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Merge pull request #1635 from freqtrade/feat/btanlaysis

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BTAnalysis - simplify backtest result analysis
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Misagh
2019-03-16 21:16:59 +01:00
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parent b0cad30796 e7f6df46e8
commit b3f42dc51e
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docs/backtesting.md
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@@ -245,6 +245,26 @@ On the other hand, if you set a too high `minimal_roi` like `"0": 0.55`
profit. Hence, keep in mind that your performance is a mix of your
strategies, your configuration, and the crypto-currency you have set up.
### Further backtest-result analysis
To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
You can then load the trades to perform further analysis.
A good way for this is using Jupyter (notebook or lab) - which provides an interactive environment to analyze the data.
Freqtrade provides an easy to load the backtest results, which is `load_backtest_data` - and takes a path to the backtest-results file.
``` python
from freqtrade.data.btanalysis import load_backtest_data
df = load_backtest_data("user_data/backtest-result.json")
# Show value-counts per pair
df.groupby("pair")["sell_reason"].value_counts()
```
This will allow you to drill deeper into your backtest results, and perform analysis which would make the regular backtest-output unreadable.
## Backtesting multiple strategies
To backtest multiple strategies, a list of Strategies can be provided.