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
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.
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.
systematic trading strategies developed and validated using walk-forward analysis. The code is modular and structured for production backtesting.
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
异步事件驱动/量化交易/做市系统/策略研究/策略回测
Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.
A leakage-controlled research framework for evaluating structured and semantic news signals in time-series asset return prediction using walk-forward validation.
Automate investment research with AI that searches sources, writes reports, scores gaps, and refines answers on a loop
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