New Measures of the COVID-19 Pandemic: A New Time-Series Dataset

Narayan, Paresh Kumar; Iyke, Bernard Njindan; Sharma, Susan Sunila

doi:10.46557/001c.23491

Cited by 53 publications

(101 citation statements)

References 13 publications

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“…They documented a possible overreaction of stock markets to the pandemic and market corrections over time. Narayan et al ( 2021a ) examined the impact of government interventions in response to the COVID-19 pandemic, such as lockdowns, stimulus packages, and travel bans, on stock markets in G7 countries. The empirical results show that lockdowns, stimulus packages, and travel bans positively impact stock markets and that the impact of lockdowns is greater than that of the other responses.…”

Section: Literature Reviewmentioning

confidence: 99%

Investor sentiments and stock markets during the COVID-19 pandemic

et al. 2022

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This study examines 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. We proxy for negative and positive investor sentiments using the Google Search Volume Index for terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significant relationships between positive and negative investor sentiments and stock market returns and volatility. Specifically, an increase in positive investor sentiment leads to an increase in stock returns while negative investor sentiment decreases stock returns at lower quantiles. The effect of investor sentiment on volatility is consistent across the distribution: negative sentiment increases volatility, whereas positive sentiment reduces volatility. These results are robust as they are corroborated by Granger causality tests and a PVAR model. The findings may have portfolio implications as they indicate that proxies for positive and negative investor sentiments seem to be good predictors of stock returns and volatility during the pandemic.

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Section: Literature Reviewmentioning

confidence: 99%

Investor sentiments and stock markets during the COVID-19 pandemic

et al. 2022

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“…Daily data are obtained for the period from January 2, 2020, to November 8, 2020. This period is based on the availability of COVID-19 aggregate index (COVI) data of Narayan et al (2021).…”

Section: Methodsmentioning

confidence: 99%

“…There is a gap in the literature examining the dynamic connectedness between crude oil, clean energy stocks, technology stocks, and COVID-19 sentiment during the peak and post-peak COVID-19 periods. This paper applies a new dataset for the news-based COVID-19 uncertainty index developed by Narayan et al (2021). It provides fresh insights into the hedging potential of clean energy stocks during the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Nexus Between COVID-19 Sentiment, Clean Energy Stocks, Technology Stocks, and Oil Prices: Global Evidence

Akram

Haider

2022

Energy RESEARCH LETTERS

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This study examines time-varying correlations between clean energy stocks, technology stocks, oil prices, and COVID-19 sentiment. The results confirm a weaker positive relation between oil prices and clean energy stocks. Correlations between COVID-19 sentiment and clean energy and technology stocks vary from low and negative during the peak period to positive and relatively high during the post-peak period. The results show the relatively better position of clean and technology stocks during the post-peak period.

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“…There are three groups of news indices with different periods considered in this document—the first group of indices [ 49 ] from 11 February 2020 to 29 October 2021 (448 observations); the second group of indices [ 20 ] from 3 March 2020 to 27 January 2022 (497 observations); the third group of indices [ 21 ] from 1 January 2020 to 28 April 21 (345 observations). To consider the three different periods, the EMV-ID index and the stock markets were matched according to the specific periods.…”

Section: Methodsmentioning

confidence: 99%

“…This index combines two indices, an index that has global news related to COVID-19 (ciustk.news) and the index of uncertainty due to global economic indicators (ciustk.mac), which contains information on the price of oil, gold, raw materials, exchange rates, and stock prices [ 20 ]. The last set of global news indices includes the aggregate index of COVID-19, medical index, travel index, uncertainty index, vaccine index, and COVID index [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Transfer Entropy Granger Causality between News Indices and Stock Markets in U.S. and Latin America during the COVID-19 Pandemic

Coronado

Martinez

Estrada

et al. 2022

Entropy

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The relationship between three different groups of COVID-19 news series and stock market volatility for several Latin American countries and the U.S. are analyzed. To confirm the relationship between these series, a maximal overlap discrete wavelet transform (MODWT) was applied to determine the specific periods wherein each pair of series is significantly correlated. To determine if the news series cause Latin American stock markets’ volatility, a one-sided Granger causality test based on transfer entropy (GC-TE) was applied. The results confirm that the U.S. and Latin American stock markets react differently to COVID-19 news. Some of the most statistically significant results were obtained from the reporting case index (RCI), A-COVID index, and uncertainty index, in that order, which are statistically significant for the majority of Latin American stock markets. Altogether, the results suggest these COVID-19 news indices could be used to forecast stock market volatility in the U.S. and Latin America

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New Measures of the COVID-19 Pandemic: A New Time-Series Dataset

Cited by 53 publications

References 13 publications

Investor sentiments and stock markets during the COVID-19 pandemic

Investor sentiments and stock markets during the COVID-19 pandemic

A Dynamic Nexus Between COVID-19 Sentiment, Clean Energy Stocks, Technology Stocks, and Oil Prices: Global Evidence

Transfer Entropy Granger Causality between News Indices and Stock Markets in U.S. and Latin America during the COVID-19 Pandemic

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