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zhutoutoutousan
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"""
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Example Trading Strategies
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These are example implementations of trading strategies that you can use as templates
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or modify for your own strategies.
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"""
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from datetime import datetime
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from typing import Dict, Any, Optional
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import MetaTrader5 as mt5
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from base_strategy import BaseStrategy
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class RSIScalpingStrategy(BaseStrategy):
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"""
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RSI Scalping Strategy - Example implementation
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Entry:
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- Buy when RSI crosses above oversold level
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- Sell when RSI crosses below overbought level
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Exit:
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- RSI reaches target levels
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- Stop loss and take profit
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"""
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def __init__(self, symbol: str, timeframe: int, initial_balance: float = 10000.0,
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rsi_period: int = 14, rsi_overbought: float = 70, rsi_oversold: float = 30,
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rsi_target_buy: float = 80, rsi_target_sell: float = 20,
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lot_size: float = 0.1, stop_loss_pips: int = 50, take_profit_pips: int = 100):
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super().__init__(symbol, timeframe, initial_balance)
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self.rsi_period = rsi_period
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self.rsi_overbought = rsi_overbought
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self.rsi_oversold = rsi_oversold
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self.rsi_target_buy = rsi_target_buy
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self.rsi_target_sell = rsi_target_sell
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self.lot_size = lot_size
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self.stop_loss_pips = stop_loss_pips
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self.take_profit_pips = take_profit_pips
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# Track previous RSI for crossover detection
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self.prev_rsi = None
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def get_required_indicators(self) -> Dict[str, Dict[str, Any]]:
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return {
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'rsi': {
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'period': self.rsi_period,
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'applied_price': mt5.PRICE_CLOSE
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}
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}
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def on_bar(self, bar_data: Dict[str, Any]) -> None:
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rsi = bar_data.get('rsi')
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if rsi is None:
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return
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current_price = bar_data['close']
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spread = bar_data.get('spread', 0)
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# Check spread
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if spread > self.max_spread:
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return
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# Check if we have a position
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if self.position is not None:
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# Check exit conditions
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if self.position['type'] == 'BUY':
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if rsi >= self.rsi_target_buy:
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self.close_position(current_price)
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elif self.position['type'] == 'SELL':
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if rsi <= self.rsi_target_sell:
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self.close_position(current_price)
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else:
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# Check entry conditions
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if self.prev_rsi is not None:
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# Buy signal: RSI crosses above oversold
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if self.prev_rsi <= self.rsi_oversold and rsi > self.rsi_oversold:
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sl = current_price - (self.stop_loss_pips / 10000)
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tp = current_price + (self.take_profit_pips / 10000)
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self.open_position('BUY', self.lot_size, current_price, sl, tp, 'RSI Scalping Buy')
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# Sell signal: RSI crosses below overbought
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elif self.prev_rsi >= self.rsi_overbought and rsi < self.rsi_overbought:
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sl = current_price + (self.stop_loss_pips / 10000)
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tp = current_price - (self.take_profit_pips / 10000)
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self.open_position('SELL', self.lot_size, current_price, sl, tp, 'RSI Scalping Sell')
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self.prev_rsi = rsi
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def get_parameters(self) -> Dict[str, Any]:
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return {
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'rsi_period': self.rsi_period,
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'rsi_overbought': self.rsi_overbought,
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'rsi_oversold': self.rsi_oversold,
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'rsi_target_buy': self.rsi_target_buy,
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'rsi_target_sell': self.rsi_target_sell,
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'lot_size': self.lot_size,
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'stop_loss_pips': self.stop_loss_pips,
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'take_profit_pips': self.take_profit_pips
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}
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class EMAStrategy(BaseStrategy):
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"""
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EMA Crossover Strategy
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Entry:
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- Buy when price crosses above EMA
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- Sell when price crosses below EMA
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Exit:
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- Opposite crossover
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- Stop loss and take profit
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"""
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def __init__(self, symbol: str, timeframe: int, initial_balance: float = 10000.0,
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ema_period: int = 50, lot_size: float = 0.1,
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stop_loss_pips: int = 50, take_profit_pips: int = 100):
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super().__init__(symbol, timeframe, initial_balance)
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self.ema_period = ema_period
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self.lot_size = lot_size
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self.stop_loss_pips = stop_loss_pips
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self.take_profit_pips = take_profit_pips
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self.prev_price = None
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self.prev_ema = None
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def get_required_indicators(self) -> Dict[str, Dict[str, Any]]:
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return {
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'ema': {
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'period': self.ema_period,
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'applied_price': mt5.PRICE_CLOSE
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}
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}
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def on_bar(self, bar_data: Dict[str, Any]) -> None:
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ema = bar_data.get('ema')
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current_price = bar_data['close']
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if ema is None:
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return
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# Check if we have a position
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if self.position is not None:
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# Exit on opposite crossover
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if self.position['type'] == 'BUY' and current_price < ema:
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self.close_position(current_price)
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elif self.position['type'] == 'SELL' and current_price > ema:
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self.close_position(current_price)
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else:
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# Check entry conditions
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if self.prev_price is not None and self.prev_ema is not None:
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# Buy signal: price crosses above EMA
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if self.prev_price <= self.prev_ema and current_price > ema:
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sl = current_price - (self.stop_loss_pips / 10000)
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tp = current_price + (self.take_profit_pips / 10000)
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self.open_position('BUY', self.lot_size, current_price, sl, tp, 'EMA Crossover Buy')
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# Sell signal: price crosses below EMA
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elif self.prev_price >= self.prev_ema and current_price < ema:
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sl = current_price + (self.stop_loss_pips / 10000)
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tp = current_price - (self.take_profit_pips / 10000)
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self.open_position('SELL', self.lot_size, current_price, sl, tp, 'EMA Crossover Sell')
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self.prev_price = current_price
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self.prev_ema = ema
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def get_parameters(self) -> Dict[str, Any]:
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return {
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'ema_period': self.ema_period,
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'lot_size': self.lot_size,
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'stop_loss_pips': self.stop_loss_pips,
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'take_profit_pips': self.take_profit_pips
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}
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class RSIReversalStrategy(BaseStrategy):
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"""
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RSI Reversal Strategy - Similar to your MQL5 RSI Reversal strategies
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Entry:
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- Buy when RSI is oversold and starts rising
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- Sell when RSI is overbought and starts falling
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Exit:
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- RSI reaches neutral level
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- Stop loss and take profit
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"""
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def __init__(self, symbol: str, timeframe: int, initial_balance: float = 10000.0,
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rsi_period: int = 14, rsi_overbought: float = 70, rsi_oversold: float = 30,
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rsi_exit: float = 50, lot_size: float = 0.1,
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stop_loss_pips: int = 50, take_profit_pips: int = 100):
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super().__init__(symbol, timeframe, initial_balance)
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self.rsi_period = rsi_period
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self.rsi_overbought = rsi_overbought
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self.rsi_oversold = rsi_oversold
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self.rsi_exit = rsi_exit
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self.lot_size = lot_size
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self.stop_loss_pips = stop_loss_pips
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self.take_profit_pips = take_profit_pips
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self.prev_rsi = None
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def get_required_indicators(self) -> Dict[str, Dict[str, Any]]:
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return {
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'rsi': {
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'period': self.rsi_period,
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'applied_price': mt5.PRICE_CLOSE
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}
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}
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def on_bar(self, bar_data: Dict[str, Any]) -> None:
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rsi = bar_data.get('rsi')
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if rsi is None:
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return
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current_price = bar_data['close']
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# Check if we have a position
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if self.position is not None:
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# Exit when RSI reaches neutral level
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if self.position['type'] == 'BUY' and rsi >= self.rsi_exit:
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self.close_position(current_price)
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elif self.position['type'] == 'SELL' and rsi <= self.rsi_exit:
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self.close_position(current_price)
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else:
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# Check entry conditions
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if self.prev_rsi is not None:
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# Buy signal: RSI was oversold and now rising
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if self.prev_rsi < self.rsi_oversold and rsi > self.prev_rsi:
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sl = current_price - (self.stop_loss_pips / 10000)
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tp = current_price + (self.take_profit_pips / 10000)
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self.open_position('BUY', self.lot_size, current_price, sl, tp, 'RSI Reversal Buy')
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# Sell signal: RSI was overbought and now falling
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elif self.prev_rsi > self.rsi_overbought and rsi < self.prev_rsi:
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sl = current_price + (self.stop_loss_pips / 10000)
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tp = current_price - (self.take_profit_pips / 10000)
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self.open_position('SELL', self.lot_size, current_price, sl, tp, 'RSI Reversal Sell')
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self.prev_rsi = rsi
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def get_parameters(self) -> Dict[str, Any]:
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return {
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'rsi_period': self.rsi_period,
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'rsi_overbought': self.rsi_overbought,
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'rsi_oversold': self.rsi_oversold,
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'rsi_exit': self.rsi_exit,
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'lot_size': self.lot_size,
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'stop_loss_pips': self.stop_loss_pips,
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'take_profit_pips': self.take_profit_pips
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}
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