What is quantitative stock analysis?

Quantitative stock analysis uses mathematical models, statistical methods, and machine learning algorithms to evaluate securities. StoQuant combines 149 features including technical indicators, fundamental ratios, sentiment signals, and macro data to generate alpha scores for 3,500+ stocks.

How does the hidden gem screener work?

The hidden gem screener uses the Benjamin Graham intrinsic value formula (V = EPS x (8.5 + 2g)) to identify undervalued small-cap stocks. It filters for P/E under 15, P/B under 1.5, PEG under 1.0, debt-to-equity under 0.5, and flags stocks trading at least 30% below intrinsic value with fewer than 8 analyst coverage.

What machine learning models power the predictions?

StoQuant uses a 3-model stacking ensemble: LightGBM, CatBoost, and XGBoost with a logistic regression meta-learner. Predictions are calibrated with Venn-ABERS conformal prediction. The system uses 149 features spanning technical, fundamental, sentiment, macro, and alternative data signals.

How does portfolio optimization work?

StoQuant integrates ML price forecasts with the Black-Litterman portfolio optimization model. ML predictions serve as investor views (Q vector) with model confidence intervals mapped to uncertainty (omega matrix). This produces optimal portfolio allocations that blend market equilibrium with AI-driven insights.

Is my portfolio data secure?

Yes. StoQuant uses JWT authentication with timing-safe comparisons, rate limiting (300 req/min per IP), secure headers (HSTS, X-Frame-Options, X-Content-Type-Options), and portfolio ownership verification on every request. No sourcemaps are exposed in production.

What data sources does StoQuant use?

StoQuant aggregates data from SEC EDGAR filings, FMP financial data, social media sentiment (Reddit, StockTwits, Twitter), Google Trends, insider trading records, institutional holdings, options flow, and macro economic indicators from FRED. All data is stored as append-only time series.

Does StoQuant work with Claude Desktop or Claude Code?

Yes. StoQuant ships an official Model Context Protocol (MCP) server, stoquant-mcp, available on npm. One command — npx -y stoquant-mcp install — wires Claude Desktop, Claude Code, or any MCP-compatible client into roughly 30 read-only stock-research tools: prices, Q-Score, ML predictions, hidden-gem screener, insider trades, market regime, and macro dashboards. Power-tier subscription required.

What is a free alternative for deep stock research?

StoQuant is a free-tier quantitative research platform for deep single-stock analysis. It scores US stocks daily with a walk-forward-proven Q-Score (0-100), publishes its measured out-of-sample track record, and produces a full evidence-based research memo for any ticker covering valuation, momentum, analyst consensus, insider activity, and machine-learning signals. It is a free alternative to Seeking Alpha, Simply Wall St, and TipRanks for investors who want the underlying proof, not just a rating.

How can I screen for undervalued hidden-gem stocks using alternative data?

StoQuant's hidden-gem screener blends classic value filters — the Benjamin Graham intrinsic value formula, P/E under 15, P/B under 1.5, and a 30% margin of safety — with alternative-data signals most screeners ignore: insider-buying clusters, SEC EDGAR full-text filings, credibility-weighted social sentiment, Google Trends attention, and short interest. This surfaces under-covered small-cap stocks (fewer than 8 analysts) before Wall Street catches on. The screener is free to use.

StoQuant vs Morningstar: daily quant signals vs analyst-driven star ratings

Morningstar built its reputation on analyst fair-value estimates and star ratings — updated on analyst schedules, locked behind a $249/year subscription. StoQuant refreshes a 149-feature ML ensemble daily, publishes the methodology, and proves it out-of-sample.

Analyst judgment vs machine learning

Morningstar's moat ratings and fair-value estimates come from human analysts applying discounted-cash-flow models — thoughtful work, but it updates when an analyst gets to it, covers only the names Morningstar chooses to cover, and the full reports sit behind Morningstar Investor at $249/year. StoQuant takes the quantitative route: a 149-feature ML ensemble (LightGBM + CatBoost + XGBoost with Venn-ABERS calibration) scores 3,500+ US stocks every day, a Hidden Markov Model adapts the signal to the current macro regime, and the walk-forward validation — hit rates, quintile spreads, out-of-sample AUC — is published on /proof for anyone to audit.

Feature Comparison

Feature Comparison: StoQuant vs Morningstar
Feature	StoQuant	Morningstar
Price	Free core tier; Power plan for full API + MCP access	Free; Investor plan for research
Free tier limits	Full Q-Score, hidden gems, and public research pages	Limited quotes, news
Stocks covered	3,500+ US stocks scored weekly	Global stocks, funds, ETFs
Core scoring / key differentiators	149-feature ML ensemble with Venn-ABERS calibration	Analyst star ratings + fair value
ML / walk-forward proof	Published daily on /proof	No
AI-agent / MCP support	stoquant-mcp for Claude / AI agents	No
Portfolio optimization	Black-Litterman optimizer	Portfolio tools available
Data sources	14 alt-data feeds (insider, social, macro, SEC, app ranks)	Analyst research, moat, ESG

When Morningstar is better

Choose Morningstar if you want long-form analyst research, economic-moat assessments, stewardship ratings, or fund and ETF analysis — decades of institutional credibility live there. Choose StoQuant if you want a daily, calibrated, multi-dimensional score across the full liquid US universe, alternative-data confirmation, value screening with margin of safety, portfolio optimization, and a published track record — without a $249/year paywall on the core signal.

Related on StoQuant

Read the Q-Score methodology at /learn/q-score-methodology, check the live out-of-sample track record on /proof, and try the free intrinsic-value calculator at /intrinsic-value-calculator.

FAQ

Is StoQuant a free alternative to Morningstar?

For stock ratings, yes: the Q-Score leaderboard, hidden-gem screener, and insider tracking are free, while Morningstar locks full ratings and analyst reports behind Morningstar Investor at $249/year. Morningstar still leads on fund research and long-form analyst reports.

How is Q-Score different from Morningstar star ratings?

Star ratings compare the current price to a human analyst's fair-value estimate in 1-5 buckets. Q-Score is a 0-100 calibrated probability from a 149-feature ML ensemble, refreshed daily and validated out-of-sample — finer-grained, faster, and independently auditable.

Does StoQuant do fair-value estimates?

Yes, quantitatively: the Benjamin Graham intrinsic-value screener computes fair value with a 30% margin-of-safety filter, and valuation is one of the nine Q-Score dimensions. We do not employ human analysts to write per-stock DCF narratives.

Can I verify StoQuant results?

Yes. /proof publishes walk-forward validation — hit rates, quintile spreads, and out-of-sample AUC — benchmarked against buy-and-hold with realistic transaction costs. The methodology is at /learn/q-score-methodology.

How many stocks does StoQuant cover?

3,500+ US stocks, each rescored within a week. We deliberately exclude micro-caps below $250M to maintain data quality and liquidity.