Advertising, research and development, and capital market risk: higher risk firms versus lower risk firms

Abstract

This study examines how a firm's advertising and R&D affects the firm's β-risk and idiosyncratic risk, which are metrics of interest to both finance executives and senior management. Due to the existence of a non-normal and heteroscedasticity dataset, we use quantile regression to analyze the sample to understand the full behavior of our non-normally distributed datapoints. The evidence of this study shows that: (1) Advertising is significantly associated with lower β-risk for firms with lower, median and higher β-risk. (2) R&D significantly increases β-risk for firms with median and higher β-risk firms. (3) Advertising is significantly associated with lower idiosyncratic risk for firms with higher idiosyncratic risk. (4) R&D is significantly associated with higher idiosyncratic risk for firms with median and higher idiosyncratic risk. In summary, our evidence shows that both advertising and R&D have a stronger effect on firms with higher β- and idiosyncratic risk than on those with lower β- and idiosyncratic risk, respectively. Our findings are useful to help both management executives and investors. Firm managers can allocate limited resources more efficiently to reduce their firm risk; investors could exert their influence on firm's senior executives to make decisions that are beneficial to stock returns.

Keywords

• β-risk
• idiosyncratic risk
• advertising
• marketing
• R&D
• quantile regression