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[ICML'26] An open-source demo of the bi-level optimization (BLO) method from "The Label Horizon Paradox". Reproduces the core method (BLO + brute-force baseline + backtest) on public Alpha158 factors and A-share data, showing that the optimal training label horizon can deviate from the inference ... Read more

Quantitative trading system for prediction markets using Bernoulli distributions, Kelly Criterion, and linear algebra. Features arbitrage detection, Monte Carlo simulation, backtesting, and interactive dashboard.

📉 Revenue resilience × price-drawdown backtesting engine — five-panel research workspace, 3D CAGR surface sweeps and out-of-sample factor search on SEC EDGAR + Yahoo Finance data.

🍜 Turning real-economy signals into testable alpha factors — K-Food alternative data and Revenue Dip Lab backtests, with point-in-time data, placebo tests and bias audits.

A hands-on Microsoft Qlib course in Chinese with 10 lessons and 5 runnable labs, covering data, Alpha158, LightGBM, portfolio strategy, backtesting, and rolling training.一个面向中文学习者的 Microsoft Qlib 实战课程：10 节 Lesson + 5 个可运行 Lab，覆盖数据准备、Alpha158、LightGBM、组合策略、回测和 Rolling。

A java stock trading algorithm backtester for users of Alpaca.markets and Polygon.io

strategy backtesting framework

SimpleBacktestLib is a C# library for backtesting trading strategies. It offers basic functions to simulate strategy performance and can be integrated into other C# projects.

A Python implementation of Walk Forward Optimization (WFO) for trading strategy backtesting with Bayesian Optimization

Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"