buy: MACD crosses MACD signal above and CCI < -50 sell: MACD crosses MACD signal below and CCI > 100
Timeframe
5m
Direction
Long Only
Stoploss
-30.0%
Trailing Stop
No
ROI
0m: 5.0%, 20m: 4.0%, 30m: 3.0%, 60m: 1.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
# --- Do not remove these libs ---
import coingro.vendor.qtpylib.indicators as qtpylib
import talib.abstract as ta
from coingro.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
class MACDStrategyCrossed(IStrategy):
"""
buy:
MACD crosses MACD signal above
and CCI < -50
sell:
MACD crosses MACD signal below
and CCI > 100
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"60": 0.01,
"30": 0.03,
"20": 0.04,
"0": 0.05
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.3
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
dataframe['cci'] = ta.CCI(dataframe)
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['macd'], dataframe['macdsignal']) &
(dataframe['cci'] <= -50.0)
),
'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[
(
qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']) &
(dataframe['cci'] >= 100.0)
),
'sell'] = 1
return dataframe