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/kanchi-dividend-sop

@5912fa6

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.

Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/kanchi-dividend-sop

This session only. Nothing lands on disk.

referencesdefault-thresholds.md

≈713 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Default Thresholds

Use these defaults when users do not provide custom risk settings.

Baseline (US Stock-Focused)

Category Metric Default Interpretation
Yield Forward dividend yield >= 3.5% Kanchi Step 1 core filter
Yield trap Extreme yield flag >= 8.0% Force deep dive before pass
Growth Revenue CAGR (5y) > 0% Basic business expansion check
Growth EPS CAGR (5y) > 0% Earnings trend health
Dividend trend Dividend growth (5y) Non-declining Allow flat only with strong safety
Safety EPS payout ratio <= 70% 70-85% = caution
Safety FCF payout ratio <= 80% >100% = high risk
Balance sheet Net debt trend Not persistently rising Rising 3 periods = warning
Balance sheet Interest coverage >= 3.0x <2.5x = caution
Entry trigger Yield alpha vs 5y average +0.5pp Default Kanchi Step 5 pullback threshold

Instrument-Specific Notes

Use these denominator replacements for coverage checks:

Instrument type Primary denominator Notes
Stock FCF Use CFO - CapEx
REIT FFO/AFFO Prefer AFFO if available
BDC NII Compare NII with distribution
ETF Fund-level distribution coverage unavailable in many cases Focus on methodology and holdings quality

Objective Tuning

Apply profile-specific adjustments:

Profile Yield floor Safety bias Notes
Income now 4.0% Tight safety checks Avoid overconcentration in one high-yield sector
Balanced 3.0-3.5% Medium Blend current income and dividend growth
Growth first 1.5-2.5% High quality first Accept lower initial yield for higher dividend CAGR

Step 5 Alpha Tuning

Use this range for yield-trigger alpha:

  • Stable mega-cap compounders: +0.3pp.
  • Default baseline: +0.5pp.
  • Higher-volatility names: +0.8pp to +1.0pp.

Entry Signal Interpretation

When using build_entry_signals.py, interpret signals as follows:

Signal Meaning Action
TRIGGERED Current price <= buy target price Ready for first tranche (40%) if thesis intact
WAIT Current price > buy target price Monitor; set limit order at buy target
ASSUMPTION-REQUIRED Missing data (yield history or dividend) Manual research needed before entry

Drop Needed Percentage

  • 0%: Price already at or below target.
  • 1-10%: Near entry zone; consider scaling in if pullback accelerates.
  • >10%: Significant gap; wait for pullback or reassess target.

Portfolio Constraints

Use these as practical defaults:

  • Max positions: 15-30.
  • Max single position at cost: <= 8%.
  • Max sector exposure: <= 25%.
  • High-yield bucket (REIT/telecom/utilities combined): <= 35%.

Override only when user explicitly chooses a different policy.

Source: SKILL.md on GitHub

1 alert16d5 checks · Risk SAFE
  • Gen Agent Trust Hub16d

    The skill provides a deterministic implementation of Kanchi's dividend stock analysis method adapted for the US market. It uses an offline financial analysis rule engine combined with external endpoints from Financial Modeling Prep (FMP) and local corporate event logs. No security issues, malicious prompt injections, obfuscations, or dangerous dynamic code evaluation vectors were detected. All external sources are well-known technology endpoints or local modules, and secret tracking instructions follow safe practices.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: MEDIUM · 1 issue

  • Runlayer7mo

    4/10 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 5912fa6. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 18 hours ago.

Activeupdated 2 months ago

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