Fama-French models, idiosyncratic volatility, event study
Codes to clean data and construct variables for empirical finance.
An introduction to database and data management in empirical finance
An introduction to popular databases in empirical finance research.
A toolkit for asset pricing research
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.
A Python tool for extracting stock repurchase program data from SEC 10-Q and 10-K filings
End-to-End Python implementation of Mo et al.'s (2025) ACT-Tensor methodology; a tensor completion framework for financial dataset imputation. Implements cluster-based CP decomposition, HOSVD factor extraction, temporal smoothing (CMA/EMA/Kalman), and downstream asset pricing evaluation. Transforms sparse data into dense machine readable data.
📈 Forecast daily log-returns of the Dow Jones Industrial Average using an Automated Machine Learning pipeline that combines economic data and computational techniques.
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