PYTHON TrendRideStrategy.py

# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
from functools import reduce
import numpy as np
import pandas as pd
from datetime import datetime, timedelta, timezone
from pandas import DataFrame
from typing import Dict, Optional, Union, Tuple

from freqtrade.strategy import (
    IStrategy,
    Trade,
    Order,
    PairLocks,
    informative,
    BooleanParameter,
    CategoricalParameter,
    DecimalParameter,
    IntParameter,
    RealParameter,
    timeframe_to_minutes,
    timeframe_to_next_date,
    timeframe_to_prev_date,
    merge_informative_pair,
    stoploss_from_absolute,
    stoploss_from_open,
    AnnotationType,
)

import talib.abstract as ta
from technical import qtpylib


class TrendRideStrategy(IStrategy):
    """
    Trend Following — Enter on EMA crossover in direction of trend,
    stay until trend reverses. No RSI exits — let trends run.
    """
    INTERFACE_VERSION = 3

    timeframe = "5m"
    can_short: bool = False

    minimal_roi = {}

    stoploss = -0.05

    trailing_stop = True
    trailing_stop_positive = 0.02
    trailing_stop_positive_offset = 0.04
    trailing_only_offset_is_reached = True

    process_only_new_candles = True
    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = False

    startup_candle_count: int = 300

    # Hyperopt parameters
    buy_ema_fast = IntParameter(5, 20, default=8, space="buy", optimize=True)
    buy_ema_slow = IntParameter(20, 100, default=50, space="buy", optimize=True)
    buy_volume_mult = RealParameter(0.5, 2.0, default=1.0, space="buy", optimize=True)

    sell_trail_offset = RealParameter(0.01, 0.06, default=0.03, space="sell", optimize=True)
    sell_trail_stop = RealParameter(0.01, 0.04, default=0.02, space="sell", optimize=True)

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['ema8'] = ta.EMA(dataframe, timeperiod=8)
        dataframe['ema13'] = ta.EMA(dataframe, timeperiod=13)
        dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21)
        dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
        dataframe['ema200'] = ta.EMA(dataframe, timeperiod=200)
        dataframe['rsi'] = ta.RSI(dataframe)
        dataframe['adx'] = ta.ADX(dataframe)
        dataframe['volume_mean'] = dataframe['volume'].rolling(20).mean()
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_above(dataframe['ema8'], dataframe['ema21'])) &
                (dataframe['close'] > dataframe['ema200']) &
                (dataframe['volume'] > dataframe['volume_mean'] * self.buy_volume_mult.value) &
                (dataframe['adx'] > 15) &
                (dataframe['volume'] > 0)
            ),
            'enter_long'
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_below(dataframe['ema8'], dataframe['ema21'])) &
                (dataframe['volume'] > 0)
            ),
            'exit_long'
        ] = 1
        return dataframe