About Alpha Galactica

Methodology

Alpha Galactica classifies tech stocks into a multi-dimensional feature framework. Each stock is tagged with codes describing its supply-chain position (S-Series), business model methodology (M-Series), secular tailwinds (T-Series), AI positioning, cycle exposure, governance, balance-sheet health, and competitive moat.

Three Scores

Quality Score (0–100) measures fundamental strength using methodology-specific weights. Six valuation formulas (M1–M6) are matched to business archetypes — Compounders score on Rule of 40, Capital-Intensive firms on acceleration and sequential growth, Digital Utilities on operating cash flow margin, and Efficiency Pivots on revenue-per-employee and OpEx leverage. Governance (G-Series) adjusts the score by up to ±10 points.

Conviction Score (0–30) counts secular tailwind themes (T1–T10). More tailwinds mean higher conviction, but macro risk caps and a quality floor prevent high conviction on weak or macro-threatened names.

Opportunity Score (0–100) combines structural health (Quality × 0.4), thematic conviction (up to 30 pts), and tactical signals like smart-money flows, cycle timing, valuation gap, and analyst momentum (up to 30 pts). A macro multiplier scales the result down in elevated or critical risk regimes.

AI Analysis Pipeline

A three-stage AI pipeline — Classify, Risks & Catalysts, Narrative — assigns features from SEC filings, FINRA data, and market signals. Each stage locks in its outputs before the next begins. Deterministic post-processing then generates health (H), valuation (V), and moat (W) features and enforces scoring rules like the Neocloud Death Cross and Phase 2 Infrastructure overrides.

Feature Reference