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@ -37,7 +37,7 @@ See the example below:
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"40": 0.0, # Sell after 40 minutes if the profit is not negative
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"30": 0.01, # Sell after 30 minutes if there is at least 1% profit
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"20": 0.02, # Sell after 20 minutes if there is at least 2% profit
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"0": 0.04 # Sell immediately if there is at least 4% profit
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"0": 0.04 # Sell immediately if there is at least 4% profit
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},
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```
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@ -164,25 +164,39 @@ optional arguments:
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Backtesting also uses the config specified via `-c/--config`.
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```
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usage: freqtrade backtesting [-h] [-l] [-i INT]
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usage: freqtrade backtesting [-h] [-l] [-i INT] [--realistic-simulation]
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optional arguments:
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-h, --help show this help message and exit
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-l, --live using live data
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-i INT, --ticker-interval INT
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specify ticker interval in minutes (default: 5)
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--realistic-simulation
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uses max_open_trades from config to simulate real
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world limitations
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```
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### Hyperopt
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### Execute tests
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It is possible to use hyperopt for trading strategy optimization.
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Hyperopt uses an internal config named `OPTIMIZE_CONFIG` located in `freqtrade/optimize/hyperopt.py`.
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```
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$ pytest
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usage: freqtrade hyperopt [-h] [-e INT] [--use-mongodb]
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optional arguments:
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-h, --help show this help message and exit
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-e INT, --epochs INT specify number of epochs (default: 100)
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--use-mongodb parallelize evaluations with mongodb (requires mongod
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in PATH)
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```
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This will by default skip the slow running backtest set. To run backtest set:
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### Execute tests
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```
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$ BACKTEST=true pytest -s freqtrade/tests/test_backtesting.py
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$ pytest freqtrade
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```
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### Contributing
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