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 Danelfin: the Danelfin alternative built on value investing for small caps

Danelfin is a legitimate AI-powered stock analyst for US and European large-caps — distilling technical, fundamental, and sentiment data into a 1-10 AI Score. StoQuant applies the Benjamin Graham value methodology to the $250M-$10B small-cap universe where retail investors have real alpha opportunities, combining a 149-feature ML ensemble with published walk-forward validation. The two tools serve different markets and different investment philosophies.

Two tools, two markets

Danelfin is one of the most polished AI stock analysis platforms for retail investors. Its AI Score (1-10) blends technical indicators, fundamental metrics, and news sentiment into a clean, actionable signal. The platform covers S&P 500 and STOXX 600 stocks — the large and mega-cap names that institutions already dominate. Danelfin's free tier gives you the Top 10 stocks and 10 reports per month; full access starts at $22/month. StoQuant takes a fundamentally different approach. Instead of competing for the same large-cap signals, we apply Benjamin Graham's value methodology to the $250M-$10B small-cap universe — exactly where retail investors have an information advantage over institutions. Our Q-Score is built from 149 features across valuation, momentum, sentiment, insider activity, ML signals, and Graham intrinsic value, then calibrated with Venn-ABERS isotonic regression so the probabilities are honest. Every single prediction is tracked in an append-only accuracy log published on /proof. For an investor screening small-caps with a value philosophy, StoQuant is the natural choice. For someone who wants AI-driven signals on large-cap US and European names, Danelfin is a strong option.

Feature Comparison

Feature Comparison: StoQuant vs Danelfin
Feature	StoQuant	Danelfin
Price	Free core tier; Power plan for full API + MCP access	Free (limited); Plus $22/mo, Pro $59/mo, Elite $134/mo
Free tier limits	Full Q-Score, hidden gems, and public research pages	Top 10 stocks, 10 reports/mo, limited AI Score
Stocks covered	3,500+ US stocks scored weekly	S&P 500 + STOXX 600 (large-cap US/Europe)
Core scoring / key differentiators	149-feature ML ensemble with Venn-ABERS calibration	AI Score 1-10 from technical, fundamental, sentiment
ML / walk-forward proof	Published daily on /proof	Published historical performance; no append-only forward validation
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)	Technical indicators, fundamentals, news sentiment

Transparency: open methodology vs black box

Danelfin's AI Score is a proprietary blend of technical, fundamental, and sentiment signals. The methodology is explained in general terms, but the exact feature weights, model architecture, and validation methodology are not published. You see the score — not how it was built or how it performed out-of-sample. StoQuant publishes everything: all 149 features are documented on /methodology, the model files are open, the Benjamin Graham formula is explained on /learn/benjamin-graham-formula, and the walk-forward validation metrics update daily on /proof. When our Q-Score says a stock has a 75% probability of outperforming, you can verify that claim against actual historical predictions. That is not possible with a proprietary score. For value investors who need to understand and trust their edge before deploying capital, transparency is the only path.

Related on StoQuant

Explore the Hidden Gems screener (stoquant.com/gems), the Q-Score leaderboard (stoquant.com/q-score-leaderboard), the walk-forward proof dashboard (stoquant.com/proof), and the Benjamin Graham formula guide (stoquant.com/learn/benjamin-graham-formula).

FAQ

Why choose StoQuant over Danelfin?

Danelfin is excellent for large-cap AI signals. StoQuant targets the small-cap value universe ($250M-$10B) where retail investors have a genuine information advantage. StoQuant publishes all 149 features, model files, and append-only walk-forward validation — you can verify every claim. Danelfin's AI Score is proprietary and its methodology is not independently auditable.

Does StoQuant cover European stocks?

StoQuant currently focuses on US-listed stocks scored weekly across 3,500+ names. Danelfin covers both S&P 500 and STOXX 600 European stocks. If European coverage is your priority, Danelfin is the stronger choice.

Is StoQuant free?

Yes. All core StoQuant features — Q-Score, Hidden Gems screener, Benjamin Graham intrinsic value calculator, and public research pages — are free. Danelfin's free tier covers S&P 500 stocks only; full coverage starts at $22/month.

Which platform has better AI accuracy?

Danelfin reports that its AI Score 10 stocks have historically outperformed by ~14.7% annualized since 2017. StoQuant publishes daily append-only walk-forward validation on /proof, showing a statistically significant Information Coefficient with a t-statistic above 3.0. Both platforms demonstrate edge, but only StoQuant's is independently verifiable in real time.