:00
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Expectancy [%] 6.92
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SQN 1.77
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Sharpe Ratio 0.22
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Sortino Ratio 0.54
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Calmar Ratio 0.07
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_strategy SmaCross
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Profit Factor 2.13
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Expectancy [%] 6.91
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SQN 1.78
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Sharpe Ratio 0.18
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Sortino Ratio 0.44
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Calmar Ratio 0.06
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_strategy SmaCross(n1=10, n2=20)
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_equity_curve Equ...
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_trades Size EntryB...
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```
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[![plot of trading simulation](https://i.imgur.com/q6OSQD8.png)](https://kernc.github.io/backtesting.py/#example)
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[![plot of trading simulation](https://i.imgur.com/xRFNHfg.png)](https://kernc.github.io/backtesting.py/#example)
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Find more usage examples in the [documentation].
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‎backtesting/__init__.py

+11-1
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@@ -1,6 +1,11 @@
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"""
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# Backtesting.py Documentation
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.. warning:: v0.2.0 breaking changes
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Version 0.2.0 introduced some **breaking API changes**. For quick ways to
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migrate existing 0.1.x code, see the implementing
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[pull request](https://github.com/kernc/backtesting.py/pull/47/).
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## Manuals
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* [**Quick Start User Guide**](../examples/Quick Start User Guide.html)
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* [Multiple Time Frames](../examples/Multiple Time Frames.html)
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* [Parameter Heatmap](../examples/Parameter Heatmap.html)
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These tutorials are also available as live notebooks:
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These tutorials are also available to test as live Jupyter notebooks:
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[![Binder](https://mybinder.org/badge_logo.svg)][binder]
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[binder]: \
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* (contributions welcome)
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## FAQ
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Potentially outdated answers to popular questions can be found on the
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[issue tracker](https://github.com/kernc/backtesting.py/issues?q=label%3Aquestion).
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## License
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This software is licensed under the terms of [AGPL 3.0]{: rel=license},

‎backtesting/backtesting.py

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@@ -1,9 +1,14 @@
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"""
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Core backtesting data structures.
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Objects from this module can be imported from the top-level
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Core framework data structures.
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Objects from this module can also be imported from the top-level
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module directly, e.g.
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from backtesting import Backtest, Strategy
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.. warning:: v0.2.0 breaking changes
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Version 0.2.0 introduced some **breaking API changes**. For quick ways to
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migrate existing 0.1.x code, see the implementing
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[pull request](https://github.com/kernc/backtesting.py/pull/47/).
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"""
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import multiprocessing as mp
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import os
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To run the backtest using e.g. 50:1 leverge that your broker allows,
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set margin to `0.02` (1 / leverage).
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If `trade_on_close` is `True`, market orders will be executed
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If `trade_on_close` is `True`, market orders will be filled
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with respect to the current bar's closing price instead of the
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next bar's open.
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@@ -1029,6 +1034,37 @@ def run(self, **kwargs) -> pd.Series:
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Run the backtest. Returns `pd.Series` with results and statistics.
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Keyword arguments are interpreted as strategy parameters.
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>>> Backtest(GOOG, SmaCross).run()
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Start 2004-08-19 00:00:00
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End 2013-03-01 00:00:00
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Duration 3116 days 00:00:00
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Exposure Time [%] 93.9944
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Equity Final [$] 51959.9
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Equity Peak [$] 75787.4
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Return [%] 419.599
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Buy & Hold Return [%] 703.458
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Max. Drawdown [%] -47.9801
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Avg. Drawdown [%] -5.92585
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Max. Drawdown Duration 584 days 00:00:00
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Avg. Drawdown Duration 41 days 00:00:00
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# Trades 65
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Win Rate [%] 46.1538
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Best Trade [%] 53.596
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Worst Trade [%] -18.3989
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Avg. Trade [%] 2.35371
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Max. Trade Duration 183 days 00:00:00
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Avg. Trade Duration 46 days 00:00:00
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Profit Factor 2.08802
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Expectancy [%] 8.79171
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SQN 0.916893
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Sharpe Ratio 0.179141
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Sortino Ratio 0.55887
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Calmar Ratio 0.049056
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_strategy SmaCross
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_equity_curve Eq...
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_trades Size EntryB...
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dtype: object
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"""
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data = _Data(self._data.copy(deep=False))
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broker = self._broker(data=data) # type: _Broker
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raise ValueError('No admissible parameter combinations to test')
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if len(param_combos) > 300:
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warnings.warn('Searching best of {} configurations.'.format(len(param_combos)),
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warnings.warn('Searching for best of {} configurations.'.format(len(param_combos)),
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stacklevel=2)
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heatmap = pd.Series(np.nan,
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a separate drawdown graph section.
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If `smooth_equity` is `True`, the equity graph will be
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interpolated between points of cash-only positions,
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interpolated between fixed points at trade closing times,
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unaffected by any interim asset volatility.
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If `relative_equity` is `True`, scale and label equity graph axis

‎backtesting/lib.py

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@@ -175,7 +175,7 @@ def resample_apply(rule: str,
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a time frame to resample `series` to.
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[Pandas offset string]: \
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http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
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http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
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`func` is the indicator function to apply on the resampled series.
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@@ -202,7 +202,7 @@ def init(self):
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self.sma = resample_apply(
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'D', SMA, self.data.Close, 10, plot=False)
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This short snippet is roughly equivalent to:
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The above short snippet is roughly equivalent to:
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class System(Strategy):
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def init(self):

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