Python Market Research Platform with Modular Analysis Framework

AEGIS is a pre-revenue, documented Python platform for systematic-market research: an explainable research organization in software, not a single strategy script. It combines point-in-time data admission and provenance, modular market-analysis departments, evidence and planning contracts, portfolio/risk controls, execution modeling, persistence, historical replay, controlled research, no-outcome-access gates and governed capability research.

Its Research Director coordinates specialized departments plus Opportunity, Postmortem and Self-Study labs. These labs examine positive and negative outcomes—including mistakes and WAIT/NO_TRADE counterfactuals—and produce evidence-linked proposals for parameter or process tuning with target versions and rollback guidance. Changes are not silently self-tuned or promoted: human approval and frozen evaluation gates remain required.

Measured before sale-only documents, the repository contained 1,534 tracked files, 800 Python files, 340 Python test files, 654 research/study files, 160 Markdown documents and 758 reachable Git commits. Its data tooling catalogs, normalizes, verifies and manifests 222 Binance-derived datasets for reproducible research. Raw third-party market archives are excluded unless redistribution rights are confirmed; otherwise a buyer regenerates them from public sources.

The asset preserves positive clues, rejected candidates and negative results. Historical research found diagnostic clues but no independently validated profit edge, and final controlled programs ended in no-go decisions under frozen gates. The sale is for engineering and research infrastructure—not a promise of returns, signals, managed trading or a turnkey live bot.