Financial Economist & Policy Adviser, Research Department, Federal Reserve Bank of Atlanta

[Disclaimer: I solely maintain this website; the views expressed here are my own and are not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System]

My Google Scholar page is available here

New working paper: Improving Hedge Fund Return Prediction: Dealing with Missing Data via Deep Learning, with Ilias Filippou, Ioannis Psaradellis, and Lazaros Zografopoulos [presented at the 2025 Alpine Finance Summit]

Revised working paper: Sparse Macro-Finance Factors, with Guofu Zhou [Sparse Macro-Finance Factors website with data/code/updates]

Revised working paper: The Anatomy of Machine Learning-Based Portfolio Performance, with Philippe Goulet Coulombe, Erik Christian Montes Schütte, and Sander Schwenk-Nebbe [subject of Machine Learning & Quant Finance blog post by Derek Snow]

Revised working paper: Going Supranational: Anomaly-Market Links and New Dimensions of Market Efficiency, with Xi Dong, Yan Li, Yanran Li, and Guofu Zhou

Revised working paper: Economic Fundamentals and Short-Run Exchange Rate Prediction: A Machine-Learning Perspective, with Ilias Filippou, Mark Taylor, and Guofu Zhou [revise and resubmit to the Journal of Financial and Quantitative Analysis]

Revised working paper: The Anatomy of Out-of-Sample Forecasting Accuracy: A Shapley-Based Approach, with Daniel Borup, Philippe Goulet Coulombe, Erik Christian Montes Schütte, and Sander Schwenk-Nebbe [Python package anatomy]

New: Cross-Sectional Expected Returns: New Fama-MacBeth Regressions in the Era of Machine Learning, with Yufeng Han, Ai He, and Guofu Zhou, Review of Finance, 2024, 28(6), 1807–1831 [R code to compute/evaluate new E-LASSO forecast]