Timeframe
5m
Direction
Long Only
Stoploss
-4.0%
Trailing Stop
No
ROI
0m: 8.0%, 120m: 4.0%
Interface Version
N/A
Startup Candles
25
Indicators
4
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy: VWAP Reversion Strategy"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class VwapReversionStrategy(IStrategy):
timeframe = "5m"
minimal_roi = {"0": 0.08, "120": 0.04}
stoploss = -0.04
startup_candle_count = 25
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
tp = (dataframe["high"] + dataframe["low"] + dataframe["close"]) / 3
dataframe["vwap"] = (tp * dataframe["volume"]).rolling(20).sum() / dataframe["volume"].rolling(20).sum()
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
dataframe["ema100"] = ta.EMA(dataframe, timeperiod=100)
dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)
dataframe["below_vwap"] = (dataframe["close"] < dataframe["vwap"]).astype(int)
dataframe["below_vwap_prev"] = dataframe["below_vwap"].shift(1)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["below_vwap"] == 0) & (dataframe["below_vwap_prev"] == 1)
& (dataframe["close"] > dataframe["ema100"])
& (dataframe["rsi"] < 65)
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] > dataframe["vwap"] * 1.02) | (dataframe["rsi"] > 72),
"exit_long",
] = 1
return dataframe