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.

Morning brief: own-signal pre-market discovery for agents

StoQuant packs the same own-signal morning brief used on the channel — regime, VIX, SPY/QQQ/IWM session moves, own earnings_history names reporting today, optional gem spotlight — into MCP stoquant_get_morning_brief and GET /api/discovery/morning-brief. TipRanks due-diligence-agent foil: descriptive discovery research only. Not a buy rating. Not TipRanks Smart Score. Not TipRanks skill. While live /proof shows grade F with inverted excessSpreadPp (gated:no_edge), do not treat the brief as ranking edge.

What this morning brief is (and is not)

A StoQuant morning brief is a descriptive pre-market snapshot from own signals: the latest macro regime classification, VIXCLS, current-session SPY/QQQ/IWM percent moves, tickers on today's own earnings_history calendar, and an optional gem spotlight that already passes the shared gem buy-gate. It is a TipRanks due-diligence-agent foil in the discovery sense — agents get a structured brief without TipRanks Smart Score or TipRanks skill marketing. It is not a buy rating, not a Q-Score dimension, and does not drive autopilot buys.

How it works

Load own market context — Pull the latest macro regime + confidence, VIXCLS, and SPY/QQQ/IWM session moves pinned to the market-wide latest bar (missing indices are omitted, never backfilled).
Attach calendar + optional spotlight — List tickers reporting today from own earnings_history. Optionally surface one gem spotlight that clears cooldown + gemBuyGatePass + research-page readiness.
Attach /proof honesty — Every MCP/REST response includes the live /proof honesty banner (grade, excessSpreadPp, dataSufficient, gatedNoEdge). While gated:no_edge, treat the brief as descriptive research only — never as TipRanks skill or proven ranking edge.

Call it from Claude / MCP or REST

Pro/Power: stoquant_get_morning_brief (hosted MCP + stdio) and GET /api/discovery/morning-brief. Response shape: {asOf, sessionDate, regime, vix, vixTake, indices, reportingToday, spotlight, summary, notes, ownSignalsOnly, note, honesty}. Read honesty.banner and https://stoquant.com/proof before treating any line as edge. Related: Proof (stoquant.com/proof), MCP hub (stoquant.com/mcp), demand-zone discovery (stoquant.com/demand-zone).

FAQ

Is the morning brief a buy rating?

No. It is descriptive pre-market discovery only. It is not a Q-Score dimension and does not drive autopilot buys. While live /proof excessSpreadPp is inverted (gated:no_edge), do not treat the brief as ranking edge.

Does this claim TipRanks skill or replace TipRanks due-diligence-agent?

No TipRanks skill claims. Own StoQuant regime / VIX / index / earnings_history / gem signals only. Responses set ownSignalsOnly: true and attach the live /proof honesty banner. Positioned as a TipRanks due-diligence-agent foil for agents who want an own-signal brief — never TipRanks Smart Score marketing.

How do I call the morning brief?

With a Pro or Power key: MCP tool stoquant_get_morning_brief or REST GET /api/discovery/morning-brief. Both attach the honesty banner. Landing + share card: https://stoquant.com/morning-brief.

What does gated:no_edge mean here?

When /proof dataSufficient is true and excessSpreadPp is negative, honesty.gatedNoEdge is true. Auto-portfolio buys stay gated; the morning brief remains descriptive research only until excessSpreadPp > 0.