Quant Futures Research Platform

About this project

A substantially developed Python-based quantitative research platform for systematically researching and evaluating futures trading strategies. The platform includes modular historical backtesting, strategy research, ICT-based market-structure research, moving-average crossover research, risk management, position sizing, transaction-cost modeling, statistical validation, permutation testing, sequential-window validation, parameter sweeps, experiment tracking, prop-firm evaluation simulation, evaluation robustness research, trade-level exports, configuration-driven experiments, a command-line interface, automated testing, and golden regression tests. The architecture is strategy-agnostic and designed to support additional futures instruments, strategies, risk models, data providers, and evaluation rules without rebuilding the underlying research infrastructure. The project is pre-revenue and is being offered as a software and quantitative research asset rather than an operating SaaS business. Source code, tests, configuration, documentation, and associated project assets are included subject to the final transfer agreement.

Original vision

Build a rigorous quantitative research foundation for testing whether futures trading strategies demonstrate repeatable statistical evidence of an edge rather than relying solely on historical profitability.

What's included

Everything that comes with the listing on day one.

• GitHub repository
• Source code archive
• Documentation and runbooks