How fears index and liquidity affect returns of ivol puzzle before and during the Covid-19 pandemic

Abstract

This study examines the impacts of investor sentiment and liquidity on the idiosyncratic volatility (IVOL) anomaly returns in Vietnam before and during the COVID-19. We construct an internet search-based measure of sentiment (FEARS) from the Google Trends Search Volume Index of Vietnam’s financial and economic search terms from December 2010 to December 2020. We employ Two-Stage Least Squares (2SLS) regressions and univariate portfolio testing to examine the existence of IVOL anomaly in Vietnam after controlling for FEARS sentiment index and liquidity proxies. Our findings document the persistence of the IVOL anomaly in the Vietnam stock market before the pandemic. However, the IVOL anomaly disappears during the pandemic. In addition, increasing investor fear sentiment reduces stock returns during the pandemic. Our robustness tests indicate that the IVOL anomaly persists in the high FEARS, low FEARS, and high turnover subsample before the pandemic. Our results contribute new evidence of how the FEARS index and liquidity help explain the IVOL puzzle before and during the pandemic. Our findings align with the trade-off theory, the efficient market theory, the attention-driven theory, and prior literature.