Clearly highlight potential problems with looking into the future
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@ -201,6 +201,8 @@ Since backtesting lacks some detailed information about what happens within a ca
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Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
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Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
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Also, keep in mind that past results don't guarantee future success.
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Also, keep in mind that past results don't guarantee future success.
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In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
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### Further backtest-result analysis
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### Further backtest-result analysis
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To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
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To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
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@ -60,8 +60,7 @@ file as reference.**
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!!! Warning Using future data
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!!! Warning Using future data
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Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
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Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
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needs to take care to avoid having the strategy utilize data from the future.
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needs to take care to avoid having the strategy utilize data from the future.
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Samples for usage of future data are `dataframe.shift(-1)`, `dataframe.resample("1h")` (this uses the left border of the interval, so moves data from an hour to the start of the hour).
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Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
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They all use data which is not available during regular operations, so these strategies will perform well during backtesting, but will fail / perform badly in dry-runs.
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### Customize Indicators
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### Customize Indicators
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@ -399,10 +398,10 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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Printing more than a few rows is also possible (simply use `print(dataframe)` instead of `print(dataframe.tail())`), however not recommended, as that will be very verbose (~500 lines per pair every 5 seconds).
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Printing more than a few rows is also possible (simply use `print(dataframe)` instead of `print(dataframe.tail())`), however not recommended, as that will be very verbose (~500 lines per pair every 5 seconds).
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### Where is the default strategy?
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### Where can i find a strategy template?
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The default buy strategy is located in the file
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The strategy template is located in the file
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[freqtrade/default_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/strategy/default_strategy.py).
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[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
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### Specify custom strategy location
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### Specify custom strategy location
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@ -412,6 +411,19 @@ If you want to use a strategy from a different directory you can pass `--strateg
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freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
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freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
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```
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```
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### Common mistakes when developing strategies
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Backtesting analyzes the whole time-range at once for performance reasons. Because of this, strategy authors need to make sure that strategies do not look into the future.
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This is a common pain-point, which can cause huge differences between backtesting and dry/live run methods, since they all use data which is not available during dry/live runs, so these strategies will perform well during backtesting, but will fail / perform badly in real conditions.
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The following lists some common patterns which should be avoided to avoid frustration:
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- don't use `shift(-1)`. This uses data from the future, which is not available.
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- don't use `.iloc[-1]` or any other absolute position in the dataframe, this will be different between dry-run and backtesting.
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- don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
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- don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
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### Further strategy ideas
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### Further strategy ideas
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To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
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To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
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