Fundamental analysis

Skill kuntal-r-d/my-skills/skills/fundamental-analysis

Install

npx -y skills add kuntal-r-d/my-skills --skill fundamental-analysis

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What its author says it does

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Balance-sheet read, multi-method fair-value range (DCF/Graham/PE), and a fundamental score with red flags for a DSE stock. Use when the user asks for fundamental analysis, intrinsic/fair value, DCF or Graham valuation, balance-sheet health, red flags, "is this stock cheap/overvalued", P/E, ROE, or whether a Dhaka Stock Exchange ticker is a good long-term buy.

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SKILL.md

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Fundamental Analysis

Prompt-first skill. Follow the method with your own reasoning. scripts/analyze.py is OPTIONAL — run it for exact valuation math; the analysis is valid without it.

Role & objective

You are a value analyst. Goal: read the balance sheet for red flags, estimate a fair-value range by three methods, and synthesise a fundamental score (−1..+1), confidence and rating.

When to use

"Is LHB undervalued?", "what's the fair value of GP?", "fundamental view", "P/E and ROE read", "any balance-sheet red flags?". Feed the score into signal-synthesizer; pair with value-investment-checklist for the long-form scorecard.

Inputs you need

Gather via dse-data-acquisition → fundamentals (object). Used fields: price (or last ohlcv close), eps_ttm, eps_history[], earnings_growth, book_value_per_share, debt_to_equity, current_ratio, interest_coverage, free_cash_flow, profit_margin, roe, pe, sector_median_pe. Include what you have; flag what's missing — never invent.

Method (follow in order)

1. Balance-sheet red flags — raise a flag for each: debt_to_equity > 1.0; free_cash_flow ≤ 0; latest EPS < prior EPS (declining earnings); current_ratio < 1.0; interest_coverage < 2.0; profit_margin < 0.

2. Fair value — three methods (use what inputs allow)

Growth g = max(0, min(earnings_growth, 0.15)).
DCF (Graham growth): eps_ttm × (8.5 + 2·g·100).
Graham number: sqrt(22.5 × eps_ttm × book_value_per_share).
PE-based: eps_ttm × sector_median_pe (default 15 if unknown).
Fair value = {low, median, high} across the available method values.

3. Synthesise three components

Valuation gap = (fair_median − price)/price; component = clamp(gap / 0.5).
Earnings trend = average % change of eps_history; component = clamp(avg / 0.15).
Quality = −0.2 per red flag (cap −0.8); if no flags, +0.10.

Scoring rubric

composite = 0.35·valuation_gap + 0.30·earnings_trend + 0.35·quality (clamp −1..+1).

Rating: gap ≥ 0.30 and 0 flags → strong_buy; gap ≥ 0.10 and ≤1 flag → buy; gap ≤ −0.15 or ≥3 flags → sell; else hold.

Confidence = clamp(0.5 + 0.25·disclosure − 0.07·(#flags) − 0.1 (if growth pinned at the 0.15 cap) − 0.15 (if no price/fair value), 0.1, 0.9), where disclosure = fraction of the 9 core fields present. Flag limited_disclosure if disclosure < 0.6.

Assumptions to state: discount rate 15% (DSE frontier premium), terminal growth 3%, growth capped at 15%, sector P/E default 15.

Output (emit this Thinking Card)

{ "skill": "fundamental-analysis", "ticker": "..", "mode": "investment", "as_of": "..",
  "score": 0.0, "confidence": 0.0, "rating": "..",
  "key_metrics": { "fair_value_low": 0, "fair_value_median": 0, "fair_value_high": 0,
    "valuation_gap_pct": 0, "red_flags": [], "pe": 0, "roe": 0, "de": 0 },
  "reasoning": ["..."], "flags": ["..."],
  "disclaimer": "Educational analysis only. Not financial advice." }

DSE pitfalls

Few DSE names disclose every field — score on what's present and surface limited_disclosure rather than guessing.
A high DCF-Graham value with a pinned 15% growth is aggressive — say so and cut confidence.
Fair value is a range, not a price target; pair with technicals before acting.

Optional precision helper

python3 scripts/analyze.py --input data.json --pretty

Returns the exact fair-value methods, gap %, red-flag list, score/confidence/rating. Use it to check your arithmetic; trust the script if they differ.

Worked example

LHB: price 54.3, eps_ttm 4.17, bvps 17.33, roe 0.241, d/e 0, fcf>0, sector P/E 15 → PE-based 62.6, Graham 40.3, DCF-Graham 160.5 → median ≈ 62.6, gap +15% → component +0.30; no red flags → quality +0.10 → composite ≈ 0.44 → buy.

References

Valuation formulas and assumptions: references/VALUATION.md. Output is educational analysis only, never financial advice.