知微 (MoFin)
aa0f740381
完整数据采集+分析管道： - market_watch.py：90行业板块采集（同花顺/东方财富） - 市场精选推荐 cron：全市场分析+候选池+星级推荐 - price_monitor.py：持仓/自选高频价格监控 - refresh_mtf_cache.py：多周期K线缓存 - 策略评估/知识萃取管道 文档：docs/ 含完整需求+架构设计 注意：尚未配置 git remote，笑笑接手后自行配置
252 lines
8.8 KiB
Python
252 lines
8.8 KiB
Python
#!/usr/bin/env python3
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"""strategy_feedback.py — 策略评估反馈引擎
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从评估结果自动推导策略调整建议：
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1. 阶段一完成（达到止盈）→ 标记成功，萃取经验
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2. 阶段一失败（跌破止损）→ 标记失败，分析原因
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3. 阶段二验证（新止损被跌破）→ 标记止损正确
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4. 长期未触及任何区间 → 建议重新评估策略区间
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5. 准确率趋势 → 调整策略参数（宽度、区间计算方法）
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输出：写入 decisions.json + 生成调整建议报告
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"""
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import json
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import sys
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from datetime import datetime, timedelta
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from pathlib import Path
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DATA_DIR = Path(__file__).parent / "data"
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DECISIONS_PATH = DATA_DIR / "decisions.json"
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PORTFOLIO_PATH = DATA_DIR / "portfolio.json"
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ACCURACY_PATH = DATA_DIR / "accuracy_stats.json"
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EVENTS_PATH = DATA_DIR / "price_events.json"
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FEEDBACK_PATH = DATA_DIR / "strategy_feedback.json"
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def load_json(path, default=None):
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try:
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with open(path, encoding="utf-8") as f:
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return json.load(f)
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except (FileNotFoundError, json.JSONDecodeError):
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return {} if default is None else default
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def save_json(path, data):
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Path(path).parent.mkdir(parents=True, exist_ok=True)
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with open(path, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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def check_phase_completion(decision, events):
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"""检查某条策略是否有阶段完成事件"""
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code = decision["code"]
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trig = decision.get("trigger", {})
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stock_events = [e for e in events.get("events", []) if e["code"] == code]
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el = trig.get("entry_zone", "")
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sl = trig.get("stop_loss", "")
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tp = trig.get("take_profit", "")
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el_low = el_high = None
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if el and "~" in str(el):
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try:
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parts = str(el).split("~")
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el_low, el_high = float(parts[0]), float(parts[1])
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except:
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pass
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sl_p = float(sl) if sl else None
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tp_p = float(tp) if tp else None
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result = {
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"phase1_completed": False,
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"phase1_result": None, # "success" or "failure"
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"phase1_completed_at": None,
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"phase1_price_at_completion": None,
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"phase2_completed": False,
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"phase2_result": None,
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"phase2_completed_at": None,
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"days_in_phase1": None,
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}
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# 检查价格事件中是否有止盈/止损触发
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for ev in stock_events:
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ev_type = ev.get("event_type", "")
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ev_price = ev.get("price", 0)
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ev_time = ev.get("timestamp", "")
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if ev_type == "stop_loss" and sl_p and ev_price <= sl_p:
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result["phase1_completed"] = True
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result["phase1_result"] = "failure"
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result["phase1_completed_at"] = ev_time
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result["phase1_price_at_completion"] = ev_price
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# 止盈：检查是否达到或超过止盈价
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if tp_p and ev_price >= tp_p:
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result["phase1_completed"] = True
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result["phase1_result"] = "success"
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result["phase1_completed_at"] = ev_time
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result["phase1_price_at_completion"] = ev_price
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return result
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def compute_accuracy_trend(accuracy_stats):
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"""计算准确率趋势，用于调整策略参数"""
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details = accuracy_stats.get("details", [])
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if not details:
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return {"trend": "stable", "phase1_accuracy": 0, "phase2_accuracy": 0}
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phase1 = accuracy_stats.get("phase1", {})
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phase2 = accuracy_stats.get("phase2", {})
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p1_acc = phase1.get("accuracy_pct", 0)
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p2_acc = phase2.get("accuracy_pct", 0)
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if p1_acc >= 80:
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trend = "improving"
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elif p1_acc <= 50 and phase1.get("correct", 0) + phase1.get("wrong", 0) >= 3:
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trend = "declining"
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else:
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trend = "stable"
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return {
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"trend": trend,
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"phase1_accuracy": p1_acc,
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"phase2_accuracy": p2_acc,
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"phase1_evaluated": phase1.get("correct", 0) + phase1.get("wrong", 0),
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"phase2_evaluated": phase2.get("correct", 0) + phase2.get("wrong", 0),
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}
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def generate_adjustment(decision, phase_check, accuracy_trend):
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"""根据评估结果生成策略调整建议"""
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code = decision["code"]
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name = decision.get("name", code)
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trig = decision.get("trigger", {})
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adjustments = []
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el = trig.get("entry_zone", "")
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sl = trig.get("stop_loss", "")
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tp = trig.get("take_profit", "")
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# 1. 阶段一完成 → 萃取经验
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if phase_check["phase1_completed"]:
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if phase_check["phase1_result"] == "success":
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adjustments.append({
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"type": "phase1_success",
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"message": f"{name}({code}) 阶段一成功：达到止盈{tp}，价格{phase_check['phase1_price_at_completion']}",
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"action": "mark_completed",
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"knowledge": f"策略区间{el}有效，价格达到止盈位{tp}",
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})
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elif phase_check["phase1_result"] == "failure":
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adjustments.append({
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"type": "phase1_failure",
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"message": f"{name}({code}) 阶段一失败：跌破止损{sl}，价格{phase_check['phase1_price_at_completion']}",
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"action": "reassess",
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"knowledge": f"策略区间{el}失效，止损{sl}被跌破，需重新评估",
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})
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# 2. 长期未触发 → 建议重新评估
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# 检查策略创建时间
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created_at = decision.get("timestamp", "")
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if created_at:
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try:
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created = datetime.fromisoformat(created_at)
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days_since = (datetime.now() - created).days
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if days_since >= 14 and not phase_check["phase1_completed"]:
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adjustments.append({
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"type": "stale_strategy",
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"message": f"{name}({code}) 策略已{days_since}天未触发任何区间，建议重新评估",
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"action": "reassess",
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})
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except:
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pass
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# 3. 准确率趋势 → 调整策略宽度
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if accuracy_trend["trend"] == "declining" and accuracy_trend["phase1_evaluated"] >= 3:
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adjustments.append({
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"type": "accuracy_declining",
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"message": f"准确率下降至{accuracy_trend['phase1_accuracy']}%，建议收紧策略区间宽度",
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"action": "tighten",
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})
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return adjustments
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def run():
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decisions = load_json(DECISIONS_PATH, {"decisions": []})
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events = load_json(EVENTS_PATH, {"events": []})
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accuracy_stats = load_json(ACCURACY_PATH, {})
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accuracy_trend = compute_accuracy_trend(accuracy_stats)
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all_feedback = []
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phase1_completed = []
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reassess_needed = []
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for d in decisions["decisions"]:
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code = d["code"]
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name = d.get("name", code)
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# 检查阶段完成情况
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phase_check = check_phase_completion(d, events)
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# 生成调整建议
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adjustments = generate_adjustment(d, phase_check, accuracy_trend)
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feedback_entry = {
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"code": code,
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"name": name,
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"evaluated_at": datetime.now().isoformat(),
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"phase_check": phase_check,
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"adjustments": adjustments,
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}
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all_feedback.append(feedback_entry)
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# 收集需要处理的策略
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if phase_check["phase1_completed"]:
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phase1_completed.append(feedback_entry)
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if any(a["action"] in ("reassess", "tighten") for a in adjustments):
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reassess_needed.append(feedback_entry)
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# 保存反馈结果
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feedback_data = {
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"updated_at": datetime.now().isoformat(),
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"accuracy_trend": accuracy_trend,
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"total_strategies": len(decisions["decisions"]),
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"phase1_completed_count": len(phase1_completed),
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"reassess_needed_count": len(reassess_needed),
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"feedback": all_feedback,
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}
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save_json(FEEDBACK_PATH, feedback_data)
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# 输出报告
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print("=" * 70)
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print(f"策略反馈引擎报告 | {datetime.now().strftime('%Y-%m-%d %H:%M')}")
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print("=" * 70)
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print(f"\n📈 准确率趋势: {accuracy_trend['trend']}")
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print(f" 阶段一准确率: {accuracy_trend['phase1_accuracy']}% ({accuracy_trend['phase1_evaluated']}次评估)")
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print(f" 阶段二准确率: {accuracy_trend['phase2_accuracy']}% ({accuracy_trend['phase2_evaluated']}次评估)")
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print(f"\n✅ 阶段一已完成: {len(phase1_completed)}只")
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for fb in phase1_completed:
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pc = fb["phase_check"]
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icon = "🟢" if pc["phase1_result"] == "success" else "🔴"
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print(f" {icon} {fb['name']}({fb['code']}) {pc['phase1_result']} 于{pc['phase1_completed_at'][:19]} 价格{pc['phase1_price_at_completion']}")
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print(f"\n🔄 需重新评估: {len(reassess_needed)}只")
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for fb in reassess_needed:
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for adj in fb["adjustments"]:
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print(f" {adj['type']}: {adj['message']}")
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if not phase1_completed and not reassess_needed:
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print(f"\n 无策略需要调整，所有策略正常运行中")
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print(f"\n✅ 反馈完成，已写入 {FEEDBACK_PATH}")
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if __name__ == "__main__":
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run()
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