Journal ArticleDOI
Investor sentiment and government policy interventions: evidence from COVID-19 spread
Garima Goel,Saumya Ranjan Dash +1 more
TLDR
In this article, the authors investigated the role of government policy interventions on the early spread of novel coronavirus (COVID-19) on the investor sentiment and stock returns relationship.Abstract:
Purpose: This paper aims to investigate the moderating role of government policy interventions amid the early spread of novel coronavirus (COVID-19) (January–May 2020) on the investor sentiment and stock returns relationship. Design/methodology/approach: This paper uses panel data from a sample of 53 countries to examine the impact of investor sentiment, measured by the financial and economic attitudes revealed by the search (FEARS) index (Da et al., 2015) on the stock return. Findings: The moderating role of government policy response indices with the FEARS index on the global stock returns is further explored. This paper finds that government policy responses have a moderating role in the sentiment and stock returns relationship. The effect holds true even when countries are split based on five classifications, i.e. cultural distance, health standard, government effectiveness, social well-being and financial development. The results are robust to an alternative measure of pandemic search intensity, quantile regression and two measures of stock market activity, i.e. conditional volatility and exchange traded fund returns. Research limitations/implications: The sample period of this study encompasses the early spread phase (January–May 2020) of the novel COVID-19 spread. Originality/value: This paper provides some early evidence on whether the government policy interventions are helpful to mitigate the impact of investor sentiment on the stock market. The paper also helps to shed better insights on the role of different country characteristics for the sentiment and stock return relationship. © 2021, Emerald Publishing Limited.read more
Citations
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Journal ArticleDOI
Investor sentiments and stock markets during the COVID-19 pandemic
TL;DR: In this paper , the authors examined the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions.
Journal ArticleDOI
Investor sentiments and stock markets during the COVID-19 pandemic
TL;DR: In this article , the authors examined the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions.
Journal ArticleDOI
The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements
TL;DR: In this article , a time-frequency based wavelet approach comprising wavelet coherence and phase difference was used to measure pandemic uncertainty and its effect on stock market activity, while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index.
Journal ArticleDOI
The asymmetric effect of COVID-19 government interventions on global stock markets: New evidence from QARDL and threshold regression approaches
TL;DR: In this paper , the authors examined the effect of COVID-19 government interventions on global stock markets using a sample of 61 countries over the period of January 2020 to December 2021, applying Quantile ARDL (QARDL) and panel threshold regressions.
References
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Noise Trader Risk in Financial Markets
TL;DR: In this article, the authors present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns.
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Detecting influenza epidemics using search engine query data
Jeremy Ginsberg,Matthew H. Mohebbi,Rajan Patel,Lynnette Brammer,Mark S. Smolinski,Lawrence B. Brilliant +5 more
TL;DR: A method of analysing large numbers of Google search queries to track influenza-like illness in a population and accurately estimate the current level of weekly influenza activity in each region of the United States with a reporting lag of about one day is presented.
Posted Content
The Worldwide Governance Indicators: Methodology and Analytical Issues
TL;DR: The Worldwide Governance Indicators (WGI) project as mentioned in this paper is a collection of six dimensions of governance starting in 1996: Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption.
Journal ArticleDOI
The Worldwide Governance Indicators : Methodology and Analytical Issues
TL;DR: The Worldwide Governance Indicators (WGI) project as mentioned in this paper is a collection of six dimensions of governance starting in 1996: Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption.
Journal ArticleDOI
Financial markets under the global pandemic of COVID-19.
Dayong Zhang,Min Hu,Qiang Ji +2 more
TL;DR: The potential consequence of policy interventions, such as the US’ decision to implement a zero-percent interest rate and unlimited quantitative easing (QE), and how these policies may introduce further uncertainties into global financial markets are analyzed.
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