Welcome to Dave Rapach’s Website
[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]
[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]
Revised working paper: Economic Fundamentals and Short-Run Exchange Rate Prediction: A Machine-Learning Perspective, with Ilias Filippou, Mark Taylor, and Guofu Zhou [resubmitted to the Journal of International Economics]
Revised working paper: Economic Fundamentals and Short-Run Exchange Rate Prediction: A Machine-Learning Perspective, with Ilias Filippou, Mark Taylor, and Guofu Zhou [resubmitted to the Journal of International Economics]
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]
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]
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]
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 | slides for CEMFI Workshop on Big Data in Asset Management]
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 | slides for CEMFI Workshop on Big Data in Asset Management]
New Atlanta Fed Policy Hub Paper: Is the Last Mile More Arduous? [subject of Bloomberg article by Steve Matthews] | discussed in Bloomberg column by Daniel Moss | discussed in Sunday Times column by Cormac Lucy | discussed in BNP Paribas Economic Research Editorial by William De Vijlder | mentioned in Financial Times column by Chris Giles | discussed in Juggling Dynamite blog post by Danielle Park]
New Atlanta Fed Policy Hub Paper: Is the Last Mile More Arduous? [subject of Bloomberg article by Steve Matthews] | discussed in Bloomberg column by Daniel Moss | discussed in Sunday Times column by Cormac Lucy | discussed in BNP Paribas Economic Research Editorial by William De Vijlder | mentioned in Financial Times column by Chris Giles | discussed in Juggling Dynamite blog post by Danielle Park]
Revised working paper: Cryptocurrency Return Predictability: A Machine-Learning Analysis, with Ilias Filippou and Christoffer Thimsen
Revised working paper: Cryptocurrency Return Predictability: A Machine-Learning Analysis, with Ilias Filippou and Christoffer Thimsen
ADDRESS
Research Department
Federal Reserve Bank of Atlanta
1000 Peachtree Street NE
Atlanta, GA 30309
CONTACT
dave.rapach@gmail.com
david.rapach@atl.frb.org