COVID-19 containment measures and stock market returns: An international spatial econometrics investigation

Alexakis, Christos; Eleftheriou, Konstantinos; Patsoulis, Patroklos

doi:10.1016/j.jbef.2020.100428

Cited by 62 publications

(47 citation statements)

References 18 publications

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“…Our analysis is related to a growing literature that establishes a link between the COVID-19 pandemic and increased volatility and uncertainty in financial markets (Akhtaruzzaman et al 2020;Alexakis et al 2021;Bouri et al 2020;Fernandez-Perez et al 2020;Goodell 2020;Sharif et al 2020;Haldar and Sethi 2020;Milcheva 2021;Ozkan 2021;Salisu et al 2021;Scherf et al 2021). The general theme in this emerging strand of the literature is that the pandemic has led to increased uncertainty regarding economic fundamentals, which in turn has led to a significant dip in financial markets driven by the greater risk premium required on risky assets.…”

Section: Introductionmentioning

confidence: 90%

COVID-19 Pandemic and Investor Herding in International Stock Markets

Bouri

Demirer

Gupta

et al. 2021

Risks

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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.

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Section: Introductionmentioning

confidence: 90%

COVID-19 Pandemic and Investor Herding in International Stock Markets

Bouri

Demirer

Gupta

et al. 2021

Risks

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“…See Elhorst [11] for an introduction to such models. We also cite the works by Zhang et al [48] and Alexakis et al [1] who utilized the concept of spatial dynamic panel data models in other COVID-19 related studies. Fourth, we implement a spatio-temporal model via integrated nested Laplace approximation (INLA).…”

Section: Model Implementation and Evaluationmentioning

confidence: 99%

A spatio-temporal statistical model to analyze COVID-19 spread in the USA

Rawat

Deb

2021

Journal of Applied Statistics

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Coronavirus pandemic has affected the whole world extensively and it is of immense importance to understand how the disease is spreading. In this work, we provide evidence of spatial dependence in the pandemic data and accordingly develop a new statistical technique that captures the spatio-temporal dependence pattern of the COVID-19 spread appropriately. The proposed model uses a separable Gaussian spatio-temporal process, in conjunction with an additive mean structure and a random error process. The model is implemented through a Bayesian framework, thereby providing a computational advantage over the classical way. We use state-level data from the United States of America in this study. We show that a quadratic trend pattern is most appropriate in this context. Interestingly, the population is found not to affect the numbers significantly, whereas the number of deaths in the previous week positively affects the spread of the disease. Residual diagnostics establish that the model is adequate enough to understand the spatio-temporal dependence pattern in the data. It is also shown to have superior predictive power than other spatial and temporal models. In fact, we show that the proposed approach can predict well for both short term (1 week) and long term (up to three months).

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“…With these features, Covid-19 has been felt in financial markets where economic distortions can be observed in a short time. There is a growing literature that examines the impact of the Covid-19 outbreak on stock market returns or volatility by country groups or countries (Baig et al, 2021;Ali et al, 2020;Zhang et al, 2020;Topcu and Gulal, 2020;Al-Awadhi et al, 2020;Alexakis et al, 2021;Haroon and Rivzi, 2020;Salisu et al, 2020). Despite of increasing interest on this issue, there is few studies analyzed emerging markets (Topcu and Gulal, 2020;Haroon and Rivzi, 2020;Salisu et al, 2020).…”

Section: Yöntemmentioning

confidence: 99%

Impacts of Global and Local Covid-19 Cases on Emerging Stock Markets

Yücel

Fikirli²,

Şahin³

2021

Mehmet Akif Ersoy Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi

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In this study, we examine the both local and global Covid-19 deaths and confirmed cases impact on stock markets return. We use the daily data from 26 countries, which are classified as emerging financial markets. According to the findings, a decrease in emerging stock market returns is not only due to local confirmed cases, but also from global confirmed cases. Our analysis also suggests that while an increase in total confirmed cases within the local variables leads to more decrease, total deaths within the global variables cause more decline in returns. When we consider the change in the stock market returns brought about by both local and global level confirmed cases rates and death rates increase, all global level variables (new confirmed cases, total confirmed deaths, new confirmed cases) except total confirmed cases lead to more decline. In other words, even if the countries control the covid-19 locally, the negative global impact on the stock market will continue.

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COVID-19 containment measures and stock market returns: An international spatial econometrics investigation

Cited by 62 publications

References 18 publications

COVID-19 Pandemic and Investor Herding in International Stock Markets

COVID-19 Pandemic and Investor Herding in International Stock Markets

A spatio-temporal statistical model to analyze COVID-19 spread in the USA

Impacts of Global and Local Covid-19 Cases on Emerging Stock Markets

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