initial-import: 2026-04-11 21:18:55

2026-04-11 21:18:55 +08:00
commit 5e6b2d73eb
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+#!/usr/bin/env python3
+"""
+在Docker容器内直接运行回测 - 不经过HTTP API
+针对 510300.SSE 的单票回测
+"""
+
+# ============================================
+# 1. 风控模块代码 (risk_control.py)
+# ============================================
+RISK_CONTROL_CODE = '''
+"""
+风控模块 - 量化策略风控系统
+功能：
+1. 单票15%止损规则
+2. 整体回撤分级风控（10%/20%/25% 分级降仓）
+3. 黑天鹅过滤（ST、跌停、财务造假排除）
+
+Author: 关羽（云长）
+Date: 2026-03-27
+"""
+
+from dataclasses import dataclass
+import pandas as pd
+
+
+@dataclass
+class StockInfo:
+    """单票基本信息"""
+    code: str
+    name: str
+    cost_price: float
+    current_price: float
+    is_st: bool = False
+    is_limit_down: bool = False
+    is_fraud: bool = False
+    volume: float = 0.0  # 日成交额（亿）
+
+
+@dataclass
+class PortfolioInfo:
+    """组合信息"""
+    total_capital: float
+    current_capital: float
+    positions: dict[str, float]  # code -> position_size
+
+
+class SingleStockRiskControl:
+    """单票风控：15%止损规则"""
+    
+    def __init__(self, stop_loss_pct: float = 0.15):
+        self.stop_loss_pct = stop_loss_pct
+    
+    def check_stop_loss(self, stock: StockInfo) -> bool:
+        """检查是否触发止损"""
+        if stock.cost_price <= 0:
+            return False
+        
+        drawdown = (stock.current_price - stock.cost_price) / stock.cost_price
+        return drawdown <= -self.stop_loss_pct
+    
+    def get_drawdown(self, stock: StockInfo) -> float:
+        """计算单票当前回撤"""
+        if stock.cost_price <= 0:
+            return 0.0
+        return (stock.current_price - stock.cost_price) / stock.cost_price
+
+
+class PortfolioDrawdownRiskControl:
+    """整体回撤分级风控"""
+    
+    def __init__(self, drawdown_levels=None, reduce_ratios=None):
+        self.drawdown_levels = drawdown_levels or [0.10, 0.20, 0.25]
+        self.reduce_ratios = reduce_ratios or [0.50, 0.25, 0.00]
+    
+    def calculate_total_drawdown(self, portfolio: PortfolioInfo) -> float:
+        """计算组合总回撤"""
+        if portfolio.total_capital <= 0:
+            return 0.0
+        return (portfolio.total_capital - portfolio.current_capital) / portfolio.total_capital
+    
+    def get_target_position_ratio(self, portfolio: PortfolioInfo) -> float:
+        """获取目标仓位比例"""
+        drawdown = self.calculate_total_drawdown(portfolio)
+        
+        for level, ratio in reversed(list(zip(self.drawdown_levels, self.reduce_ratios))):
+            if drawdown >= level:
+                return ratio
+        
+        return 1.0
+
+
+class RiskController:
+    """总风控控制器"""
+    
+    def __init__(self):
+        self.single_stock_rc = SingleStockRiskControl()
+        self.portfolio_rc = PortfolioDrawdownRiskControl()
+'''
+
+# ============================================
+# 2. 简化策略代码 (回测510300.SSE单票)
+# ============================================
+SIMPLE_STRATEGY_CODE = '''
+"""
+简化版策略 - 针对510300.SSE的单票回测测试
+"""
+
+from vnpy.app.cta_strategy import CtaTemplate
+
+class SingleStockStopLossStrategy(CtaTemplate):
+    """
+    简化版单票策略 - 测试510300.SSE
+    """
+    
+    parameters = ["fast_window", "slow_window", "stop_loss_pct"]
+    variables = ["stop_loss_triggered"]
+    
+    def __init__(self, cta_engine, strategy_name, setting_dict):
+        super().__init__(cta_engine, strategy_name, setting_dict)
+        self.fast_window = getattr(self, 'fast_window', 5)
+        self.slow_window = getattr(self, 'slow_window', 20)
+        self.stop_loss_pct = getattr(self, 'stop_loss_pct', 0.15)
+        self.stop_loss_triggered = False
+    
+    def on_init(self):
+        self.write_log("策略初始化")
+        self.load_bar(100)
+    
+    def on_bar(self, bar):
+        # 检查止损
+        if self.pos > 0:
+            profit = (bar.close_price - self.avg_price) / self
+            if profit <= -self.stop_loss_pct:
+                self.write_log(f"触发止损: {bar.datetime}, 回撤: {profit:.2%}")
+                self.stop_loss_triggered = True
+                self.sell(bar.close_price, abs(self.pos))
+                return
+        
+        # 简单均线策略
+        if not self.stop_loss_triggered:
+            if bar.close_price > self.amo(bar.close_price, self.fast_window):
+                if self.pos == 0:
+                    self.buy(bar.close_price, 10000)
+            elif bar.close_price < self.amo(bar.close_price, self.slow_window):
+                if self.pos > 0:
+                    self.sell(bar.close_price, abs(self.pos))
+'''
+
+# ============================================
+# 3. 执行回测
+# ============================================
+
+# 导入必要模块
+import types
+import sys
+
+print("=" * 80)
+print("🚀 在Docker容器内直接运行回测")
+print("=" * 80)
+
+# 加载vnpy.app兼容性模块
+vnpy_app_module = types.ModuleType('vnpy.app')
+sys.modules['vnpy.app'] = vnpy_app_module
+
+submodules = ['cta_strategy', 'cta_backtester', 'data_manager']
+for name in submodules:
+    full_name = f'vnpy.app.{name}'
+    submodule = types.ModuleType(full_name)
+    sys.modules[full_name] = submodule
+    setattr(vnpy_app_module, name, submodule)
+
+from vnpy_ctastrategy import CtaTemplate, BarData
+sys.modules['vnpy.app.cta_strategy'].CtaTemplate = CtaTemplate
+
+from vnpy_ctabacktester import BacktesterEngine
+sys.modules['vnpy.app.cta_backtester'].BacktesterEngine = BacktesterEngine
+
+print("✅ vnpy.app兼容性模块加载完成")
+
+# 执行风控代码
+exec(RISK_CONTROL_CODE, globals())
+
+# 执行策略代码
+exec(SIMPLE_STRATEGY_CODE, globals())
+
+# 运行回测
+from vnpy.event import EventEngine
+from vnpy.trader.engine import MainEngine
+from vnpy.trader.constant import Exchange, Interval
+from datetime import datetime
+
+print("\n" + "=" * 80)
+print("初始化回测引擎...")
+print("=" * 80)
+
+event_engine = EventEngine()
+main_engine = MainEngine(event_engine)
+
+# 手动实例化BacktesterEngine
+backtester_engine = BacktesterEngine(main_engine, event_engine)
+backtester_engine.classes["SingleStockStopLossStrategy"] = SingleStockStopLossStrategy
+
+print("✅ BacktesterEngine 初始化完成")
+
+# 加载数据
+print("\n" + "=" * 80)
+print("加载数据...")
+print("=" * 80)
+
+from vnpy.trader.database import get_database
+db = get_database()
+
+symbol = "510300"
+exchange = Exchange.SSE
+interval = Interval.DAILY
+start = datetime(2021, 1, 1)
+end = datetime(2026, 3, 1)
+
+bars = db.load_bar_data(symbol, exchange, interval, start, end)
+print(f"✅ 加载了 {len(bars)} 条bar数据")
+
+if len(bars) == 0:
+[TRUNCATED]