Author
Listed:
- Naveed Khan
- Mustafa Afeef
- Hassan Zada
Abstract
In the wake of recurring crises, traditional factor-based asset pricing models often fail to capture the return dynamics in emerging markets. Therefore, this study evaluates the performance of the augmented human-capital six-factor asset pricing model (HC6FM) in explaining the variability in excess portfolio returns in the Chinese equity market from July 2013 to June 2023. For empirical estimation, we employ the Fama and MacBeth two-step estimation procedure, and the findings demonstrate that the market premium exhibits a positive and significant relationship with excess portfolio returns. Furthermore, the results show that the size and value effects predominated before the Chinese stock market crash, but their influence diminished during the crisis. On the other hand, during the Chinese stock market crash, the profitability factor exhibits a negative and insignificant relationship with excess portfolio returns. Additionally, findings report a negative relationship between investment factor and excess portfolio returns. Moreover, the labor-based risk factor often highlights the pricing role of human capital during periods of heightened uncertainty. Furthermore, findings from the Gibbons-Ross-Shanken (GRS) test indicate that, during the Chinese stock market crash and the post-COVID-19 period, the HC6FM reports the lowest mean-absolute alphas, thereby demonstrating superior explanatory power over competing asset pricing models. Moreover, the results demonstrate that incorporating human capital significantly improves model accuracy during periods of market turmoil, offering valuable insights for both portfolio managers and regulatory bodies.
Suggested Citation
Naveed Khan & Mustafa Afeef & Hassan Zada, 2026.
"Does Human Capital Six-Factor Asset Pricing Model Explain the Variability in Asset Returns? A Lesson from the Normal and Crisis Periods in China,"
Chinese Economy, Taylor & Francis Journals, vol. 59(4), pages 319-346, July.
Handle:
RePEc:mes:chinec:v:59:y:2026:i:4:p:319-346
DOI: 10.1080/10971475.2025.2605836
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