The Macroeconomy and the Cross-Section of International Equity Index Returns: A Machine Learning Approach

62 Pages Posted: 13 Nov 2019

See all articles by Andreea Victoria Popescu

Andreea Victoria Popescu

Tilburg University - School of Economics and Management

Date Written: October 2019

Abstract

The paper evaluates the out-of-sample predictive ability of machine learning methods in the cross-section of international equity index returns using both firm fundamentals and macroeconomic predictors. The study performs a horserace between classical forecasting methods and the machine learning repertoire, including principal component analysis, partial least squares, and neural networks. Macroeconomic signals seem to substantially improve out-of-sample performance, especially when non-linear features are incorporated via neural networks.

Keywords: Asset Pricing, Equity Indices, Return Forecasting, Machine Learning, Neural Networks, Macroeconomic predictability

JEL Classification: C21, C45, C58, C38, G12

Suggested Citation

Popescu, Andreea Victoria, The Macroeconomy and the Cross-Section of International Equity Index Returns: A Machine Learning Approach (October 2019). Available at SSRN: https://ssrn.com/abstract=3480042 or http://dx.doi.org/10.2139/ssrn.3480042

Andreea Victoria Popescu (Contact Author)

Tilburg University - School of Economics and Management ( email )

P.O. Box 90153
Tilburg, 5000 LE
Netherlands

Register to save articles to
your library

Register

Paper statistics

Downloads
53
Abstract Views
228
rank
389,790
PlumX Metrics