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SMAOffset

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remiotore/ccxt-freqtrade/strategies/Discord_SMAOffset_converted.py · ★3 · ⑂2 · first seen 2026-07-28 · repo updated 2026-01-11

Basics mode: spot timeframe: 5m interface version: 3
Settings stoploss: -99.0 has minimal roi trailing custom stoploss process only new candles
Indicators Bollinger_Bands SMA talib technical
Concepts trailing
Methods custom_stoploss
15 related strategies (⧉ identical code, ≈ similar name)

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# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import datetime
from technical.util import resample_to_interval, resampled_merge
from datetime import datetime, timedelta
from freqtrade.persistence import Trade
from freqtrade.strategy import stoploss_from_open
# PLEAS CHANGE THIS SETTINGS WITH BACKTEST
base_nb_candles = 30  #something higher than 1
low_offset = 0.958  # something lower than 1
high_offset = 1.012  # something higher than 1

class SMAOffset(IStrategy):
    INTERFACE_VERSION = 3
    # ROI table:
    minimal_roi = {'0': 1}
    # Stoploss:
    stoploss = -99
    # Trailing stop:
    trailing_stop = False
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.5
    trailing_only_offset_is_reached = True
    # Optimal timeframe for the strategy
    timeframe = '5m'
    use_exit_signal = True
    exit_profit_only = True
    process_only_new_candles = True
    startup_candle_count = base_nb_candles
    plot_config = {'main_plot': {'sma_30_offset': {'color': 'orange'}, 'sma_30_offset_pos': {'color': 'orange'}}}
    use_custom_stoploss = False

    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float:
        # Make sure you have the longest interval first - these conditions are evaluated from top to bottom.
        if current_time - timedelta(minutes=1200) > trade.open_date_utc and current_profit < -0.05:
            return -0.001
        # return maximum stoploss value, keeping current stoploss price unchanged
        return 1

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # required for graphing
        bollinger = qtpylib.bollinger_bands(dataframe['close'], window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']
        dataframe['sma_30_offset'] = ta.SMA(dataframe, timeperiod=base_nb_candles) * low_offset
        dataframe['sma_30_offset_pos'] = ta.SMA(dataframe, timeperiod=base_nb_candles) * high_offset
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['close'] < dataframe['sma_30_offset']) & (dataframe['volume'] > 0), 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['close'] > dataframe['sma_30_offset_pos']) & (dataframe['volume'] > 0), 'exit_long'] = 1
        return dataframe