From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions

Kizys, Renatas; Tzouvanas, Panagiotis; Donadelli, Michael

doi:10.1016/j.irfa.2021.101663

Cited by 110 publications

(108 citation statements)

References 48 publications

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“…However, the results show that high A investors trade more when comparing the high frequency of trading and low frequency of trading. The findings are not consistent with past studies (Chang et al, 2020;Durand et al, 2013;Kizys et al, 2021;Shuai et al, 2014;Sun et al, 2021;Tauni et al, 2015Tauni et al, , 2017 based on model 1, where high A investors tend to herd and trade more compared with those who are not. The results are consistent for model 2 but not significant.…”

Section: Analysis and Discussioncontrasting

confidence: 99%

“…Numerous studies have found high A investors tend to trade more than low A investors (Durand et al, 2013;Tauni et al, 2015Tauni et al, , 2017. Recent studies have highlighted significant herding behaviours during the COVID-19 pandemic (Chang et al, 2020;Kizys et al, 2021;Sun et al, 2021). Thus, hypothesis 4 was developed as follows because high A individuals are more likely to herd.…”

Section: Agreeableness (A)mentioning

confidence: 99%

“…Smales (2021) used Google search volume (GSV) as a proxy for investor attention and found that rising investor attention is associated with larger volatility in the financial market of the G20 nations. Kizys et al (2021) adopted cross-sectional absolute deviation (CSAD) and the cross-sectional standard deviation (CSSD) as measures of investor herding behaviour showing significant herding behaviour among international investors during the COVID-19 pandemic. Herding behaviour during the COVID-19 pandemic is also being found in other studies in the context of the energy stock market (Chang et al, 2020) and medical stocks (Sun et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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What Drives Excess Trading during the COVID-19 Pandemic?

Chin

2021

AJBA

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Manuscript type: Research paperResearch aims: This study aims to examine the underlying psychological and sociological factors that drive excess trading in the Malaysian stock market during a global health crisis such as the COVID-19 pandemic. Design/Methodology/Approach: A self-administered online questionnaire was collected from 271 individual investors to examine the association between big-five personality traits and trading frequency. Demographic information and investment behaviours of investors were also included in the study. The multinomial logit regression model was used to test the research hypotheses. Research findings: Findings show that personality traits such as openness to experience and agreeableness have a significant influence on trading frequency. Demographic factors and investment behaviours such as gender, household income level, years of investment experience and type of investor all have a significant positive relationship with trading frequency. Theoretical contribution/Originality: This study contributes to the current investor behaviour literature in Malaysia, which remains to be very limited, especially during a global health crisis. The study indicates that personality traits, demographic, socio-economic factors, and investment behaviours affect the trading frequency of Malaysian. Practitioner/Policy implication: This study offers insights for financial institutions and individual investors on the type of personality traits, demographic, socio-economic factors, and investment behaviours that drive excess trading during a global health crisis. The findings provide important contributions to avoid serious mistakes in investment analysis and trading profitable investment strategies, thus improving individual and team performance. Research limitation/Implications: Some results are not significant and may be limited due to the small sample size used in this study. Future research could recruit more retail investors to confirm the significance level of those variables. Besides, the study can be conducted after the COVID-19 pandemic to explore whether there is any significant difference in the variables during and after the global health crisis.

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Section: Analysis and Discussioncontrasting

confidence: 99%

Section: Agreeableness (A)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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What Drives Excess Trading during the COVID-19 Pandemic?

Chin

2021

AJBA

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“…Evidence from literature shows that the COVID-19 effect on financial markets is devastating compared to other crises that spread in the past (Baker et al, 2020;Zhang et al, 2020). This research studies that look at the impact of a pandemic on the stock market include (Pavlyshenko, 2020;Topcu & Gulal, 2020;Umar, Mirza, et al, 2021), studies that examine volatility (Albulescu, 2021;Cheng & Yao, 2021;Su, Huang, et al, 2021;Su, Sun, et al, 2021), researchers analysing liquidity includes (Haroon & Rizvi, 2020;Su, Qin, Tao, Shao, et al, 2020;Zaremba et al, 2020) studies exploring herding include (Kizys et al, 2021), papers looking at the fund flows P astor and Vorsatz (2020) or financial projections are examined by Bretscher et al (2020), Gormsen and Koijen (2020) and Umar, Su, et al (2021).…”

Section: Pandemic and Financial Marketsmentioning

confidence: 99%

The impact of COVID-19 shocks on the volatility of stock markets in technologically advanced countries

Zhang

2021

Economic Research-Ekonomska Istraživanja

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This study examines the volatility of China and the most advanced countries of the world stock markets due to the pandemic of COVID-19 using the TGARCH model. This research study presents empirical support for the TGARCH specification for explaining the daily time dependence in the rate of information arrival to the market for stocks traded on China stock market. Using the sample containing closing stock market returns from 05 January 2015 to 04 April 2020 of sample countries, we found that through the COVID-19, there is no significant impact of returns volatility coming from advanced countries towards the China stock market. Further, results state that China has a significant impact on explaining the volatility of the most advanced countries of the world (Switzerland, Sweden, Netherlands, and the UK) except the U.S.A. during COVID-19. We found no significant impact of China stock market returns on the U.S.A.'s volatility, but there is a presence of leverage effect during COVID À19.

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“…with dynamic interactions between credit limits and asset prices, which turns out to be a transmission mechanism by which the effects of shocks persist, amplify and leak to other sectors. The authors also show that small, temporary shocks to technology or income distribution can generate large, persistent fluctuations in output and asset prices (Kiyotaki and Moore, 1997 [57]). More recently, Adrian and Shin (2008[58]) show that investment banks' leverage has been highly pro-cyclical and increased about threefold in the run-up to the crisis.…”

Section: Treatment Of the Banking Sector In Forecasting Modelsmentioning

confidence: 99%

Forecasting developing Asian economies during normal times and large external shocks: Approaches and challenges

Tanaka¹

2021

OECD Development Centre Working Papers

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This series of working papers is intended to disseminate the Development Centre's research findings rapidly among specialists in the field concerned. These papers are generally available in the original English or French, with a summary in the other language.OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors.This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to the OECD Development Centre,

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From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions

Cited by 110 publications

References 48 publications

What Drives Excess Trading during the COVID-19 Pandemic?

What Drives Excess Trading during the COVID-19 Pandemic?

The impact of COVID-19 shocks on the volatility of stock markets in technologically advanced countries

Forecasting developing Asian economies during normal times and large external shocks: Approaches and challenges

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