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 StockAnalysis.com: predictive ML depth vs fundamentals-only data

StockAnalysis.com is one of the best free fundamentals sites: financials, ratios, and forecasts, fast and clean. StoQuant starts where fundamentals stop — a 149-feature ML ensemble, alternative-data signals, regime detection, and walk-forward validation of every signal.

Descriptive data vs predictive signal

StockAnalysis.com answers "what does this company look like?" extremely well — income statements, balance sheets, ratios, and analyst forecasts in a fast, free UI. But fundamentals describe the present; they do not tell you which of the 500 stocks that screen "cheap" will actually outperform next quarter. StoQuant answers that question: a 149-feature ML ensemble (LightGBM + CatBoost + XGBoost with Venn-ABERS calibration) produces a 0-100 Q-Score for 3,500+ US stocks, and the walk-forward results — hit rates, quintile spreads, out-of-sample AUC — are published on /proof.

Feature Comparison

Feature Comparison: StoQuant vs StockAnalysis.com
Feature	StoQuant	StockAnalysis.com
Price	Free core tier; Power plan for full API + MCP access	Free
Free tier limits	Full Q-Score, hidden gems, and public research pages	Full access
Stocks covered	3,500+ US stocks scored weekly	US stocks
Core scoring / key differentiators	149-feature ML ensemble with Venn-ABERS calibration	Financial statements, ratios, analyst forecasts
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	No
Data sources	14 alt-data feeds (insider, social, macro, SEC, app ranks)	Fundamentals, estimates

When StockAnalysis.com is better

Choose StockAnalysis.com when you need to read financial statements, compare ratios across peers, or check analyst revenue forecasts — quickly and for free. It is one of the cleanest fundamentals UIs on the web, and we use similar data ourselves. Choose StoQuant when you have the fundamentals and need the next step: which names the model expects to outperform, confirmed by alternative data, with a published track record you can audit.

Related on StoQuant

See the Q-Score methodology at /learn/q-score-methodology, the live out-of-sample track record on /proof, and the free hidden-gems screener at /gems.

FAQ

Is StoQuant a free alternative to StockAnalysis.com?

They overlap partly. StockAnalysis.com is free for fundamentals; StoQuant is free for predictive scoring, hidden-gem screening, and insider tracking. Many investors use both: StockAnalysis.com to read the financials, StoQuant to decide what to buy.

Does StoQuant have financial statements and ratios?

Yes — fundamentals are a core input to the 149 ML features, and per-ticker research pages surface the key ratios. But our focus is turning that data into a forward-looking score, not replicating a statements viewer.

What does Q-Score add over analyst forecasts?

Analyst forecasts are slow, often conflicted, and one-dimensional. Q-Score blends analyst revisions with momentum, sentiment, insider activity, regime, and 140+ other features, then calibrates the output as a probability validated on out-of-sample data.

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.

Can I verify StoQuant predictions actually work?

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