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
5
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy: Keltner Channel Breakout"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class KeltnerChannelStrategy(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["ema20"] = ta.EMA(dataframe, timeperiod=20)
dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)
dataframe["kc_upper"] = dataframe["ema20"] + 2 * dataframe["atr"]
dataframe["kc_lower"] = dataframe["ema20"] - 2 * dataframe["atr"]
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] > dataframe["kc_upper"])
& (dataframe["adx"] > 25)
& (dataframe["rsi"] > 50) & (dataframe["rsi"] < 70)
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] < dataframe["ema20"]) | (dataframe["rsi"] > 75),
"exit_long",
] = 1
return dataframe