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An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates strategy robustness by applying Rademacher random vectors for anti-overfitting analysis.
An honesty harness for LLM trading research: point-in-time discipline, leakage self-tests, and forward-only LLM feature collection. A-shares + US equities.
Adversarial co-evolution orchestrator: an executor LLM improves an artifact, a deterministic scorer judges it (keep-if-better via git), a validator LLM advises — until quality peaks. Off-the-shelf agent CLIs, walk-forward scoring, live web dashboard. General-purpose, not just trading.
Systematic intraday opening-range breakout strategy on US equities — 10-year validated backtest with walk-forward optimization, statistical robustness suite, and live paper-trading on Alpaca.
Portfolio research on US equities — point-in-time data, survivorship-bias-free backtests, walk-forward validation gated by Deflated Sharpe and PBO. 158 factors over 20,931 tickers (1997-2026), plus tactical ETF allocation. Ships the rejections too: 1 adopted, 20+ rejected, and one headline number retracted.
This project implements a Walk-Forward Optimization (WFO) strategy using Tree-Parzen Estimator (TPE) for hyperparameter optimization. It includes modules for backtesting, configuration, optimization, and reporting.
A walk-forward crypto research system, paper-traded in public: a weekly self-refitting BTC/ETH machine with real costs, real funding, frozen-replay validation, and seven documented failed ideas.
Portfolio backtest engine with montecarlo simulation, walk-forward, efficient frontier, FIRE, charts, performance optimization, max drowdown with Ai suggest!