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Matthias 2022-04-22 06:38:51 +02:00
parent f92997d378
commit 7f60364f63
3 changed files with 11 additions and 10 deletions
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8
docs/advanced-backtesting.md
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@ -1,6 +1,6 @@
# 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
mark up different buy conditions. You might want to see more complex statistics about each buy and
@ -24,7 +24,7 @@ trades:
freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=trades
```
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
in their README to copy the script into your `freqtrade/scripts/` folder.
@ -39,7 +39,7 @@ 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
`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
python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4
@ -76,5 +76,5 @@ 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
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.

8
freqtrade/optimize/backtesting.py
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@ -1077,8 +1077,8 @@ class Backtesting:
})
self.all_results[self.strategy.get_strategy_name()] = results
if self.backtest_signal_candle_export_enable and \
self.dataprovider.runmode == RunMode.BACKTEST:
if (self.backtest_signal_candle_export_enable and
self.dataprovider.runmode == RunMode.BACKTEST):
self._generate_trade_signal_candles(preprocessed_tmp, results)
return min_date, max_date
@ -1163,8 +1163,8 @@ class Backtesting:
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'], self.results)
if self.backtest_signal_candle_export_enable and \
self.dataprovider.runmode == RunMode.BACKTEST:
if (self.backtest_signal_candle_export_enable and
self.dataprovider.runmode == RunMode.BACKTEST):
store_backtest_signal_candles(self.config['exportfilename'], self.processed_dfs)
# Results may be mixed up now. Sort them so they follow --strategy-list order.

1
mkdocs.yml
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@ -29,6 +29,7 @@ nav:
- Data Analysis:
- Jupyter Notebooks: data-analysis.md
- Strategy analysis: strategy_analysis_example.md
- Backtest analysis: advanced-backtesting.md
- Advanced Topics:
- Advanced Post-installation Tasks: advanced-setup.md
- Edge Positioning: edge.md