Forecasting relative returns for S&P 500 stocks using machine learning

Abstract Forecasting changes in stock prices is extremely challenging given that numerous factors cause these prices to fluctuate. The random walk hypothesis and efficient market hypothesis essentially state that it is not possible to systematically, reliably predict future stock prices or forecast...

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Bibliographic Details

Published in:	Financial Innovation
Main Authors:	Htet Htet Htun, Michael Biehl, Nicolai Petkov
Format:	Article
Language:	English
Published:	SpringerOpen 2024-04-01
Subjects:	Stock returns prediction Relative returns Classification Random forest Support vector machine Long short-term memory
Online Access:	https://doi.org/10.1186/s40854-024-00644-0