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Updated 3/24/2018 4:35PMC

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Updated 3/24/2018 4:35PMC

Added example notes on how to configure your strategy.
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MoonGem 2018-03-23 16:37:16 -05:00 committed by GitHub
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1 changed files with 28 additions and 2 deletions
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user_data/strategies/test_strategy.py
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@ -13,9 +13,35 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy # noqa
# Make a backup of default_strategy then move this file over your default strategy in freqtrade/strategy and to run run with -s all to find best values when running hyperopt.
#
# Make a backup of default_strategy then move this file over your default strategy in freqtrade/strategy and to run:
# 'python3.6 freqtrade/main.py -c config.json hyperopt -s all --realistic-simulation -i 5'
# Make sure to take note of the if statements at the bottom of the file, and the pattern of > < and >= <= and the triggers configuration.
# Then, take note of the results: There is one trigger in the results, map the trigger as an example:
# 'Trigger: 7'
# The 7th trigger in this file's if statement such as:
# 'sar_reversal': (qtpylib.crossed_above(
# dataframe['close'], dataframe['sar']
#
# Drop the trigger into 'def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:' as:
# dataframe['close'], dataframe['sar'] &
# Then for your other values such as: 'Mfi-Value: 15.00'
# The if statement looks like: conditions.append(dataframe['mfi'] < params['mfi']['value']
# Drop this in as:
# (dataframe['mfi'] < 15.00) &
# The last condition in 'def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:' will have no &
### As an example the sell/buy trend looks like this:
# dataframe.loc[
# (
# (dataframe['adx'] > 70) &
# (dataframe['tema'] < dataframe['tema'].shift(1))
# ),
# 'sell'] = 1
#
class_name = 'DefaultStrategy'