80 lines
2.4 KiB
Python
80 lines
2.4 KiB
Python
|
|
||
|
|
# --- Do not remove these libs ---
|
||
|
|
from freqtrade.strategy.interface import IStrategy
|
||
|
|
from typing import Dict, List
|
||
|
|
from hyperopt import hp
|
||
|
|
from functools import reduce
|
||
|
|
from pandas import DataFrame
|
||
|
|
# --------------------------------
|
||
|
|
|
||
|
|
import talib.abstract as ta
|
||
|
|
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||
|
|
|
||
|
|
|
||
|
|
class Long(IStrategy):
|
||
|
|
"""
|
||
|
|
|
||
|
|
author@: Gert Wohlgemuth
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Minimal ROI designed for the strategy.
|
||
|
|
# This attribute will be overridden if the config file contains "minimal_roi"
|
||
|
|
minimal_roi = {
|
||
|
|
"60": 0.05,
|
||
|
|
"30": 0.06,
|
||
|
|
"20": 0.07,
|
||
|
|
"0": 0.08
|
||
|
|
}
|
||
|
|
|
||
|
|
# Optimal stoploss designed for the strategy
|
||
|
|
# This attribute will be overridden if the config file contains "stoploss"
|
||
|
|
stoploss = -0.15
|
||
|
|
|
||
|
|
# Optimal ticker interval for the strategy
|
||
|
|
ticker_interval = 5
|
||
|
|
|
||
|
|
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
|
||
|
|
|
||
|
|
macd = ta.MACD(dataframe)
|
||
|
|
dataframe['macd'] = macd['macd']
|
||
|
|
dataframe['macdsignal'] = macd['macdsignal']
|
||
|
|
dataframe['macdhist'] = macd['macdhist']
|
||
|
|
dataframe['cci'] = ta.CCI(dataframe)
|
||
|
|
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=50)
|
||
|
|
|
||
|
|
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
|
||
|
|
dataframe['bb_lowerband'] = bollinger['lower']
|
||
|
|
dataframe['bb_middleband'] = bollinger['mid']
|
||
|
|
dataframe['bb_upperband'] = bollinger['upper']
|
||
|
|
return dataframe
|
||
|
|
|
||
|
|
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
|
||
|
|
"""
|
||
|
|
Based on TA indicators, populates the buy signal for the given dataframe
|
||
|
|
:param dataframe: DataFrame
|
||
|
|
:return: DataFrame with buy column
|
||
|
|
"""
|
||
|
|
dataframe.loc[
|
||
|
|
(
|
||
|
|
(dataframe['macd'] > dataframe['macdsignal']) &
|
||
|
|
(dataframe['macd'] > 0) &
|
||
|
|
(dataframe['cci'] <= 0.0)
|
||
|
|
),
|
||
|
|
'buy'] = 1
|
||
|
|
|
||
|
|
return dataframe
|
||
|
|
|
||
|
|
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
|
||
|
|
"""
|
||
|
|
Based on TA indicators, populates the sell signal for the given dataframe
|
||
|
|
:param dataframe: DataFrame
|
||
|
|
:return: DataFrame with buy column
|
||
|
|
"""
|
||
|
|
dataframe.loc[
|
||
|
|
(
|
||
|
|
(dataframe['tema'] < dataframe['close'])
|
||
|
|
),
|
||
|
|
'sell'] = 1
|
||
|
|
return dataframe
|