fundamental-analysis

compatibility	Python 3.8+, standard library only. No network. No third-party packages.
description	Reads a DSE stock's fundamentals, flags balance-sheet risks, derives a multi-method fair-value range, and returns a fundamental score, rating, and reasoning. 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.
license	Apache-2.0
metadata	{"author":"stock-buddy","github-path":"skills/fundamental-analysis","github-pinned":"main","github-ref":"refs/heads/main","github-repo":"https://github.com/kuntal-r-d/my-skills","github-tree-sha":"7e866e6949a7626c009229cb2941119761fb845a","mode":["investment"],"prd_refs":["PRD-002:REQ-018","PRD-002:REQ-104","PRD-002:REQ-105","PRD-001:REQ-006","PRD-001:REQ-044"],"version":"0.1.0"}
name	fundamental-analysis

Fundamental Analysis

When to use

Activate when a user wants a fundamental read on a DSE stock: "is GP fundamentally strong?", "what's the fair value of BEXIMCO?", "run a DCF", "any balance-sheet red flags?", "is this overvalued?". This is the fundamental leg of the dual-mode signal — feed its score into signal-synthesizer, or pair it with value-investment-checklist.

What it does

Runs three logical stages in one pass (PRD-002 REQ-104/105/018):

1. Balance Sheet Reader (balance_sheet_reader) — extracts key line items and emits RED FLAGS: D/E > 1.0 (high leverage), free cash flow <= 0, declining earnings (latest EPS < prior), current ratio < 1, interest coverage < 2, profit margin < 0.
2. Valuation Extractor (valuation_extractor) — three methods with explicit assumptions and a fair-value range (low / median / high):
   • DCF (Graham growth formula) — eps_ttm * (8.5 + 2 * g * 100) where g = min(earnings_growth, 15%).
   • Graham number — sqrt(22.5 * eps_ttm * book_value_per_share).
   • PE-based — eps_ttm * sector_median_pe (default 15 if unknown).
3. Fundamental Synthesizer (analyze) — combines earnings trend (EPS slope), red-flag count, valuation gap (fair_median - price) / price, and disclosure quality into a score in [-1, +1]. Confidence drops with red flags, aggressive assumptions, or thin disclosure. Rating: strong_buy / buy / hold / sell.

Output is a Thinking Card (see suite README).

How to run

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

Reads fundamentals (required). Price is taken from fundamentals.price, falling back to the last ohlcv close. Returns score (-1..+1), confidence (0..1), rating, key_metrics (fair_value_low/median/high, valuation_gap_pct, red_flags, pe, roe, de, methods, assumptions) and reasoning.

Try it now with the shared fixture:

python3 scripts/analyze.py --input ../_fixtures/sample_input.json --pretty

Interpreting output

• A large positive valuation_gap_pct means price sits below the fair-value median (potentially undervalued); a negative gap means the opposite.
• rating blends the valuation gap with the red-flag count — sell triggers on a negative gap or three-plus red flags regardless of cheapness.
• flags carry confidence penalties (limited_disclosure, no_eps_history, no_price_or_fair_value) — never silently dropped.

Notes

Valuation methods, the Graham formulas, default assumptions (r = 15%, terminal g = 3%, sector P/E = 15), and DSE caveats are documented in references/VALUATION.md — including why DSE P/E benchmarks run higher than US comparables (PRD-001 REQ-044). Output is educational analysis only, never financial advice.