Abstract

The aim of this study is to understand the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets. Utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, we examine the association between pandemic-induced market uncertainty and herding behavior in a set of 49 global stock markets. More specifically, we study the pattern of cross-sectional market behavior and examine whether the pandemic-induced uncertainty drives directional similarity across the global stock markets that cannot be explained by the standard asset pricing models. Utilizing a time-varying variation of the static herding model, we first identify periods during which herding is detected. We then employ probit models to examine the possible association between pandemic-induced uncertainty and the formation of herding. Our findings show a strong association between herd formation in stock markets and COVID-19 induced market uncertainty. The herding effect of COVID-19 induced market uncertainty is particularly strong for emerging stock markets as well as European PIIGS stock markets that include some of the hardest hit economies in Europe by the pandemic. The findings establish a direct link between the recent pandemic and herd formation among market participants in global financial markets. Considering the evidence that herding behavior can drive security prices away from equilibrium values supported by fundamentals and further contribute to price fluctuations in financial markets, our findings have significant implications for policy makers and investors in their efforts to monitor investor sentiment and mitigate mis-valuations that might occur as a result. Furthermore, the evidence on the behavioral pattern of stock investors in relation to infectious diseases uncertainty can be useful in studying price discovery in stock markets and might help market participants in forming hedging strategies to mitigate downside risk in their investment portfolios.

Highlights

  • Given that the recent COVID-19 pandemic has triggered a massive spike in uncertainty, quickly transitioning from a healthcare crisis into an economic one, this paper examines the role of the pandemic as a driver of investor herding in international stock markets by utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, recently developed by Baker et al (2020)

  • It can be argued that the finding of anti-herding in the full sample is driven by the heterogeneity in how global financial markets responded to the pandemic as such heterogeneity in global markets would lead to greater dispersion in the cross-sectional behavior of global returns

  • This study examines the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets by utilizing the recently developed newspaperbased index of Baker et al (2020), which tracks equity market volatility (EMV), in particular the movements in the Chicago Board Options Exchange (CBOE)’s Volatility Index (VIX), due to infectious diseases

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Summary

Introduction

Irrespective of the nature of such behavior among investors, rational or otherwise, the literature generally suggests that herding is more prevalent during periods of market stress or heightened uncertainty. A large number of studies have examined the presence of herding behavior in financial markets from different angles and using a wide range of samples (e.g., see Uwilingiye et al 2019 for a recent review), the literature has not yet examined the role of the recent COVID-19 pandemic in this context as a driver of herding behavior among market participants. Given that the recent COVID-19 pandemic has triggered a massive spike in uncertainty, quickly transitioning from a healthcare crisis into an economic one, this paper examines the role of the pandemic as a driver of investor herding in international stock markets by utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, recently developed by Baker et al (2020)

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