graham-value-investing_skill

This skill applies Graham's deep value framework to identify safe, discounted investments through Net-Net screening and margin-of-safety based valuation.
  • Rust

7

GitHub Stars

5

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill louloulin/claude-agent-sdk --skill graham-value-investing

  • detailed-analysis.md4.9 KB
  • evaluation-criteria.md4.7 KB
  • reference-implementation.md9.4 KB
  • reference.md4.0 KB
  • SKILL.md5.9 KB

Overview

This skill implements Benjamin Graham’s deep value investing framework focused on margin of safety and buying at deep discounts to intrinsic value. It codifies Net-Net screening, the Graham valuation formula (with bond yield adjustment), and a multi-factor scoring system to support buy/observe/sell decisions. The skill is designed for disciplined, capital-protecting value investors seeking systematic screening and valuation guidance.

How this skill works

The skill computes intrinsic value using Graham’s formula (V = EPS × (8.5 + 2g), adjusted by prevailing AAA bond yield when needed) and measures margin of safety against the current market price. It performs a strict Net-Net calculation (current assets minus total liabilities, per share) and applies liquidity, leverage, profitability, and stability filters. Finally it aggregates weighted sub-scores (safety, financial health, earnings quality, valuation) into a 0–100 score with thresholds for buy/hold/avoid.

When to use it

  • Screening undervalued, traditional or cyclical companies where balance-sheet metrics matter
  • Seeking disciplined entry points with defined margin-of-safety thresholds (≥30%)
  • Evaluating small or neglected stocks with strong asset coverage or recurring earnings
  • Running systematic value checks during bear markets or panic-driven sell-offs
  • Filtering out growth-oriented or intangible-heavy businesses unsuitable for balance-sheet value methods

Best practices

  • Use conservatively estimated growth rates (g) based on 3–5 year EPS averages and industry context
  • Verify net-net calculations on a per-share basis and confirm no off-balance-sheet liabilities or major contingencies
  • Require liquidity and leverage thresholds (current ratio ≥2.0, current assets ≥2× total liabilities) before considering purchase
  • Combine quantitative scores with qualitative checks (management integrity, litigation, regulatory risk)
  • Treat Net-Net hits as high-conviction but rare opportunities; expect low frequency in modern markets

Example use cases

  • Identify small-cap manufacturing companies trading below 2/3 of Net-Net per-share value for potential deep-value purchases
  • Run batch valuation across a watchlist to highlight stocks with ≥30% margin of safety per Graham formula
  • Score candidates for a concentrated, capital-preserving value portfolio using the 0–100 rubric
  • Reject tech or high-intangibles firms automatically and focus analyst time on balance-sheet-rich targets
  • Monitor bond yield adjustments to Graham valuation when AAA yields deviate materially from historical averages

FAQ

No. The framework relies on tangible assets and earnings history; firms with large intangible value or no consistent earnings are not suitable.

How conservative should the growth rate g be?

Use a conservative estimate based on historical EPS trends and industry outlook; default to a low single-digit rate unless justified.

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