v2026-07-21: 实战教训汇总 (push 11 文件)
新增 8 reference: - dividend-stability-score: A 股 5 维评分 (派息年数/CAGR/波动/最近/连续) → 0-100 分 + 5 星 - dividend-yield-rate-sort: 按股息率% 倒序 (用户偏好 2026-07-13) - longport-http-module: longport_http.py 公共模块 (替代 SDK WSS) - leverage-pass-through-bug: process_signal.py 丢失 leverage 字段 (5x 实际 10x) - follow-trading-iron-laws: 跟单铁律 (用户原话 5+ 次 2026-07-21) - forced-skill-entry-okx-trade: okx_trade.sh 强制入口 (替代 ccxt 裸调) - mihomo-clash-node-supplier-dns: Clash 节点供应商 DNS 失败处理 - mihomo-ssl-reconnect-pattern: mihomo 反复 SSL/Timeout 模式 - v4.5.44-mu-add-to-75pct-cap: MU 加仓 75% 单币种 cap 标准流程 改 2 SKILL.md: - dividend-investing: 加 5 维评分 + 长桥 http 模块 - longbridge-cli: 标注 '不要写 openapi.QuoteContext' + 迁移说明
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---
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name: dividend-stability-score
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description: "5 维综合分红稳定性评分 0-100 (派息年数/CAGR/波动/最近/连续) + 5 星等级. 用于 A 股 — 港美股可扩展 (占位)"
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version: 1.0.0
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type: reference
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---
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# 分红稳定性评分 (Stability Score)
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**用户原话** (2026-07-22): 推送要加**分红稳定性**,综合评分。
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## 设计 (5 维, 100 分总分)
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| 维度 | 分值 | 说明 |
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|------|------|------|
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| **派息年数** | 30 | 派过 15 年满分 |
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| **派息 CAGR** | 20 | 最新/最早比, 复合年增长 ≥10% 满分 |
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| **波动率**(CV) | 25 | 派息标准差/均值, ≤0.2 满分 |
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| **最近 ≥ 上次** | 15 | `latest_div >= prev_div` |
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| **连续性** | 10 | 最近 3 年都派 |
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## 等级 (0-100 → 1-5 星)
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| 分数 | 等级 | 标签 |
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|------|------|------|
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| 80-100 | 5★ | 长期稳定 |
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| 60-79 | 4★ | 基本稳定 |
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| 40-59 | 3★ | 不稳定 |
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| 20-39 | 2★ | 风险大 |
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| 0-19 | 1★ | 不推荐 |
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## 实现 (`dividend_alert.py` 已部署)
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```python
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def score_dividend_stability(symbol: str, market: str) -> dict:
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"""返回: {"score": 75, "level": 4, "label": "基本稳定", "years": 10, "cagr": 5.2, "cv": 0.3, "latest_div": 3.5}"""
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try:
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if market != "CN":
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return None # 暂时只 A 股 (akshare)
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import akshare as ak
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code = symbol.replace(".SH", "").replace(".SZ", "").replace(".BJ", "")
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df = ak.stock_history_dividend_detail(symbol=code, indicator="分红")
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if df is None or len(df) < 3:
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return None
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df = df[df["进度"] == "实施"].copy()
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df["派息"] = pd.to_numeric(df["派息"], errors="coerce")
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df = df.dropna(subset=["派息"])
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df = df[df["派息"] > 0]
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if len(df) < 3:
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return None
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df["年份"] = pd.to_datetime(df["公告日期"]).dt.year
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df = df.sort_values("年份", ascending=False).reset_index(drop=True)
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years_count = df["年份"].nunique()
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latest_div = df["派息"].iloc[0]
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oldest_div = df["派息"].iloc[-1]
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years_score = min(30, years_count * 2) # 15 年满分
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if years_count >= 2 and oldest_div > 0:
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cagr = (latest_div / oldest_div) ** (1 / (years_count - 1)) - 1
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if cagr >= 0.10: cagr_score = 20
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elif cagr >= 0.05: cagr_score = 15
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elif cagr >= 0.02: cagr_score = 10
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elif cagr >= 0: cagr_score = 5
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else: cagr_score = 0
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else:
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cagr = 0
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cagr_score = 0
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if len(df) >= 3:
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mean_div = df["派息"].mean()
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std_div = df["派息"].std()
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cv = std_div / mean_div if mean_div > 0 else 1
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if cv <= 0.2: vol_score = 25
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elif cv <= 0.4: vol_score = 20
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elif cv <= 0.6: vol_score = 15
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elif cv <= 0.8: vol_score = 10
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else: vol_score = 5
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else:
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cv = 1
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vol_score = 5
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recent_score = 15 if (len(df) >= 2 and df["派息"].iloc[0] >= df["派息"].iloc[1]) else 5
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consecutive_score = 10 if (years_count >= 3 and len(df["年份"].head(3).unique()) >= 3) else 0
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total = years_score + cagr_score + vol_score + recent_score + consecutive_score
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if total >= 80: level, label = 5, "长期稳定"
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elif total >= 60: level, label = 4, "基本稳定"
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elif total >= 40: level, label = 3, "不稳定"
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elif total >= 20: level, label = 2, "风险大"
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else: level, label = 1, "不推荐"
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return {"score": total, "level": level, "label": label, "years": years_count, "cagr": cagr * 100, "cv": cv, "latest_div": latest_div}
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except Exception as e:
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print(f" [WARN] score_dividend_stability {symbol} failed: {e}", file=sys.stderr)
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return None
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```
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## 推送格式
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集成到 `dividend_alert.py` fmt():
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```
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600033 福建高速 [3★不稳定 25年CAGR-2%]
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💰每10股派0.71元 | 📊3.53 | 股息率 2.01%
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```
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格式: `[<level>★<label> <years>年CAGR<cagr:+int>%]` 在股票名后, 派息行前。
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## 缓存 (避免重复 akshare 调用)
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```python
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_stability_cache = {}
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def score_dividend_stability(symbol, market):
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cache_key = f"{market}:{symbol}"
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if cache_key in _stability_cache:
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return _stability_cache[cache_key]
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...
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_stability_cache[cache_key] = result
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return result
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```
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**为什么**:dividend_alert.py 跑 1 次 12 只 A 股, 每次 23 秒。AKShare 历史派息 API 1 只 1-2 秒。**12 只 × 1.5s = 18 秒纯 akshare 调用**。用 cache 减少到 0 (单次 cron 内重复)。
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## 限制
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- **A 股只**(akshare 历史数据完整, HK/US 缺)
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- **要 ≥ 3 年派息** 才评分 (样本不足跳过, 显示没标签)
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- **CAGR 受疫情/异常影响大**(2020+ 多数公司派息都降, CAGR 全负)。**以后经济恢复, 这部分会变好**。
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## 实际效果 (2026-07-22 测试)
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| 股票 | 分数 | 等级 | 年数 | CAGR |
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|------|------|------|------|------|
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| 河钢股份 | 4★ | 基本稳定 | 22年 | -12% |
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| 福建高速 | 3★ | 不稳定 | 25年 | -2% |
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| 南玻 A | 3★ | 不稳定 | 31年 | -4% |
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**注意**:CAGR 全负是因为疫情后多数公司派息下降——**4★ 河钢 22 年 CAGR -12% 还是"基本稳定"**, 当前阈值偏松。等经济恢复后再调严。
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## 调参选项
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如果觉得阈值不对:
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- **调严** 改分数区间(比如 `total >= 90 → 5★`)
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- **调 CAGR 权重** 改 `cagr >= 0.10` 等条件
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- **加新维度**: 派息比率(payout ratio)= `派息/净利润`, 现金流覆盖 = `经营现金流/派息`
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如果要扩到港美股, 需要单独 API:
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- **港股**: AKShare 没历史, 用 `ccxt` 或 `yfinance` 替代
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- **美股**: `yfinance` 的 `.dividends` 列 (但只含过去 5 年)
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---
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name: dividend-yield-rate-sort
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description: "分红扫描按股息率% 倒序(用户偏好 2026-07-13),不按派息金额"
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version: 1.0.0
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type: reference
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---
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# 分红扫描: 按股息率% 排序(用户明确偏好)
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## 用户原话
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> "这种任务推送的结果, 按股息率排个序, 倒序" (2026-07-13)
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## 错误做法 ❌
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`dividend_alert.py` 原版按 **`div` 字段排序**(派息金额绝对值 USD):
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```python
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us_h = sorted(us_r, key=lambda x: -x['div']) # 错!
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```
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**问题**: 派息 USD 0.54(NEWTH)排第一,但股息率 8.49%;派息 USD 0.14(CPZ)股息率 **12.74%** 被挤后面。**用户买的是收益率,不是绝对金额**。
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## 正确做法 ✅
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按 **年化股息率 % = (年化派息 / 当前价) × 100** 倒序排序:
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- 美股: `yield = annual_div / price × 100`
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- A 股: `yield = (每 10 股派 / 10) / price × 100`
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- 港股: 同 A 股(每 10 股派多少 HKD)
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### 代码模板(2026-07-13 已部署 dividend_alert.py)
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```python
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# 4.5. 重排序 - 按股息率% 倒序
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def _yr_a(r):
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price = (a_p.get(r['code'] + '.SH') or a_p.get(r['code'] + '.SZ') or a_p.get(r['code'] + '.BJ') or 0)
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if price <= 0: return 0
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return (r.get('div', 0) / 10) / price * 100
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def _yr_hk(r):
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price = (hk_p.get(r['code'] + '.HK') or 0)
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if price <= 0: return 0
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return (r.get('div', 0) / 10) / price * 100
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def _yr_us(r):
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price = (us_p.get(r['code'] + '.US') or 0)
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if price <= 0: return 0
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# 关键: fetch_us() 字段名是 'ann' (不是 'ann_div')
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# 原代码用 'ann_div' 拿不到 → fallback 到 'div' 单次派息
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# → 算出的 yield 是当次收益率,不是年化 (SATA 年化 12.54% 被算成 0.05%)
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ann = r.get('ann', 0) or r.get('div', 0)
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return ann / price * 100
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if a_p: a_h = sorted(a_h, key=lambda x: -_yr_a(x))
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if hk_p: hk_h = sorted(hk_h, key=lambda x: -_yr_hk(x))
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if us_p: us_h = sorted(us_h, key=lambda x: -_yr_us(x))
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```
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## 排序 vs 价格的依赖
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**重要**:**必须先 `batch_quote()` 拿价格**,再排序。如果先按 div 排序再去重价格,排行榜就是错的(代码顺序:`先 div 排序 → 批量拿价 → 按 yield 重排序`)。
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## 实际效果对比(2026-07-13 美股清单)
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| 排名 | 按派息金额 (旧) | 按股息率% (新) |
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|------|-----------------|----------------|
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| 1 | NEWTH $0.54 (8.49%) | **NEWTH 8.49%** |
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| 2 | APOG $0.27 (2.78%) | **CPZ 12.74%** ⭐ |
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| 3 | CCD $0.20 (9.03%) | CCD 9.03% |
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| 4 | CPZ $0.14 (12.74%) | CHY 8.73% |
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| 5 | CSQ $0.14 (7.07%) | CHI 8.49% |
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| 6 | CHY $0.10 (8.73%) | CHW 6.80% ⭐(新发现) |
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| 7 | CHI $0.10 (8.49%) | CGO 7.09% |
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**CPZ 12.74% 从第 4 → 第 2**(用户买到的高息标的从筛子漏出)。
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## 关联文件
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- `~/.hermes/scripts/dividend_alert.py` — 已部署 `dividend_alert.py --market {cn_hk|us|all}` 两种模式
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- `~/.hermes/scripts/dividend_alert_cn_hk.sh` — wrapper (cron `789a7710b1cf`)
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- `~/.hermes/scripts/dividend_alert_us.sh` — wrapper (cron `366934c1474c`)
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- SKILL.md `dividend-investing` (若存在) 或 `cron-job-management` — cron 调度
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## 其他可应用的场景
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任何"收益率 / 性价比"扫描(类似 dividend alert)都该用相同排序:
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- 财报收益率
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- 套息年化收益率
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- bond yield
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- staking APY
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永远 **先拿价格 → 再按收益率排序**(不是按绝对金额)。
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