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BaseFuturesStrategy

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freqle/uploads/user-90abf0da8f3178f3/base_converted.py · first seen 2026-07-28

Basics mode: spot timeframe: 5m interface version: 3
Settings stoploss: -0.03 has minimal roi trailing startup candle count: 300
Concepts trailing
15 related strategies (⧉ identical code, ≈ similar name)

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from freqtrade.strategy import IStrategy
from pandas import DataFrame
from typing import Dict, List

class BaseFuturesStrategy(IStrategy):
    INTERFACE_VERSION = 3
    '\n    Base class for futures trading strategies.\n    Provides common functionality for all futures strategies.\n    '
    # Define minimal ROI
    minimal_roi = {'0': 0.05}
    # Define stoploss
    stoploss = -0.03
    # Use trailing stop
    trailing_stop = False
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.02
    trailing_only_offset_is_reached = False
    # Order types
    order_types = {'entry': 'limit', 'exit': 'limit', 'stoploss': 'market', 'stoploss_on_exchange': False}
    # Timeframe for the strategy
    timeframe = '5m'
    # Stake amount in USDT
    stake_amount = 0.01
    # Number of startup candles
    startup_candle_count = 300
    # Unfilled timeout
    unfilledtimeout = {'entry': 10, 'exit': 10, 'exit_timeout_count': 0, 'unit': 'seconds'}

    def informative_pairs(self) -> List[tuple]:
        """
        Define additional informative pairs.
        """
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        This method is invoked for each candle and should implement the indicators creation logic.
        """
        # Base implementation - to be overridden by specific strategies
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        This method is invoked for each candle and should implement the buy signal logic.
        """
        # Base implementation - to be overridden by specific strategies
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        This method is invoked for each candle and should implement the sell signal logic.
        """
        # Base implementation - to be overridden by specific strategies
        return dataframe