MetaRegimeStrategy

from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import pandas as pd

class MetaRegimeStrategy(IStrategy):

    timeframe = "1h"

    can_short = True

    startup_candle_count = 250

    stoploss = -0.08

    minimal_roi = {
        "0": 0.05
    }

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

        dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50)
        dataframe["ema200"] = ta.EMA(dataframe, timeperiod=200)

        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)

        dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)

        dataframe["atr_ma"] = dataframe["atr"].rolling(50).mean()

        dataframe["bb_upper"], dataframe["bb_mid"], dataframe["bb_lower"] = ta.BBANDS(
            dataframe["close"],
            timeperiod=20
        )

        dataframe["volume_mean"] = dataframe["volume"].rolling(20).mean()

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame,
                             metadata: dict) -> DataFrame:

        bull = (
            (dataframe["ema50"] > dataframe["ema200"])
            &
            (dataframe["adx"] > 25)
        )

        bear = (
            (dataframe["ema50"] < dataframe["ema200"])
            &
            (dataframe["adx"] > 25)
        )

        ranging = (
            (dataframe["adx"] < 20)
        )

        high_vol = (
            dataframe["atr"] >
            dataframe["atr_ma"] * 1.5
        )

        dataframe.loc[
            (
                bull
                &
                (dataframe["close"] > dataframe["ema50"])
                &
                (dataframe["volume"] > dataframe["volume_mean"])
            ),
            "enter_long"
        ] = 1

        dataframe.loc[
            (
                bear
                &
                (dataframe["close"] < dataframe["ema50"])
                &
                (dataframe["volume"] > dataframe["volume_mean"])
            ),
            "enter_short"
        ] = 1

        dataframe.loc[
            (
                ranging
                &
                (dataframe["close"] < dataframe["bb_lower"])
            ),
            "enter_long"
        ] = 1

        dataframe.loc[
            (
                high_vol
                &
                (dataframe["close"] > dataframe["bb_upper"])
                &
                (dataframe["volume"] >
                 dataframe["volume_mean"] * 1.2)
            ),
            "enter_long"
        ] = 1

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame,
                            metadata: dict) -> DataFrame:

        dataframe.loc[
            (
                dataframe["close"] <
                dataframe["ema50"]
            ),
            "exit_long"
        ] = 1

        dataframe.loc[
            (
                dataframe["close"] >
                dataframe["ema50"]
            ),
            "exit_short"
        ] = 1

        return dataframe