kanchi-dividend-sop

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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.

2installs

Sourcetradermonty/claude-trading-skills

Added on2026-02-24

NPX Install

npx skill4agent add tradermonty/claude-trading-skills kanchi-dividend-sop

SKILL.md Content

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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

Prepare one of the following inputs before running the workflow:

Output from

skills/value-dividend-screener/scripts/screen_dividend_stocks.py

.

Output from

skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py

.

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/

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

skills/kanchi-dividend-sop/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:

skills/value-dividend-screener/scripts/screen_dividend_stocks.py

output (FMP/FINVIZ).

skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py

output.

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:

```
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.

4) Apply Kanchi Step 2 (growth and safety)

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.

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

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.

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%
```
.
Require one-sentence sanity check before each add: "thesis intact vs structural break".

8) Produce standardized outputs

Always produce three artifacts:

Screening table (
```
PASS
```
,
```
HOLD-FOR-REVIEW
```
,
```
FAIL
```
with evidence).

One-page stock memo (use

skills/kanchi-dividend-sop/references/stock-note-template.md

).

Limit-order plan with split sizing and invalidation condition.

Output

Return and/or generate:

SOP screening summary in markdown.

Underwriting memo set based on

skills/kanchi-dividend-sop/references/stock-note-template.md

.

Optional plan artifact file generated by

skills/kanchi-dividend-sop/scripts/build_sop_plan.py

in

reports/

.

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:

To
```
kanchi-dividend-review-monitor
```
for daily/weekly/quarterly anomaly detection.
To
```
kanchi-dividend-us-tax-accounting
```
for account-location and tax classification planning.

Guardrails

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.

Resources

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.