Where the systematic stack is documented.
QISAgent covers the machinery of quantitative investing: the platforms, data, and code that produce systematic strategies — and the autonomous agents beginning to run those workflows end-to-end. Everything here is working infrastructure, not commentary: a daily regime snapshot generated by published code, and the QIS Atlas, the working directory of the field.
Today's market snapshot.
Generated by a deterministic Python pipeline from public market data — no model outputs, no forecasts. The full generation code is published here. Informational only; not investment advice.
The QIS Atlas.
The working map of the systematic investment stack: execution platforms, market data providers, backtesting libraries, research frameworks, AI infrastructure, and quantum programs — each entry independently written, with dedicated profiles for the tools practitioners actually deploy.
QuantConnect
Cloud research-to-production on the open-source LEAN engine — the reference platform for algorithm development.
Interactive Brokers
The institutional execution workhorse behind custom trading systems — TWS API, FIX, and global market access.
Massive
Developer-first market data across equities, options, and futures — flat files to websockets.
Where intelligence meets governance.
The agents this pillar documents are the ones autonomous enough to need the governance layer at all. The walkthrough is where that connection stops being an assertion: one governed-quantity schedule, taken through Define, Validate, Evaluate, Record, and Inspect, with the real command and the real output at every stage — the interface an institutional buyer gets shown, not a description of one.
The code behind the platform.
Every automated utility on this ecosystem ships with its methodology published. The first workflow documents the daily snapshot pipeline itself — signal definitions, regime thresholds, failure handling, and the scheduled automation that runs it — as a reproducible template for rules-based market monitoring. The generator behind the whole ecosystem ships the same way: the knowledge graph is laid out deterministically at build time, published as formal RDF/OWL with a public SHACL shapes file, and re-validated against those shapes on every build — an outside system can confirm it conforms, not take our word for it.