Categorical Factors for Asset Pricing

25 Pages Posted: 30 Aug 2024

See all articles by Yu Zhao

Yu Zhao

Nanjing University of Finance and Economics

Sen Lin

University of Houston

Ao Kong

Nanjing University of Finance and Economics

Abstract

Linear models have traditionally been favored for their interpretability in low-dimensional asset pricing problems. However, in today's high-dimensional context, non-linear models, especially machine learning algorithms, often surpass linear regression models in predictive power, albeit at the cost of interpretability due to their inherent black-box nature. This paper introduces and tests a new kind of factor, categorical factors, for asset pricing. A large number of firm characteristics are divided into several groups based on their financial nature and then a categorical factor for each group is extracted using certain feature selection techniques. Based on the data from the US stock market, we demonstrate that these categorical factors outperform raw firm characteristics as predictors for asset pricing, significantly improving the accuracy of linear models while maintaining the performance of machine learning algorithms. Crucially, the best pricing performance is achieved when categorical factors are extracted using non-linear feature selection techniques and then applied in linear models to predict stock returns. This underscores the potential of using categorical factors to integrates the strengths of both linear and non-linear models, thereby enhancing both the interpretability and predictive accuracy of asset pricing models. Moreover, our findings indicate that the categorical factors are not only highly significant from both pricing and investment perspectives but also exhibit low correlations among themselves, indicating that they capture a broad spectrum of firm characteristics. Finally, we observe a temporal decline in the predictive power of these categorical factors, suggesting an increase in market efficiency within the US stock market.

Keywords: Asset pricing, Machine Learning, Feature selection, Categorical factor, Interpretability

Suggested Citation

Zhao, Yu and Lin, Sen and Kong, Ao, Categorical Factors for Asset Pricing. Available at SSRN: https://ssrn.com/abstract=4941835 or http://dx.doi.org/10.2139/ssrn.4941835

Yu Zhao

Nanjing University of Finance and Economics ( email )

Nanjing
China

Sen Lin

University of Houston ( email )

4800 Calhoun Road
Houston, TX 77204
United States

Ao Kong (Contact Author)

Nanjing University of Finance and Economics ( email )

Nanjing
China

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