A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy

TL;DR

This paper introduces RIC-NN, a deep learning framework for stock return prediction that leverages nonlinear multi-factor analysis, rank IC stopping criteria, and transfer learning across regions, achieving superior long-term investment performance.

Contribution

The paper presents a novel deep learning framework, RIC-NN, that improves stock return prediction through innovative multi-factor modeling, stopping criteria, and transfer learning, outperforming existing methods.

Findings

RIC-NN outperforms standard machine learning models.

RIC-NN surpasses average returns of major equity funds.

The framework maintains long-term investment consistency.

Abstract

Stock return predictability is an important research theme as it reflects our economic and social organization, and significant efforts are made to explain the dynamism therein. Statistics of strong explanative power, called "factor" have been proposed to summarize the essence of predictive stock returns. Although machine learning methods are increasingly popular in stock return prediction, an inference of the stock returns is highly elusive, and still most investors, if partly, rely on their intuition to build a better decision making. The challenge here is to make an investment strategy that is consistent over a reasonably long period, with the minimum human decision on the entire process. To this end, we propose a new stock return prediction framework that we call Ranked Information Coefficient Neural Network (RIC-NN). RIC-NN is a deep learning approach and includes the following three novel ideas: (1) nonlinear multi-factor approach, (2) stopping criteria with ranked information coefficient (rank IC), and (3) deep transfer learning among multiple regions. Experimental comparison with the stocks in the Morgan Stanley Capital International (MSCI) indices shows that RIC-NN outperforms not only off-the-shelf machine learning methods but also the average return of major equity investment funds in the last fourteen years.