A complete toolkit for quantitative research and development of options trading strategies.

Nautilus_Trader_Jerry_fall_2023 is a customized verision of Nautilus trader by Zhuoran "Jerry" Li on Fall 2023

Exhaustive research on Polymarket prediction market inefficiencies — past exploits, academic foundations, live mispricings, trading strategies, and future alpha. 100+ sources across EN/KR/CN.

9 天的散戶量化失敗記錄 — 從 +211% 年化到認輸買 0050 的誠實報告

Cross-sectional Transformer and FFN for stock return prediction and alpha generation. Implements GKX (2020) NN5 replication and MSRR loss (Kelly et al. 2025) for direct portfolio Sharpe optimization. Avg SDF Sharpe 2.05, significant alpha (t=5.34) unexplained by FF5+Momentum.

Fail-closed Codex/Claude Code skill for crypto quant alpha research - Stage 0, falsification, provider concordance, promotion gates

A PyTorch research pipeline for cross-sectional stock return forecasting with grouped factors and stock-wise attention.

A modular Python framework for researching and backtesting multi-factor equity strategies using classical factors (Value, Momentum, Size), Fama–MacBeth regressions, IC/IR analysis, and long–short portfolio evaluation.

Bias-aware, reproducible daily-frequency multi-factor alpha research platform with PIT controls, segmented IC validation, and institutional robustness workflow.

World Quant 101 alphas的计算和策略化

* Calculates technical and custom alpha factors * Trains ML models to predict short-term returns * Evaluates predictive power (IC, precision, Sharpe ratio) * Visualises insights

Transformer-based HFT alpha research framework for LOB prediction, symbolic factor mining, and signal ranking

systematic trading strategies developed and validated using walk-forward analysis. The code is modular and structured for production backtesting.

Short Term Alpha Model

Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.

异步事件驱动/量化交易/做市系统/策略研究/策略回测

A leakage-controlled research framework for evaluating structured and semantic news signals in time-series asset return prediction using walk-forward validation.

Automated paper-to-backtest replication engine for quantitative finance signals. LLM-powered. Open methodology.

Institutional reference loops for agentic alpha research, prediction-market market making, replay, TCA, and risk gates on SimpleFunctions data.

Document a quantitative trading project that compares custom machine learning strategies against a simple 0050 buy and hold approach using backtested data.