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kanchi-dividend-sop

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Kanchi Dividend Sop

Kanchi股息投资SOP

Overview

概述

Implement Kanchi's 5-step method as a deterministic workflow for US dividend investing. Prioritize safety and repeatability over aggressive yield chasing.
将Kanchi的5步方法落地为美股股息投资的确定性工作流。优先保障安全性与可重复性，而非追求激进收益。

When to Use

适用场景

Use this skill when the user needs:
  • Kanchi-style dividend stock selection adapted for US equities.
  • A repeatable screening and pullback-entry process instead of ad-hoc picks.
  • One-page underwriting memos with explicit invalidation conditions.
  • A handoff package for monitoring and tax/account-location workflows.
当用户有以下需求时使用本技能：
  • 适配美股市场的Kanchi式股息选股。
  • 可重复的筛选与回调入场流程，而非随机选股。
  • 带有明确失效条件的单页尽职调查备忘录。
  • 用于监控及税务/账户配置规划的交接包。

Prerequisites

前置条件

Prepare one of the following inputs before running the workflow:
  1. Output from 
    skills/value-dividend-screener/scripts/screen_dividend_stocks.py
    .
  2. Output from 
    skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py
    .
  3. User-provided ticker list (broker export or manual list).
For deterministic artifact generation, provide tickers to:
bash
python3 skills/kanchi-dividend-sop/scripts/build_sop_plan.py \
  --tickers "JNJ,PG,KO" \
  --output-dir reports/
For Step 5 entry timing artifacts:
bash
python3 skills/kanchi-dividend-sop/scripts/build_entry_signals.py \
  --tickers "JNJ,PG,KO" \
  --alpha-pp 0.5 \
  --output-dir reports/
运行工作流前请准备以下输入之一：
  1. skills/value-dividend-screener/scripts/screen_dividend_stocks.py
    的输出结果。
  2. skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py
    的输出结果。
  3. 用户提供的股票代码列表（券商导出或手动整理）。
若要生成确定性成果，请将股票代码传入以下命令：
bash
python3 skills/kanchi-dividend-sop/scripts/build_sop_plan.py \
  --tickers "JNJ,PG,KO" \
  --output-dir reports/
若要生成第5步入场时机相关成果：
bash
python3 skills/kanchi-dividend-sop/scripts/build_entry_signals.py \
  --tickers "JNJ,PG,KO" \
  --alpha-pp 0.5 \
  --output-dir reports/

Workflow

工作流

1) Define mandate before screening

1) 筛选前明确投资要求

Collect and lock the parameters first:
  • Objective: current cash income vs dividend growth.
  • Max positions and position-size cap.
  • Allowed instruments: stock only, or include REIT/BDC/ETF.
  • Preferred account type context: taxable vs IRA-like accounts.
Load 
skills/kanchi-dividend-sop/references/default-thresholds.md
and apply baseline settings unless the user overrides.
先收集并锁定以下参数：
  • 目标：当前现金收益 vs 股息增长。
  • 最大持仓数量及单仓上限。
  • 允许的工具：仅股票，或包含REIT/BDC/ETF。
  • 偏好的账户类型：应税账户 vs IRA类账户。
加载
skills/kanchi-dividend-sop/references/default-thresholds.md
，除非用户自定义，否则使用基线设置。

2) Build the investable universe

2) 构建可投资标的池

Start with a quality-biased universe:
  • Core bucket: long dividend growth names (for example, Dividend Aristocrats style quality set).
  • Satellite bucket: higher-yield sectors (utilities, telecom, REITs) in a separate risk bucket.
Use explicit source priority for ticker collection:
  1. skills/value-dividend-screener/scripts/screen_dividend_stocks.py
    output (FMP/FINVIZ).
  2. skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py
    output.
  3. User-provided broker export or manual ticker list when APIs are unavailable.
Return a ticker list grouped by bucket before moving forward.
从质量导向的标的池开始：
  • 核心池：长期股息增长标的（例如股息贵族风格的优质标的组）。
  • 卫星池：高收益板块（公用事业、电信、REITs），单独划分风险池。
按以下优先级收集股票代码：
  1. skills/value-dividend-screener/scripts/screen_dividend_stocks.py
    的输出结果（来自FMP/FINVIZ）。
  2. skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py
    的输出结果。
  3. 当API不可用时，使用用户提供的券商导出或手动整理的股票代码列表。
按池分组返回股票代码列表后再进入下一步。

3) Apply Kanchi Step 1 (yield filter with trap flag)

3) 应用Kanchi第1步（带陷阱标记的收益率筛选）

Primary rule:
  • forward_dividend_yield >= 3.5%
Trap controls:
  • Flag extreme yield (
    >= 8%
    ) as 
    deep-dive-required
    .
  • Flag sudden jump in payout as potential special dividend artifact.
Output:
  • PASS
    or 
    FAIL
    per ticker.
  • deep-dive-required
    flag for potential yield traps.
核心规则：
  • forward_dividend_yield >= 3.5%
陷阱控制：
  • 将极端收益率（
    >= 8%
    ）标记为
    deep-dive-required
    （需深度分析）。
  • 将派息额突增的标的标记为潜在特殊股息影响。
输出：
  • 每个标的的
    PASS
    （通过）或
    FAIL
    （失败）结果。
  • 对潜在收益率陷阱标的标记
    deep-dive-required
    。

4) Apply Kanchi Step 2 (growth and safety)

4) 应用Kanchi第2步（增长与安全性检查）

Require:
  • Revenue and EPS trend positive on multi-year horizon.
  • Dividend trend non-declining over the review period.
Add safety checks:
  • Payout ratio and FCF payout ratio in reasonable range.
  • Debt burden and interest coverage not deteriorating.
When trend is mixed but not broken, classify as 
HOLD-FOR-REVIEW
instead of hard reject.
要求：
  • 多年度营收及EPS趋势为正。
  • 回顾期内股息趋势未下降。
额外安全检查：
  • 派息率及FCF派息率处于合理区间。
  • 债务负担及利息覆盖率未恶化。
当趋势混杂但未破裂时，归类为
HOLD-FOR-REVIEW
（待复查）而非直接拒绝。

5) Apply Kanchi Step 3 (valuation) with US sector mapping

5) 应用Kanchi第3步（结合美股板块映射的估值）

Use 
skills/kanchi-dividend-sop/references/valuation-and-one-off-checks.md
and apply sector-specific valuation logic:
  • Financials: 
    PER x PBR
    can remain primary.
  • REITs: use 
    P/FFO
    or 
    P/AFFO
    instead of plain 
    P/E
    .
  • Asset-light sectors: combine forward 
    P/E
    , 
    P/FCF
    , and historical range.
Always report which valuation method was used for each ticker.
使用
skills/kanchi-dividend-sop/references/valuation-and-one-off-checks.md
，应用板块专属估值逻辑：
  • 金融板块：
    PER x PBR
    可作为主要估值方法。
  • REITs：使用
    P/FFO
    或
    P/AFFO
    替代普通
    P/E
    。
  • 轻资产板块：结合远期
    P/E
    、
    P/FCF
    及历史区间。
需始终报告每个标的所使用的估值方法。

6) Apply Kanchi Step 4 (one-off event filter)

6) 应用Kanchi第4步（一次性事件筛选）

Reject or downgrade names where recent profits rely on one-time effects:
  • Asset sale gains, litigation settlement, tax effect spikes.
  • Margin spike unsupported by sales trend.
  • Repeated "one-time/non-recurring" adjustments.
Record one-line evidence for each 
FAIL
to keep auditability.
拒绝或下调近期利润依赖一次性因素的标的：
  • 资产出售收益、诉讼和解、税收效应激增。
  • 无营收趋势支撑的利润率飙升。
  • 反复出现的“一次性/非经常性”调整。
为每个
FAIL
标的记录一行证据，保持可审计性。

7) Apply Kanchi Step 5 (buy on weakness with rules)

7) 应用Kanchi第5步（逢低买入规则）

Set entry triggers mechanically:
  • Yield trigger: current yield above 5y average yield + alpha (default 
    +0.5pp
    ).
  • Valuation trigger: target multiple reached (
    P/E
    , 
    P/FFO
    , or 
    P/FCF
    ).
Execution pattern:
  • Split orders: 
    40% -> 30% -> 30%
    .
  • Require one-sentence sanity check before each add: "thesis intact vs structural break".
机械设置入场触发条件：
  • 收益率触发：当前收益率高于5年平均收益率+alpha（默认
    +0.5pp
    ）。
  • 估值触发：达到目标估值倍数（
    P/E
    、
    P/FFO
    或
    P/FCF
    ）。
执行模式：
  • 拆分订单：
    40% -> 30% -> 30%
    。
  • 每次加仓前需进行一句话合理性检查：“投资逻辑是否完整 vs 是否出现结构性破裂”。

8) Produce standardized outputs

8) 生成标准化输出

Always produce three artifacts:
  1. Screening table (
    PASS
    , 
    HOLD-FOR-REVIEW
    , 
    FAIL
    with evidence).
  2. One-page stock memo (use 
    skills/kanchi-dividend-sop/references/stock-note-template.md
    ).
  3. Limit-order plan with split sizing and invalidation condition.
需始终生成三类成果：
  1. 筛选表格（含
    PASS
    、
    HOLD-FOR-REVIEW
    、
    FAIL
    及对应证据）。
  2. 单页股票备忘录（使用
    skills/kanchi-dividend-sop/references/stock-note-template.md
    ）。
  3. 带拆分仓位及失效条件的限价单规划。

Output

输出内容

Return and/or generate:
  1. SOP screening summary in markdown.
  2. Underwriting memo set based on 
    skills/kanchi-dividend-sop/references/stock-note-template.md
    .
  3. Optional plan artifact file generated by 
    skills/kanchi-dividend-sop/scripts/build_sop_plan.py
    in 
    reports/
    .
  4. Optional Step 5 entry-signal artifacts generated by 
    skills/kanchi-dividend-sop/scripts/build_entry_signals.py
    in 
    reports/
    .
返回并/或生成：
  1. Markdown格式的SOP筛选摘要。
  2. 基于
    skills/kanchi-dividend-sop/references/stock-note-template.md
    的尽职调查备忘录集。
  3. 可选：由
    skills/kanchi-dividend-sop/scripts/build_sop_plan.py
    在
    reports/
    目录下生成的规划成果文件。
  4. 可选：由
    skills/kanchi-dividend-sop/scripts/build_entry_signals.py
    在
    reports/
    目录下生成的第5步入场信号成果。

Cadence

监控节奏

Use this minimum rhythm:
  • Weekly (15 min): check dividend and business-news changes only.
  • Monthly (30 min): rerun screening and refresh order levels.
  • Quarterly (60 min): deep safety review using latest filings/earnings.
遵循以下最低监控频率：
  • 每周（15分钟）：仅检查股息及业务新闻变化。
  • 每月（30分钟）：重新运行筛选并更新订单价位。
  • 每季度（60分钟）：结合最新财报/业绩进行深度安全复查。

Multi-Skill Handoff

多技能交接

Run this skill first, then hand off outputs:
  1. To 
    kanchi-dividend-review-monitor
    for daily/weekly/quarterly anomaly detection.
  2. To 
    kanchi-dividend-us-tax-accounting
    for account-location and tax classification planning.
先运行本技能，再将输出结果交接至：
  1. kanchi-dividend-review-monitor
    用于每日/每周/季度异常检测。
  2. kanchi-dividend-us-tax-accounting
    用于账户配置及税务分类规划。

Guardrails

约束规则

  • Do not issue blind buy calls without Step 4 and safety checks.
  • Do not treat high yield as value before validating coverage quality.
  • Keep assumptions explicit when data is missing.
  • 未通过第4步及安全检查前，不得发出盲目买入建议。
  • 在验证派息覆盖质量前，不得将高收益率视为价值标的。
  • 当数据缺失时，需明确说明假设条件。

Resources

资源

  • skills/kanchi-dividend-sop/scripts/build_sop_plan.py
    : deterministic SOP plan generator.
  • skills/kanchi-dividend-sop/scripts/tests/test_build_sop_plan.py
    : tests for plan generation.
  • skills/kanchi-dividend-sop/scripts/build_entry_signals.py
    : Step 5 target-buy calculator (
    5y avg yield + alpha
    ).
  • skills/kanchi-dividend-sop/scripts/tests/test_build_entry_signals.py
    : tests for signal calculations.
  • skills/kanchi-dividend-sop/references/default-thresholds.md
    : baseline thresholds and profile tuning.
  • skills/kanchi-dividend-sop/references/valuation-and-one-off-checks.md
    : sector valuation map and one-off checklist.
  • skills/kanchi-dividend-sop/references/stock-note-template.md
    : one-page memo template for each candidate.
  • skills/kanchi-dividend-sop/scripts/build_sop_plan.py
    ：确定性SOP规划生成器。
  • skills/kanchi-dividend-sop/scripts/tests/test_build_sop_plan.py
    ：规划生成测试脚本。
  • skills/kanchi-dividend-sop/scripts/build_entry_signals.py
    ：第5步目标买入计算器（
    5年平均收益率+alpha
    ）。
  • skills/kanchi-dividend-sop/scripts/tests/test_build_entry_signals.py
    ：信号计算测试脚本。
  • skills/kanchi-dividend-sop/references/default-thresholds.md
    ：基线阈值及配置调优参考。
  • skills/kanchi-dividend-sop/references/valuation-and-one-off-checks.md
    ：板块估值映射及一次性事件检查清单。
  • skills/kanchi-dividend-sop/references/stock-note-template.md
    ：单页候选标的备忘录模板。