# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # isort: skip_file # --- Do not remove these libs --- import numpy as np import pandas as pd from datetime import datetime from typing import Dict, Optional, Union, Tuple from freqtrade.strategy import IStrategy import talib.abstract as ta import pandas_ta as pta class RSI_EMA(IStrategy): INTERFACE_VERSION = 3 timeframe = '15m' can_short = True # minimal_roi defines profit targets: # e.g., sell when 5% profit is reached at any time, # 2% after 30 minutes, 1% after 60 mins. minimal_roi = { "0": 0.05, "30": 0.02, "60": 0.01, "120": 0 } # stoploss - set to -15% to allow breathing room for futures stoploss = -0.15 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 = 200 def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) dataframe['ema200'] = ta.EMA(dataframe, timeperiod=200) return dataframe def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe.loc[ ( (dataframe['rsi'] < 40) & (dataframe['close'] > dataframe['ema200']) ), 'enter_long'] = 1 dataframe.loc[ ( (dataframe['rsi'] > 60) & (dataframe['close'] < dataframe['ema200']) ), 'enter_short'] = 1 return dataframe def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe.loc[ ( (dataframe['rsi'] > 70) ), 'exit_long'] = 1 dataframe.loc[ ( (dataframe['rsi'] < 30) ), 'exit_short'] = 1 return dataframe