initial-import: 2026-04-11 21:18:55
This commit is contained in:
cfdaily
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#!/usr/bin/env python3
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"""
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通过RPC执行回测 - 完整版
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"""
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import zmq
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import json
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# 策略代码
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STRATEGY_CODE = '''
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"""
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单票固定比例止损策略 - vnpy CTA回测
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"""
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from vnpy_ctastrategy import (
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CtaTemplate, StopOrder, TickData, BarData, TradeData, OrderData, BarGenerator, ArrayManager
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)
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from vnpy.trader.constant import Direction, Offset
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class SingleStockStopLossStrategy(CtaTemplate):
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"""单票固定比例止损策略"""
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author = "关羽 (云长)"
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parameters = ["fast_window", "slow_window", "stop_loss_pct"]
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variables = ["fast_ma", "slow_ma", "cost_price", "in_position"]
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def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
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super().__init__(cta_engine, strategy_name, vt_symbol, setting)
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self.bg = BarGenerator(self.on_bar)
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self.am = ArrayManager(max(30, 100))
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self.fast_ma = 0.0
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self.slow_ma = 0.0
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self.cost_price = 0.0
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self.in_position = False
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def on_init(self):
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self.write_log(f"策略初始化，fast={self.fast_window}, slow={self.slow_window}, stop_loss={self.stop_loss_pct:.1%}")
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self.put_event()
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def on_bar(self, bar):
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self.am.update_bar(bar)
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if not self.am.inited:
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return
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self.fast_ma = self.am.sma(self.fast_window)
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self.slow_ma = self.am.sma(self.slow_window)
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have_signal = True
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if self.in_position and self.cost_price > 0:
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current_drawdown = (bar.close_price - self.cost_price) / self.cost_price
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if current_drawdown <= -self.stop_loss_pct:
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if self.pos > 0:
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self.sell(bar.close_price, self.pos)
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self.in_position = False
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self.write_log(f"触发止损：成本{self.cost_price:.2f}，当前{bar.close_price:.2f}，回撤{current_drawdown:.1%}")
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have_signal = False
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if have_signal:
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if not self.in_position:
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if self.fast_ma > self.slow_ma:
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self.buy(bar.close_price, 10000)
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self.cost_price = bar.close_price
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self.in_position = True
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self.write_log(f"金叉开多：价格{bar.close_price:.2f}")
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else:
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if self.fast_ma < self.slow_ma:
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if self.pos > 0:
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self.sell(bar.close_price, self.pos)
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self.in_position = False
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self.write_log(f"死叉平仓：价格{bar.close_price:.2f}")
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self.put_event()
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'''
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print("=" * 80)
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print("🚀 通过RPC执行回测")
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print("=" * 80)
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print(f"✅ 策略代码: {len(STRATEGY_CODE)} 字符")
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# RPC请求
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request = {
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"strategy_code": STRATEGY_CODE,
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"symbol": "510300.S.SSE",
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"interval": "1d",
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"start": 1609459200,
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"end": 1772515200,
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"capital": 1000000,
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"rate": 3e-5,
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"slippage": 0.002,
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"size": 10000,
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"pricetick": 0.001,
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"data_source": "sqlite"
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}
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print("\n请求配置:")
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print(f" 标的: 510300.SSE")
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print(f" 时间: 2021-01-01 ~ 2026-03-01")
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print(f" 资金: 1,000,000")
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print(f" 止损: 15%")
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# 连接RPC
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print(f"\n连接RPC: 127.0.0.1:8008")
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context = zmq.Context()
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socket = context.socket(zmq.REQ)
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socket.setsockopt(zmq.LINGER, 0)
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socket.connect("tcp://127.0.0.1:8008")
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socket.setsockopt(zmq.RCVTIMEO, 30000)
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socket.setsockopt(zmq.SNDTIMEO, 30000)
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# 发送请求
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print("\n发送请求...")
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request_json = json.dumps(request)
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socket.send_string(request_json)
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print("✅ 请求已发送，等待响应...")
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# 接收响应
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try:
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response_json = socket.recv_string()
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response = json.loads(response_json)
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print("✅ 收到响应")
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if "error" in response:
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print(f"\n❌ 回测失败: {response['error']}")
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if "traceback" in response:
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print("\n错误堆栈:")
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print(response["traceback"])
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else:
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print("\n" + "=" * 80)
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print("回测结果:")
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print("=" * 80)
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if "statistics" in response:
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stats = response["statistics"]
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print(f"\n📊 绩效指标:")
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print(f" 总收益率: {stats.get('total_return', 0):.2%}")
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print(f" 年化收益率: {stats.get('annual_return', 0):.2%}")
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print(f" 最大回撤: {stats.get('max_drawdown', 0):.2%}")
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print(f" 夏普比率: {stats.get('sharpe_ratio', 0):.2f}")
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print(f" 卡玛比率: {stats.get('calmar_ratio', 0):.2f}")
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print(f" 总交易次数: {stats.get('total_trades', 0)}")
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print(f" 胜率: {stats.get('win_rate', 0):.2%}")
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print(f" 盈亏比: {stats.get('profit_loss_ratio', 0):.2f}")
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if "trades" in response:
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trades = response["trades"]
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print(f"\n📝 交易记录: 共 {len(trades)} 笔")
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for idx, trade in enumerate(trades[:20], 1):
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print(f" {idx}. {trade.get('datetime')} {trade.get('direction')} {trade.get('symbol')} @ {trade.get('price'):.2f} × {trade.get('volume')}")
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if len(trades) > 20:
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print(f" ... 还有 {len(trades) - 20} 笔")
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print("\n" + "=" * 80)
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print("✅ 回测执行完成!")
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print("=" * 80)
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except zmq.error.Again:
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print("❌ 请求超时: RPC服务响应时间过长")
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except Exception as e:
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print(f"❌ 接收响应失败: {e}")
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import traceback
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traceback.print_exc()
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finally:
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socket.close()
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context.term()
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