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docs/advanced-backtesting.md
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# Advanced Backtesting Analysis # Advanced Backtesting Analysis
## Analyse the buy/entry and sell/exit tags ## Analyze the buy/entry and sell/exit tags
It can be helpful to understand how a strategy behaves according to the buy/entry tags used to It can be helpful to understand how a strategy behaves according to the buy/entry tags used to
mark up different buy conditions. You might want to see more complex statistics about each buy and mark up different buy conditions. You might want to see more complex statistics about each buy and
@ -10,21 +10,14 @@ determine indicator values on the signal candle that resulted in a trade opening
!!! Note !!! Note
The following buy reason analysis is only available for backtesting, *not hyperopt*. The following buy reason analysis is only available for backtesting, *not hyperopt*.
We first need to tell freqtrade to export the signal candles for each opened trade, We need to run backtesting with the `--export` option set to `signals` to enable the exporting of
so add the following option to your config file: signals **and** trades:
```
'backtest_signal_candle_export_enable': true,
```
We then need to run backtesting and include the `--export` option to enable the exporting of
trades:
``` bash ``` bash
freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=trades freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=signals
``` ```
To analyse the buy tags, we need to use the `buy_reasons.py` script from To analyze the buy tags, we need to use the `buy_reasons.py` script from
[froggleston's repo](https://github.com/froggleston/freqtrade-buyreasons). Follow the instructions [froggleston's repo](https://github.com/froggleston/freqtrade-buyreasons). Follow the instructions
in their README to copy the script into your `freqtrade/scripts/` folder. in their README to copy the script into your `freqtrade/scripts/` folder.
@ -39,7 +32,7 @@ backtesting with the `--cache none` option to make sure no cached results are us
If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the
`user_data/backtest_results` folder. `user_data/backtest_results` folder.
Now run the buy_reasons.py script, supplying a few options: Now run the `buy_reasons.py` script, supplying a few options:
``` bash ``` bash
python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4 python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4
@ -76,5 +69,5 @@ python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange
``` ```
The indicators have to be present in your strategy's main DataFrame (either for your main The indicators have to be present in your strategy's main DataFrame (either for your main
timeframe or for informatives) otherwise they will simply be ignored in the script timeframe or for informative timeframes) otherwise they will simply be ignored in the script
output. output.

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mkdocs.yml
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- Data Analysis: - Data Analysis:
- Jupyter Notebooks: data-analysis.md - Jupyter Notebooks: data-analysis.md
- Strategy analysis: strategy_analysis_example.md - Strategy analysis: strategy_analysis_example.md
- Backtest analysis: advanced-backtesting.md
- Advanced Topics: - Advanced Topics:
- Advanced Post-installation Tasks: advanced-setup.md - Advanced Post-installation Tasks: advanced-setup.md
- Edge Positioning: edge.md - Edge Positioning: edge.md