Timeframe
N/A
Direction
Long Only
Stoploss
-20.0%
Trailing Stop
No
ROI
0m: 10.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class AlligatorStrat_222(IStrategy):
"""
author@: Gert Wohlgemuth
idea:
buys and sells on crossovers - doesn't really perfom that well and its just a proof of concept
"""
minimal_roi = {
"0": 0.1
}
stoploss = -0.2
ticker_interval = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['SMAShort'] = ta.SMA(dataframe, timeperiod=5)
dataframe['SMAMedium'] = ta.SMA(dataframe, timeperiod=8)
dataframe['SMALong'] = ta.SMA(dataframe, timeperiod=13)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(
qtpylib.crossed_above(dataframe['SMAShort'], dataframe['SMAMedium']) &
((dataframe['macd'] > -0.00001)) &
(dataframe['macd'] > dataframe['macdsignal'])
)
|
qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
((dataframe['close'] < dataframe['SMAMedium']) &
(dataframe['macd'] < dataframe['macdsignal'])
)
|
qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal'])
),
'sell'] = 1
return dataframe