Timeframe
5m
Direction
Long Only
Stoploss
-4.0%
Trailing Stop
No
ROI
0m: 8.0%, 120m: 4.0%
Interface Version
N/A
Startup Candles
20
Indicators
3
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy 5: Stochastic Oversold Bounce"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class StochasticOversoldStrategy(IStrategy):
timeframe = "5m"
minimal_roi = {"0": 0.08, "120": 0.04}
stoploss = -0.04
startup_candle_count = 20
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
stoch = ta.STOCH(dataframe, fastk_period=14, slowk_period=3, slowd_period=3)
dataframe["stoch_k"] = stoch["slowk"]
dataframe["stoch_d"] = stoch["slowd"]
dataframe["stoch_k_prev"] = dataframe["stoch_k"].shift(1)
dataframe["stoch_d_prev"] = dataframe["stoch_d"].shift(1)
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["stoch_k"] > dataframe["stoch_d"])
& (dataframe["stoch_k_prev"] <= dataframe["stoch_d_prev"])
& (dataframe["stoch_k"] < 30)
& (dataframe["close"] > dataframe["ema50"])
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["stoch_k"] > 80) | (dataframe["rsi"] > 70),
"exit_long",
] = 1
return dataframe