--- name: dividend-investing description: "Dividend stock research, analysis, and ex-dividend alerting across A/HK/US markets. Covers: dividend history analysis (yield, growth, payout ratio), pre-ex-dividend day alerts via cron job, yield-vs-financing-cost arbitrage calculations, and record date tracking. Not for short-term trading entries — this is the dividend-side analysis mindset." version: 1.0.0 author: Hermes Agent license: MIT platforms: [linux, macos] metadata: hermes: tags: [trading, dividends, stocks, a-shares, hk-stocks, us-stocks, cron] related_skills: [tonghuashun, longbridge-python-sdk, stock-analysis] scripts: - dividend_alert.py: "python3 ~/.hermes/scripts/dividend_alert.py — daily cron job; runs via cronjob no_agent=true (script output delivered verbatim)" requires: - python3 + akshare (pip install akshare) - python3 + requests (stdlib) - For US stocks: internet access to api.nasdaq.com (no API key needed) - Cron job management (cronjob tool) --- # 股息投资 Skill — Dividend Investing Dividend-focused stock analysis and pre-ex-dividend alerting. **Mindset is fundamentally different from trading:** focus on yield stability, growth trajectory, payout ratio, cash coverage, and tax implications — not technical entry points. ## Data Sources | Market | Data Source | API Key? | Speed | |--------|-------------|----------|-------| | 🇨🇳 A股 | `akshare.news_trade_notify_dividend_baidu(date)` | Free | ~3s | | 🇭🇰 港股 | Same Baidu function (HK stocks included) | Free | ~3s | | 🇺🇸 美股 | `https://api.nasdaq.com/api/calendar/dividends?date=YYYY-MM-DD` | Free | ~2s | ## Cross-Market Alerting Cron Job The script `~/.hermes/scripts/dividend_alert.py` runs daily and outputs a formatted dividend alert. Key design decisions: ### Core Logic ```python # 1. Find next trading day (skip weekends) def next_trading_day(d): while d.weekday() >= 5: d += timedelta(days=1) return d # 2. A/HK: AKShare Baidu dividend calendar df = ak.news_trade_notify_dividend_baidu(date=target_date_str) # Returns: 股票代码, 除权日, 分红, 送股, 转增, 交易所, 股票简称, 报告期 # 3. US: Nasdaq API url = f'https://api.nasdaq.com/api/calendar/dividends?date={date_str}' # Returns: symbol, dividend_Rate (per-share), indicated_Annual_Dividend, record_Date, dividend_Ex_Date ``` ### Format Parsing A-share dividend from Baidu is in **元/10股** format (e.g., "38.00元" = 3.80元/股). HK dividend from Baidu is in **港元/10股** format (e.g., "0.62港元"). US dividend from Nasdaq is in **美元/股** format (e.g., 0.56). ### Cron Setup ```bash # Create the job (EDT server time, 20:30 = Beijing 08:30 next day) # Use no_agent=true for reliable script-only delivery cronjob action=create \ name='股息登记日前一天提醒' \ schedule='30 20 * * 1-5' \ script='dividend_alert.py' \ no_agent=true ``` The `no_agent=true` mode delivers the script's stdout verbatim — no LLM token waste, no risk of the agent reformatting or truncating the message. ### Proxy Pitfall AKShare AND the Nasdaq API BOTH break when system proxy env vars are set: ```python import os for k in ['http_proxy','https_proxy','HTTP_PROXY','HTTPS_PROXY']: os.environ.pop(k, None) # Now import akshare and requests — they'll connect directly ``` Always put this at the top of your dividend scripts. The proxy env vars are typically set by Hermes gateway or system-level VPN wrappers, and they prevent direct HTTPS connections to Chinese financial data API endpoints (ProxyError). ## Dividend Investor Mindset (vs Trader) When the user says they want dividends (not trading), shift analysis completely: | Dimension | Trader | Dividend Investor | |-----------|--------|-------------------| | **Focus** | Entry/exit price, momentum, MACD | Yield %, payout ratio, dividend growth CAGR | | **Key metric** | Buy point, stop loss, R:R | 股息率 vs 资金成本(如银行分期3%) | | **Timescale** | Days to weeks | Quarters to years | | **Data** | K-line, volume, ADR, MACD | Dividend history, cash flow, FCF, payout ratio | | **When to buy** | Technical breakout / support | Before ex-div date (登记日前一天 = last buy day) | | **Tax** | Short-term capital gains | Holding period tax rules (A股: 1月内20%, 1年以上免税) | ### Analysis Template ``` 股息率 = 全年每股分红 / 当前股价 净息差 = 股息率 - 融资成本 分红增长率(5年CAGR) = (当年分红 / 5年前分红)^(1/5) - 1 分红覆盖率 = 经营现金流 / 分红总额 ``` ## Dividend Capture Analysis (Buy Before Ex-div, Sell After) When the user asks about "收息后卖" (dividend capture), the math is NOT free money: ### The Core Equation ``` Net P&L = Dividend_Net - (Buy_Price - Sell_Price) × Shares = Dividend × (1 - Tax_Rate) × Shares - Price_Drop × Shares ``` ### Why Dividend Capture Fails for Retail | Scenario | Tax | Price Action | Net Result | |----------|-----|-------------|------------| | Sell at exact ex-div price | 20% (<1mo) | -div amount | **LOSE** (tax eaten) | | Sell at exact ex-div price | 10% (1mo-1yr) | -div amount | **LOSE** (tax eaten) | | Sell at exact ex-div price | 0% (>1yr) | -div amount | **BREAKEVEN** | | Stock recovers +2% (填权) | 20% | -div +2% | **SLIGHT GAIN** | | Stock fully fills gap | Any | -div +div | **GAIN = Dividend net** | **Rule of thumb:** The stock MUST recover (填权) by at least the tax rate × dividend/price to break even. For A-shares with 20% tax, that's ~0.4% on a 2元 dividend on a 28元 stock. ### 填权 (Gap Fill) Timeline Analysis Historical data for 华特达因 (000915): ``` 2025年: 除权日6/11收29.49 → 第10天31.15(+5.6%) → 第15天33.22(+12.6%) ✅ 填权 2024年: 除权日5/16收33.48 → 第2天33.95(+1.4%) → 60天跌到26.89(-19.7%) ❌ 未填权(大盘差) ``` **填权 probability depends primarily on:** 1. **Stock's position in its range** — near 52-week low = higher fill probability (safety margin) 2. **Broader market direction** — bull market = fast fill, bear market = may never fill 3. **Stock quality** — strong fundamentals (growing dividends, cash-rich) = faster fill ### Dividend Capture Decision Matrix ``` Q: "Can I buy today for the dividend and sell right after?" → Show the math above. The answer is almost always NO unless the user can wait for 填权. Q: "How long does it usually take to fill the gap?" → Check historical 填权 data. For quality dividend stocks at low prices, typically 2-4 weeks. ``` ## Push Notification Formatting For dividend alerts delivered to QQ/Telegram, use this card-style layout: ``` 📢 明日除权·红利提醒 ━━━━━━━━━━━━━━━━━━━━ 📅 今日 {date} 推送 ⏰ 明天 {next_date} ({weekday}) 除权除息 💡 明天是登记日,今天买入仍享分红 ──────────────────── 🇨🇳 A股 明日除权 TOP ⭐{code} {name} 💰每10股派{d:.2f}元 💎{code} {name} 💰每10股派{d:.2f}元 ──────────────────── 🇭🇰 港股 明日除权 TOP {code} {name} 💰每10股派{d:.2f}港元 ──────────────────── 🇺🇸 美股 明日除权 TOP {code} 💰${d:.2f}/股 | 年化${ann:.2f} | 年付{n}次 📅登记日{rec_date} ━━━━━━━━━━━━━━━━━━━━ 📌 操作提示 • 今天买入 → 明天登记 → 拿分红 • A股持仓1年以上免税,1月内20%税 ━━━━━━━━━━━━━━━━━━━━ 🤖 Hermes 每日红利雷达 ``` Visual hierarchy rules: - ⭐ for very high dividend (≥10元/10股) - 💎 for good dividend (5-10元/10股) - No prefix for lower dividends - `━` for header/footer separators, `─` for section dividers - 2-space indent per card, newline between cards - Empty market sections are simply omitted (no "0 results" noise) ## Dividend Calendar Key Dates **A股**: - 股权登记日 (Record date) = T day — buy on this day, still get dividend - 除权除息日 (Ex-div date) = T+1 trading day - **登记日前一天通知** → 用户登记日当天买入仍可拿分红 **港股**: - Generally same system as A-shares **美股**: - 除权日 (Ex-div date) = cut-off. Buy on or after ex-div → no dividend - 登记日 (Record date) = often same day as ex-div - Notification should say "明天除权,今天是最后买入日" ## Current Price Fetching in dividend_alert.py The `dividend_alert.py` script enriches each alert card with real-time prices via **LongPort SDK**. Unlike the old approach (AKShare for A, Sina for HK, LongPort for US), the current unified approach uses LongPort for ALL three markets in a single batch: | Market | Symbol Mapping | LongPort Format | |--------|---------------|-----------------| | 🇨🇳 A股 | 603733 → 603733.SH, 000858 → 000858.SZ | `.SH`, `.SZ`, `.BJ` | | 🇭🇰 港股 | 01088 → 01088.HK, 5 → 00005.HK | `.HK` (5-digit padded) | | 🇺🇸 美股 | AAPL → AAPL.US | `.US` suffix | **Batch all symbols in one LongPort call:** ```python # One ctx.quote() call for all three markets all_syms = a_syms + hk_syms + us_syms for i in range(0, len(all_syms), 15): for q in ctx.quote(all_syms[i:i+15]): prices[q.symbol] = float(q.last_done) ``` **⚠️ LongPort connection can be intermittent** — the SDK prints a permission table on first init and may timeout on high-load days. If LongPort fails, prices show as N/A but dividend data still outputs. The script retries on each run (cron runs daily), so a single failure self-recovers. **Dividend yield formula:** Yield = (dividend_per_10shares / 10) / current_price * 100. The Baidu API returns dividend in 元/10股 format, so divide by 10 before calculating yield. ## Script Reference See `scripts/dividend_alert.py` for the production alerting script. See `references/dividend-yield-arbitrage.md` for yield vs financing cost analysis. See `references/fill-gap-timing.md` for historical 填权 timing data and dividend capture analysis. ## Pitfalls 1. **Proxy environment variables** — always `unset` proxy vars before calling AKShare or Nasdaq API 2. **Baidu dividend data is per-10-shares** for A/HK. Don't multiply by 10 again when displaying. 3. **Nasdaq API rate limits** — fine for 1 query/day in a cron job, but don't query multiple times rapidly 4. **Weekend/holiday handling** — `next_trading_day()` only skips Sat/Sun. For CN/HK holidays, you'd need a full trading calendar. 5. **No backward-looking price fetching for yield** — current market price is available from `stock_zh_a_hist()` (1-2s per stock), but fetching for all alert stocks is slow (~15s for 8-10 stocks). Tradeoff: speed vs completeness. 6. **Timezone confusion** — Server is usually EDT (UTC-4). Beijing is UTC+8. Cron schedule must account for this: 20:30 EDT = 08:30 BJT next day. 7. **`stock_zh_a_spot_em()` downloads the full A-share market (~5000 stocks)** — Takes ~3-5s for a single call. This is **fine** for one-shot batch price lookups (as done in `dividend_alert.py`) but avoid calling it repeatedly in loops. For single-stock lookups, prefer `stock_zh_a_hist(code, period='daily', start_date=today, end_date=today, adjust='qfq')` instead (1-2s each). 9. **AKShare Baidu dividend API is intermittent** — `ak.news_trade_notify_dividend_baidu()` may return 0 results on some runs despite having data on others. This is a server-side issue, not rate limiting. **Mitigation**: Added `time.sleep(0.5)` before the call to avoid cache issues. The cron job reruns daily, so a single failure self-recovers. 10. **Yield formula: divide-by-10 trap** — The Baidu API returns dividend in **元/10股** format. When calculating dividend yield in percent, use `(dividend_per_10shares / 10) / current_price * 100`. A common bug is forgetting to divide by 10 (the "per 10 shares" unit). Verified correct formula: `d/10/p*100` where `d` is the Baidu dividend value and `p` is the stock price. 11. **Variable name collisions in patch replacements** — When patching Python code that uses short variable names (`p`, `d`, `c`, `n`), find-and-replace patterns can accidentally match unrelated code. Always use 3+ lines of surrounding context for unique matching.