git:20260303.49f4e4f to git:20260517.7e57390

---

name: kanchi-dividend-sop

description: Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure. Use when users ask for かんち式配当投資, dividend screening, dividend growth quality checks, PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation. Covers screening, deep dive, entry planning, and post-purchase monitoring cadence.

---

# Kanchi Dividend Sop

## Overview

Implement Kanchi's 5-step method as a deterministic workflow for US dividend investing.

Prioritize safety and repeatability over aggressive yield chasing.

## When to Use

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.

## Prerequisites

### API Key Setup

The entry signal script requires FMP API access:

```bash

export FMP_API_KEY=your_api_key_here

```

### Input Sources

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.py`.

3. User-provided ticker list (broker export or manual list).

#### Expected JSON Input Format

When using `--input`, provide JSON in one of these formats:

```json

{

"profile": "balanced",

"candidates": [

{"ticker": "JNJ", "bucket": "core"},

{"ticker": "O", "bucket": "satellite"}

]

}

```

Or simplified:

```json

{

"tickers": ["JNJ", "PG", "KO"]

}

```

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/

```

```bash

python3 skills/kanchi-dividend-sop/scripts/build_entry_signals.py \

--tickers "JNJ,PG,KO" \

--alpha-pp 0.5 \

--output-dir reports/

```

## Workflow

### 1) Define mandate before screening

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 `references/default-thresholds.md` and apply baseline

settings unless the user overrides.

### 2) Build the investable universe

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.

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

Primary rule:

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

Use `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.

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

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.

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

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%`.

### 8) Produce standardized outputs

## Output

Return and/or generate:

1. SOP screening summary in markdown.

2. Underwriting memo set based on

`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/`.

## Cadence

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.

## Multi-Skill Handoff

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.

## Guardrails

- Do not treat high yield as value before validating coverage quality.

## Resources