ASDTSRockwellTrading_3

from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from hyperopt import hp
from functools import reduce
from pandas import DataFrame


import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


class ASDTSRockwellTrading_3(IStrategy):
    """
    trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0
    author@: Gert Wohlgemuth

    idea:

        uptrend definition:
            MACD above 0 line AND above MACD signal


        downtrend definition:
            MACD below 0 line and below MACD signal

        sell definition:
            MACD below MACD signal

    it's basically a very simple MACD based strategy and we ignore the definition of the entry and exit points in this case, since the trading bot, will take of this already

    """


    minimal_roi = {
        "60":  0.01,
        "30":  0.03,
        "20":  0.04,
        "0":  0.05
    }


    stoploss = -0.3

    ticker_interval = '5m'

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

        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']

        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                (dataframe['macd'] > 0) &
                (dataframe['macd'] > dataframe['macdsignal'])
            ),
            'buy'] = 1

        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                (dataframe['macd'] < dataframe['macdsignal'])
            ),
            'sell'] = 1
        return dataframe