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songkunling
2025-08-14 23:17:12 +08:00
parent e8226edd96
commit 2ad610d8fd
23 changed files with 6022 additions and 586 deletions
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execution/realtime_trader.py
+159 -20
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@@ -1,35 +1,171 @@
import time
import signal
import sys
import json
import pandas as pd
from datetime import datetime
from logger import logger
from config import SYMBOL, TIMEFRAME, REALTIME_CONFIG, SIGNAL_THRESHOLDS
from config import SYMBOL, TIMEFRAME, REALTIME_CONFIG
from core.risk import RiskController
from execution.dynamic_weights import DynamicWeightManager
from strategies.wave_theory import WaveTheoryStrategy
from strategies.ma_cross import MACrossStrategy
from strategies.rsi import RSIStrategy
from strategies.bollinger import BollingerStrategy
from strategies.mean_reversion import MeanReversionStrategy
from strategies.momentum_breakout import MomentumBreakoutStrategy
from strategies.macd import MACDStrategy
from strategies.kdj import KDJStrategy
from strategies.turtle import TurtleStrategy
from strategies.daily_breakout import DailyBreakoutStrategy
class RealtimeTrader:
"""实时交易器 (已重构为依赖注入)"""
"""实时交易器 (已重构为依赖注入和市场状态参数切换)"""
def __init__(self, data_provider, update_interval=60):
self.data_provider = data_provider
self.update_interval = update_interval
self.running = False
self.risk_controller = None
self.weight_manager = None
self.regime_params = {}
self.regime_detector = None
self.current_regime = 'Ranging' # Default regime
self.strategy_instances = {}
self.current_weights = {}
self.signal_thresholds = {}
self.strategy_config_key_to_class = {
"ma_cross": MACrossStrategy,
"rsi": RSIStrategy,
"bollinger": BollingerStrategy,
"mean_reversion": MeanReversionStrategy,
"momentum_breakout": MomentumBreakoutStrategy,
"macd": MACDStrategy,
"kdj": KDJStrategy,
"turtle": TurtleStrategy,
"daily_breakout": DailyBreakoutStrategy,
"wave_theory": WaveTheoryStrategy
}
def _initialize(self):
if not self.data_provider.initialize():
return False
self.risk_controller = RiskController(self.data_provider)
self.weight_manager = DynamicWeightManager(self.data_provider)
# Load regime parameters
try:
with open('regime_optimal_params.json', 'r') as f:
self.regime_params = json.load(f)
logger.info("成功加载市场状态参数文件: regime_optimal_params.json")
except FileNotFoundError:
logger.error("错误: 未找到 regime_optimal_params.json。请先运行 regime_optimizer.py。")
return False
except json.JSONDecodeError:
logger.error("错误: regime_optimal_params.json 文件格式不正确。")
return False
# Instantiate regime detector
self.regime_detector = WaveTheoryStrategy(self.data_provider, SYMBOL, TIMEFRAME)
# Create strategy instances
self._create_strategy_instances()
self.risk_controller.sync_state()
signal.signal(signal.SIGINT, self._signal_handler)
signal.signal(signal.SIGTERM, self._signal_handler)
logger.info("实时交易系统初始化完成")
return True
def _create_strategy_instances(self):
for name, strategy_class in self.strategy_config_key_to_class.items():
# Use the name that corresponds to the keys in the parameter file (e.g., 'MACrossStrategy')
class_name = strategy_class.__name__
self.strategy_instances[class_name] = strategy_class(self.data_provider, SYMBOL, TIMEFRAME)
logger.info(f"创建了 {len(self.strategy_instances)} 个策略实例")
def _update_parameters_for_regime(self):
# 1. Determine current regime
df_history = self.data_provider.get_historical_data(SYMBOL, TIMEFRAME, count=200)
if df_history is None or df_history.empty:
logger.warning("无法获取历史数据来判断市场状态，将使用上一个状态。")
return
df_history = pd.DataFrame(df_history)
df_history.set_index(pd.to_datetime(df_history['time'], unit='s'), inplace=True)
df_with_indicators = self.regime_detector._calculate_indicators(df_history.copy())
last_row = df_with_indicators.iloc[-1]
new_regime = "Ranging" # Default
if not pd.isna(last_row['adx']):
if last_row['adx'] < self.regime_detector.adx_threshold:
new_regime = "Ranging"
elif last_row['ema_short'] > last_row['ema_medium'] > last_row['ema_long']:
new_regime = "Uptrend"
else:
new_regime = "Downtrend"
# 2. If regime changed, update parameters
if new_regime != self.current_regime:
self.current_regime = new_regime
logger.info(f"市场状态已切换为: {self.current_regime}")
regime_config = self.regime_params.get(self.current_regime)
if not regime_config:
logger.error(f"在参数文件中未找到状态 {self.current_regime} 的配置，将使用默认参数。")
return
params = regime_config.get('best_parameters', {})
# Group parameters by component (strategy, risk, etc.)
strategy_params = {strat_name: {} for strat_name in self.strategy_instances.keys()}
risk_params = {}
temp_weights = {}
prefix_map = {
'MACrossStrategy': 'ma_cross_',
'RSIStrategy': 'rsi_',
'BollingerStrategy': 'bollinger_',
'MACDStrategy': 'macd_',
'MeanReversionStrategy': 'mean_reversion_',
'MomentumBreakoutStrategy': 'momentum_breakout_',
'KDJStrategy': 'kdj_',
'TurtleStrategy': 'turtle_',
'DailyBreakoutStrategy': 'daily_breakout_',
'WaveTheoryStrategy': 'wave_'
}
for key, value in params.items():
if key.startswith('weight_'):
strategy_name = key.replace('weight_', '')
temp_weights[strategy_name] = value
elif key in ['buy_threshold', 'sell_threshold']:
self.signal_thresholds[key] = value
elif hasattr(self.risk_controller, key):
risk_params[key] = value
else:
for strat_name, prefix in prefix_map.items():
if key.startswith(prefix):
param_name = key.replace(prefix, '')
# BUG FIX: Handle the 'wave_period' special case
if strat_name == 'WaveTheoryStrategy' and key == 'wave_period':
param_name = 'wave_period'
strategy_params[strat_name][param_name] = value
break
# Update parameters in a batch
for strat_name, params_dict in strategy_params.items():
if params_dict:
self.strategy_instances[strat_name].set_params(params_dict)
if risk_params:
for key, value in risk_params.items():
setattr(self.risk_controller, key, value)
self.current_weights = temp_weights
logger.info(f"已为 {self.current_regime} 状态加载新参数和权重。")
def _signal_handler(self, signum, frame):
logger.info(f"接收到信号 {signum}，准备退出...")
@@ -38,22 +174,29 @@ class RealtimeTrader:
def _run_cycle(self):
try:
self.risk_controller.sync_state()
# Update parameters based on current market regime
self._update_parameters_for_regime()
current_price = self.data_provider.get_current_price(SYMBOL)
if not current_price:
logger.warning("无法获取当前价格，跳过本次循环")
return
strategies_with_weights = self.weight_manager.get_current_strategies_and_weights()
signals, weights = [], []
strategies_with_weights = []
for strat_name, strat_instance in self.strategy_instances.items():
weight = self.current_weights.get(strat_name, 0.0)
if weight > 0: # Only calculate signal if weight is positive
strategies_with_weights.append((strat_instance, weight))
signals.append(strat_instance.generate_signal())
weights.append(weight)
if not strategies_with_weights: return
signals, weights = [], []
for strat, weight in strategies_with_weights:
signals.append(strat.generate_signal())
weights.append(weight)
# 打印详细信号日志
logger.info("--- 信号计算详情 ---")
logger.info(f"--- 信号计算详情 (状态: {self.current_regime}) ---")
for i, (strat, weight) in enumerate(strategies_with_weights):
signal = signals[i]
weighted_signal = signal * weight
@@ -63,11 +206,9 @@ class RealtimeTrader:
weighted_signal_sum = sum(s * w for s, w in zip(signals, weights))
buy_threshold = SIGNAL_THRESHOLDS.get('buy_threshold', 1.5)
sell_threshold = SIGNAL_THRESHOLDS.get('sell_threshold', -1.5)
buy_threshold = self.signal_thresholds.get('buy_threshold', 1.5)
sell_threshold = self.signal_thresholds.get('sell_threshold', -1.5)
logger.info(f"加权信号: {weighted_signal_sum:.2f} (买入阈值: {buy_threshold}, 卖出阈值: {sell_threshold})")
# logger.info(f"信号比较: {weighted_signal_sum} > {buy_threshold} = {weighted_signal_sum > buy_threshold}")
# logger.info(f"信号比较: {weighted_signal_sum} < {sell_threshold} = {weighted_signal_sum < sell_threshold}")
direction = None
if weighted_signal_sum > buy_threshold:
@@ -94,8 +235,7 @@ class RealtimeTrader:
logger.info(f" 当前持仓: {len(open_positions)} 个")
for pos in open_positions:
pnl_pct = self.risk_controller.position_manager._calculate_pnl_pct(pos, current_price['last'])
# 计算持仓时间
holding_time = current_price['time'] - pos['entry_time']
holding_time = datetime.fromtimestamp(current_price['time']) - pos['entry_time']
holding_minutes = holding_time.total_seconds() / 60
logger.info(f" - Ticket {pos['ticket']}: {pos['position_type']} {pos['symbol']} @ {pos['entry_price']:.2f} | 持仓时间: {holding_minutes:.1f}分钟 | 浮动盈亏: {pnl_pct:.2%}")
@@ -137,5 +277,4 @@ class RealtimeTrader:
finally:
self.data_provider.shutdown()
logger.info("实时交易系统已停止")
sys.exit(0)
sys.exit(0)