The hyped AI/quant topics people search for, mapped honestly to what Quantustik actually ships — grounded in a real artifact, or clearly labelled educational. Nothing here is a performance promise.
Quantustik's core forecasting engine — a Schrödinger-equation + Feynman path-integral model with publicly calibrated confidence bands, including the failures. See the full page.
A live, hosted Model Context Protocol server exposing S&P 500 signals, forecasts, and market-conditions data so AI agents can query Quantustik directly. See the full page.
Two real LLM features layered on top of the quantitative model — a per-ticker AI summary and a news-sentiment score — framed honestly as context, not a trading signal. See the full page.
The honest answer: a single point prediction ("$X by Friday") is unfalsifiable marketing — a published, testable interval forecast is the real product. See the full page.
A 90% confidence interval is a coverage promise, not a difficulty rating — about 90% of realized prices should land inside the band over time, and it says nothing about direction. See the full page.
A well-calibrated confidence band and a profitable trade direction are two different questions — we publish coverage continuously and gate any win-rate behind a pre-registered track record. See the full page.
Named failure, not a hidden one: our confidence bands for AVGO and BRK-B at the 1-year horizon cover far fewer realized outcomes than the aggregate figure suggests — both went through a structural break the model cannot see coming. See the full page.
Corporate officers, directors, and large owners must report their own trades on SEC Form 4 within days of the transaction — a real paper trail, but a laggy and incomplete one on its own. See the full page.
Form 13F tells you what large institutional managers held at quarter end — weeks after the fact, and only the long equity side of their book. See the full page.
Crossing the ownership-disclosure threshold triggers a Schedule 13D or 13G filing — which one tells you whether the buyer wants to influence the company or just hold the stock. See the full page.
A market-conditions classifier tries to label the current backdrop as risk-on, risk-off, or somewhere in between — a genuinely useful framing, and one that is inherently uncertain and slow to catch turning points. See the full page.
A live view grouping the S&P 500 by GICS sector — realised returns over selectable windows plus average expected growth — portfolio context, not a timing signal. See the full page.
A live correlation heatmap framed as a concentration-risk lens — a metaphor for co-movement, not a prediction of it, and not literal quantum entanglement. See the full page.
How a calibrated forecast band's width becomes a stop distance, a reward-to-risk ratio, and a bounded position size — process, not promise. See the full page.
A live TP1/TP2/TP3 exit ladder and a volatility-scaled stop, with a break-even stop advance after the first target — untested for P&L publicly. See the full page.
A real trade plan needs an entry trigger, an invalidation level, a take-profit ladder, and a risk/reward gate — and a refusal to hand out an entry when the setup does not clear the bar. See the full page.
A real, hosted Model Context Protocol server for stock market data — streamable-HTTP, no API key required, a public discovery manifest, and a growing tool set for signals, forecasts, and trade plans. See the full page.
A step-by-step tutorial for pointing Claude (or any MCP client) at Quantustik's live stock market MCP server: get a key, add the server config, and run a guided risk-check prompt. See the full page.
A public v1 REST API for S&P 500 signals and forecasts, documented by a live OpenAPI schema — keyless for light use, metered for higher throughput, read-only by design. See the full page.
Educational research only — not investment advice.