Coronavirus (Covid-19) outbreak, investor sentiment, and medical portfolio: Evidence from China, Hong Kong, Korea, Japan, and U.S

Sun, Yunpeng; Bao, Qun; Lu, Zhou

doi:10.1016/j.pacfin.2020.101463

Cited by 92 publications

(93 citation statements)

References 45 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%

“…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: Introductionsupporting

confidence: 77%

“…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%

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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: Introductionsupporting

confidence: 77%

Section: Agreeableness (A)mentioning

confidence: 99%

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What Drives Excess Trading during the COVID-19 Pandemic?

Chin

2021

AJBA

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“…The Covid-19 pandemic struck the global landscape sometime around later November to early December 2019. However, the WHO issued a series of guidelines for the world leaders regarding the safeguards against the spread of the coronavirus pandemic on 10 January 2020, which has been taken as a guideline for the event declaration ( 20 ). The impact of the global pandemic can be seen through a slump in the economic activity worldwide through the nationwide shutdowns enforced by the governments and the policymakers ( 21 ).…”

Section: Methodsmentioning

confidence: 99%

An Evaluation of the Impact of Monetary Easing Policies in Times of a Pandemic

Sun

Chen

2021

Front. Public Health

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This article tests five major economies of the world, United Kingdom, Japan, Brazil, Chin and lastly, India, for the changes in the monetary policy decisions that have been implemented following the Covid-19 outbreak. The assessment was undertaken in the form of an event study analysis, further substantiated with a regression analysis conducted for exploring the significance of CPI and real GDP in predicting the policy interest rates in the economy. The results of the event study analysis presented that the abnormal changes in the interest rates were statistically significant in the case of the United Kingdom, Brazil, and China, while the abnormal changes were found to be statistically insignificant in the case of India and Japan.

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“…Investor sentiment was studied also in connection with mass-media influences (Sun et al 2021). Aguilar et al (2021) proposed a novel newspaper-based sentiment indicator in order to monitor real-time changes within the Spanish economy.…”

Section: Literature Reviewmentioning

confidence: 99%

Empirical Evidence Regarding the Impact of Economic Growth and Inflation on Economic Sentiment and Household Consumption

Bătrâncea

2021

JRFM

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The dynamics of the interconnected global market and consumption behavior has recently changed considerably. Using a sample of 28 nations within the European Union, the study examined the degree to which economic growth and inflation impacted economic sentiment and household consumption during the time frame of December 2019 up to October 2020. The results estimated via panel generalized method of moments and panel least squares (with cross-section weights, time fixed effects) showed that economic sentiment and household consumption were significantly shaped by the proxies of economic growth and inflation. Moreover, in the case of economic sentiment, the negative impact of inflation was much stronger than the positive impact of economic growth. The reverse applied in the case of household consumption. The study draws policy implications regarding the strategies that public authorities, companies, and individual consumers could apply for stimulating national economies amid challenging times.

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Coronavirus (Covid-19) outbreak, investor sentiment, and medical portfolio: Evidence from China, Hong Kong, Korea, Japan, and U.S

Cited by 92 publications

References 45 publications

What Drives Excess Trading during the COVID-19 Pandemic?

What Drives Excess Trading during the COVID-19 Pandemic?

An Evaluation of the Impact of Monetary Easing Policies in Times of a Pandemic

Empirical Evidence Regarding the Impact of Economic Growth and Inflation on Economic Sentiment and Household Consumption

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