The Role of Human Capital in Explaining Asset Return Dynamics in the Indian Stock Market During the COVID Era

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the com-mon assertion that higher risk tends to yield higher returns, this study empirically exam-ines the augmented human capital six-factor model’s performance on thirty-two portfoli-os of non-financial firms sorted by size, value, profitability, investment, and labor income growth in the Indian market over the period July 2010 to June 2023. Moreover, the current study extends the Fama and French five-factor model by incorporating human capital proxy by labor income growth as an additional factor, thereby proposing an augmented six-factor asset pricing model. The Fama and MacBeth (1973) two-step estimation meth-odology is employed for the empirical analysis. The results reveal that small-cap portfoli-os yield significantly higher returns than large-size portfolios. Moreover, all six factors significantly explain the time-series variation in excess portfolio returns. Findings reveal that the Indian stock market experienced heightened volatility during the COVID-19 pan-demic, leading to a decline in the six-factor model’s efficiency in explaining returns. Fur-thermore, Gibbons, Ross, and Shanken (GRS) test results reveal mispricing of portfolio re-turns during COVID-19, with a stronger rejection of portfolio efficiency across models. However, the HC6FM consistently shows lower pricing errors and better performance, specifically during and after the pandemic era. Overall, the results offer important insights for policymakers, investors, and portfolio managers in optimizing portfolio selection, par-ticularly during periods of heightened market uncertainty.