Timeframe
5m
Direction
Long Only
Stoploss
-25.0%
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
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class MACD_EMA(IStrategy):
EMA_LONG_TERM = 200
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# 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
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
# EMA 200 for trend indicator
dataframe['ema_{}'.format(self.EMA_LONG_TERM)] = ta.EMA(
dataframe, timeperiod=self.EMA_LONG_TERM
)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal']) &
((dataframe['close'] > dataframe['ema_{}'.format(self.EMA_LONG_TERM)]))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']) &
(dataframe['close'] < dataframe['ema_{}'.format(self.EMA_LONG_TERM)])
),
'sell'] = 1
return dataframe