Timeframe
5m
Direction
Long Only
Stoploss
-5.0%
Trailing Stop
No
ROI
0m: 10.0%, 180m: 5.0%
Interface Version
N/A
Startup Candles
25
Indicators
3
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy: ADX Strength Entry Strategy"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class AdxStrengthStrategy(IStrategy):
timeframe = "5m"
minimal_roi = {"0": 0.10, "180": 0.05}
stoploss = -0.05
startup_candle_count = 25
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
dataframe["adx_prev"] = dataframe["adx"].shift(1)
dataframe["plus_di"] = ta.PLUS_DI(dataframe, timeperiod=14)
dataframe["minus_di"] = ta.MINUS_DI(dataframe, timeperiod=14)
dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50)
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["adx"] > 25) & (dataframe["adx_prev"] <= 25)
& (dataframe["plus_di"] > dataframe["minus_di"])
& (dataframe["close"] > dataframe["ema50"])
& (dataframe["rsi"] < 68)
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["plus_di"] < dataframe["minus_di"])
| (dataframe["adx"] < 15)
| (dataframe["rsi"] > 74),
"exit_long",
] = 1
return dataframe