Convert MACDStrategy to hyperoptable strategy
This commit is contained in:
Matthias
@@ -1,100 +0,0 @@
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# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
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import talib.abstract as ta
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from pandas import DataFrame
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from typing import Dict, Any, Callable, List
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# import numpy as np
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from skopt.space import Categorical, Dimension, Integer, Real
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# import freqtrade.vendor.qtpylib.indicators as qtpylib
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from freqtrade.optimize.hyperopt_interface import IHyperOpt
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class_name = 'MACDStrategy_hyperopt'
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# This class is a sample. Feel free to customize it.
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class MACDStrategy_hyperopt(IHyperOpt):
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"""
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This is an Example hyperopt to inspire you. - corresponding to MACDStrategy in this repository.
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To run this, best use the following command (adjust to your environment if needed):
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```
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freqtrade hyperopt --strategy MACDStrategy --hyperopt MACDStrategy_hyperopt --spaces buy sell
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```
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The idea is to optimize only the CCI value.
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- Buy side: CCI between -700 and 0
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- Sell side: CCI between 0 and 700
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More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
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"""
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@staticmethod
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def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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dataframe['macdsignal'] = macd['macdsignal']
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dataframe['macdhist'] = macd['macdhist']
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dataframe['cci'] = ta.CCI(dataframe)
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return dataframe
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@staticmethod
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def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Define the buy strategy parameters to be used by hyperopt
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"""
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def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Buy strategy Hyperopt will build and use
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"""
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dataframe.loc[
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(
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(dataframe['macd'] > dataframe['macdsignal']) &
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(dataframe['cci'] <= params['buy-cci-value']) &
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(dataframe['volume'] > 0) # Make sure Volume is not 0
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),
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'buy'] = 1
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return dataframe
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return populate_buy_trend
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@staticmethod
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def indicator_space() -> List[Dimension]:
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"""
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Define your Hyperopt space for searching strategy parameters
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"""
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return [
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Integer(-700, 0, name='buy-cci-value'),
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]
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@staticmethod
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def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Define the sell strategy parameters to be used by hyperopt
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"""
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def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Sell strategy Hyperopt will build and use
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"""
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dataframe.loc[
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(
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(dataframe['macd'] < dataframe['macdsignal']) &
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(dataframe['cci'] >= params['sell-cci-value'])
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),
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'sell'] = 1
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return dataframe
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return populate_sell_trend
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@staticmethod
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def sell_indicator_space() -> List[Dimension]:
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"""
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Define your Hyperopt space for searching sell strategy parameters
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"""
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return [
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Integer(0, 700, name='sell-cci-value'),
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]
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@@ -1,8 +1,7 @@
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# --- Do not remove these libs ---
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from freqtrade.strategy.interface import IStrategy
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from typing import Dict, List
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from functools import reduce
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from freqtrade.strategy import IStrategy
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from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter
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from pandas import DataFrame
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# --------------------------------
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@@ -11,7 +10,6 @@ import talib.abstract as ta
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class MACDStrategy(IStrategy):
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"""
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author@: Gert Wohlgemuth
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idea:
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@@ -24,7 +22,14 @@ class MACDStrategy(IStrategy):
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MACD below MACD signal
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and CCI > 100
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freqtrade hyperopt --strategy MACDStrategy --hyperopt-loss <someLossFunction> --spaces buy sell
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The idea is to optimize only the CCI value.
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- Buy side: CCI between -700 and 0
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- Sell side: CCI between 0 and 700
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"""
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INTERFACE_VERSION = 2
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# Minimal ROI designed for the strategy.
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# This attribute will be overridden if the config file contains "minimal_roi"
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@@ -42,6 +47,19 @@ class MACDStrategy(IStrategy):
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# Optimal timeframe for the strategy
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timeframe = '5m'
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buy_cci = IntParameter(low=-700, high=0, default=-50, space='buy', optimize=True)
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sell_cci = IntParameter(low=0, high=700, default=100, space='sell', optimize=True)
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# Buy hyperspace params:
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buy_params = {
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"buy_cci": -48,
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}
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# Sell hyperspace params:
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sell_params = {
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"sell_cci": 687,
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}
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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macd = ta.MACD(dataframe)
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@@ -61,7 +79,8 @@ class MACDStrategy(IStrategy):
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dataframe.loc[
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(
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(dataframe['macd'] > dataframe['macdsignal']) &
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(dataframe['cci'] <= -50.0)
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(dataframe['cci'] <= self.buy_cci.value) &
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(dataframe['volume'] > 0) # Make sure Volume is not 0
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),
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'buy'] = 1
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@@ -76,7 +95,8 @@ class MACDStrategy(IStrategy):
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dataframe.loc[
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(
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(dataframe['macd'] < dataframe['macdsignal']) &
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(dataframe['cci'] >= 100.0)
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(dataframe['cci'] >= self.sell_cci.value) &
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(dataframe['volume'] > 0) # Make sure Volume is not 0
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),
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'sell'] = 1
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