Fama-French models, idiosyncratic volatility, event study
Replication package for 'The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book.' Eight stylized facts on a pre-registered 600-market panel plus a methodological result: feed-inferred trade direction agrees with on-chain ground truth on ~59% of buckets vs ~80% Lee-Ready on equities.
Codes to clean data and construct variables for empirical finance.
An introduction to popular databases in empirical finance research.
An introduction to database and data management in empirical finance
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 toolkit for asset pricing research
ASSIP 2026 cohort - 8-week empirical-finance research program with Prof. Lei Gao (GMU). Textbook + Jupyter notebooks + MkDocs wiki + 5 capstone exemplars.
A Python tool for extracting stock repurchase program data from SEC 10-Q and 10-K filings
An end-to-end Automated ML pipeline for empirical asset pricing & DJI forecasting. Bridges econometric rigor with modern AI using H2O AutoML. Features include advanced preprocessing (Winsorization, ADF), statistical validation via the Diebold-Mariano test, and model explainability using SHAP values. Optimized for reproducible quantitative research.
Code and data for "When Volatility Masquerades as Fragility". Hourly DeFi liquidation panel and quantile local projections of ETH returns, 2021-2025.
A prose-first, multi-pass workflow for drafting and revising empirical finance manuscripts with AI agents.
Open and reproducible empirical research on cryptocurrency cross-sectional factors, asset-pricing evidence, and robust validation.
This project replicates the connected-firm momentum factor in Ali & Hirshleifer (2020), extends the framework to a quarterly frequency, and applies the same signal construction, portfolio sorts, and factor regressions to an updated 2016–2026 sample.
Replication of patent-based return predictability using rolling 5-year technology vectors, CRSP returns, Compustat controls, and Fama-MacBeth tests.
From-scratch replication of Loughran and McDonald (2011) — SEC 10-K sentiment analysis with the LM Master Dictionary, and Fama-MacBeth regressions on filing-period excess returns.
Code and reproducibility package for “What Does Deep Hedging Actually Learn? Delta Corrections, Regime Fragility, and Symbolic Distillation.”
Code and data for evaluating informed trading by U.S. Congress members. Employs Fama-French factor models and committee-level jurisdictional mapping to analyze abnormal returns.
Public release materials for CVE Case Study #3: Multi-Regime Observations Across Fifteen Digital Asset Windows.
Project Code of my Master Thesis: The Equity Duration Channel of ECB Monetary Policy Transmission
Add a description, image, and links to the empirical-finance topic page so that developers can more easily learn about it.
To associate your repository with the empirical-finance topic, visit your repo's landing page and select "manage topics."