arXiv Open Access 2023

Stock Price Predictability and the Business Cycle via Machine Learning

Li Rong Wang Hsuan Fu Xiuyi Fan
Lihat Sumber

Abstrak

We study the impacts of business cycles on machine learning (ML) predictions. Using the S&P 500 index, we find that ML models perform worse during most recessions, and the inclusion of recession history or the risk-free rate does not necessarily improve their performance. Investigating recessions where models perform well, we find that they exhibit lower market volatility than other recessions. This implies that the improved performance is not due to the merit of ML methods but rather factors such as effective monetary policies that stabilized the market. We recommend that ML practitioners evaluate their models during both recessions and expansions.

Topik & Kata Kunci

Penulis (3)

L

Li Rong Wang

H

Hsuan Fu

X

Xiuyi Fan

Format Sitasi

Wang, L.R., Fu, H., Fan, X. (2023). Stock Price Predictability and the Business Cycle via Machine Learning. https://arxiv.org/abs/2304.09937

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓