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docs: remove more --dmmp docs
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@ -917,7 +917,7 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
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Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
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To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt for Backtesting.
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### Why do my backtest results not match my hyperopt results?
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Should results not match, check the following factors:
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@ -215,7 +215,7 @@ trades.groupby("pair")["exit_reason"].value_counts()
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```
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## Analyze the loaded trades for trade parallelism
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This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.
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This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with a very high `max_open_trades` setting.
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`analyze_trade_parallelism()` returns a timeseries dataframe with an "open_trades" column, specifying the number of open trades for each candle.
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@ -305,7 +305,7 @@
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"metadata": {},
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"source": [
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"## Analyze the loaded trades for trade parallelism\n",
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"This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
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"This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with a very high `max_open_trades` setting.\n",
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"\n",
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"`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
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]
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