Alpha Go Everywhere: Machine Learning and International Stock Returns

78 Pages Posted: 5 Dec 2019 Last revised: 26 Jan 2024

See all articles by Darwin Choi

Darwin Choi

The Chinese University of Hong Kong (CUHK) - CUHK Business School

Wenxi Jiang

CUHK Business School, The Chinese University of Hong Kong

Chao Zhang

University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance

Date Written: January 25, 2024

Abstract

We apply machine learning techniques to predict international stock returns using firm characteristics. Market-specific features are important, as neural network models (NNs) achieve stronger results when they are trained in each market separately than in a global model trained with U.S. data. NNs outperform linear models in predicting stock return rankings and forming profitable portfolios. In contrast, regression trees underperform linear models when the number of observations is low. We also show that adding foreign variables constructed from U.S. firm characteristics further enhances the return predictability of market-specific NNs, consistent with the notion that the markets are partially integrated.

Keywords: International Asset Pricing, Cross-section of Stock Returns, Market Integration, Neural Networks, Regression Trees

JEL Classification: C52, G10, G12, G15

Suggested Citation

Choi, Darwin and Jiang, Wenxi and Zhang, Chao, Alpha Go Everywhere: Machine Learning and International Stock Returns (January 25, 2024). Available at SSRN: https://ssrn.com/abstract=3489679 or http://dx.doi.org/10.2139/ssrn.3489679

Darwin Choi (Contact Author)

The Chinese University of Hong Kong (CUHK) - CUHK Business School ( email )

Cheng Yu Tung Building
12 Chak Cheung Street
Shatin, N.T.
Hong Kong

Wenxi Jiang

CUHK Business School, The Chinese University of Hong Kong ( email )

Room 1210, Cheng Yu Tung Building
Chinese University of Hong Kong
Shatin, NT 06520
Hong Kong

HOME PAGE: http://https://sites.google.com/site/jiangwenxi/

Chao Zhang

University of Oxford ( email )

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

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