Behavioral-related firm characteristics, risks and determinants of stock returns

Purpose: This paper aims to investigate a relatively new anomaly of investment growth and revisits well-known anomalies of size and value. It aims to answer two main research questions. First, can covariance risks (i.e. factor loadings) be excluded from being determining variables that drive return premiums and explain stock returns? Second, from a behavioral finance standpoint, the authors examine whether using firm characteristics is a more practical and accessible approach and also meets the necessary and sufficient conditions to analyze stock returns. Design/methodology/approach: The authors create the investment-growth-based factor (LMH) which is defined as the return difference between low and high investment growth portfolios. The authors then incorporate the LMH factor along with other characteristic-based factors and their loadings into characteristic-balanced portfolio and three-factor model tests. Findings: The authors find that covariance risks on investment growth, size and value are not necessary as determining variables. Instead, they find that behavioral-related firm characteristics of investment growth, size and value are necessary and sufficient as determinants of return premiums and stock returns. Practical implications: The results have practical and useful implications for investors in their stock portfolio analysis and selection because firm characteristics are relatively more available than covariance risks that need estimation and typically contain measurement errors. Originality/value: The paper has practical value to investors in their stock portfolio analysis and selection. Methodologically, in contrast to prior studies that do not directly use the investment growth to control for portfolio characteristics, the use of the newly created LMH factor and its loadings allows us to directly and properly test if the investment growth anomaly is related to the investment growth characteristic that is hypothesized to drive return premiums and determine stock returns from behavioral finance perspectives.