Pandemic-induced fear and stock market returns: Evidence from China

We construct a pandemic-induced fear (PIF) index to measure fear of the COVID-19 pandemic using Internet search volumes of the Chinese local search engine and empirically investigate the impact of fear of the pandemic on Chinese stock market returns. A reduced-bias estimation approach for multivariate regression is employed to address the issue of small-sample bias. We find that the PIF index has a negative and significant impact on cumulative stock market returns. The impact of PIF is persistent, which can be explained by mispricing from investors' excessive pessimism. We further reveal that the PIF index directly predicts stock market returns through noise trading. Investors' Internet search behaviors enhance the fear of the pandemic, and pandemic-induced fear determines future stock market returns, rather than the number of cases and deaths caused by the COVID-19 pandemic.

Commonality in BRICS stock markets' reaction to global economic policy uncertainty: Evidence from a panel GARCH model with cross sectional dependence

The rapid growth of BRICS has increasingly integrated their markets into the global economy. Thus, making their financial markets more vulnerable to external shocks. This study examines BRICS stock markets' response to global economic policy uncertainty using a panel GARCH model. The results show that global economic policy uncertainty significantly raises volatility with homogeneous response across the markets. The findings also suggests that COVID-19 has amplified the adverse impact of the uncertainties on prices and volatility. One major implication of the findings is that the BRICS can develop a joint policy for mitigating policy uncertainties spillovers. © 2023 Elsevier Inc.

Hedging effectiveness of cryptocurrencies in the European stock market

The aim of the paper is twofold: first, to examine the hedging effectiveness of cryptocurrencies and cryptocurrency portfolios for European equities in bearish and bullish market conditions, and second, to contrast cryptocurrencies with gold as a safe haven asset. To this end, daily data from 2018 to 2022 were employed in a linear and nonlinear Autoregressive Distributed Lag (ARDL) framework. The findings have significant implications for investors, financial intermediaries and regulators. © 2023 Elsevier B.V.

Heterogenous responses of stock markets to covid related news and sentiments: Evidence from the 1st year of pandemic

In this paper, we study the impact of news and sentiments related to covid-19 on United Kingdom (UK)'s stock returns from February 4, 2020 to December 7, 2020. Our results show that covid-19 daily cases exert a significant negative effect on stock returns whereas covid-19 daily deaths have a significant positive impact. These findings hold when covid-related news and sentiments indices are controlled with the 2nd wave data, and when the US policies and equity market volatilities from infectious diseases are used as controls. The magnitude of the effect of covid cases and deaths indicates that the pandemic is not very harmful to the UK stock market. © 2022 CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), a center for research and expertise on the world economy

Impact of COVID-19 and economic policy uncertainty on China's stock market returns: evidence from quantile-on-quantile and causality-in-quantiles approaches.

COVID-19 unexpectedly ensnared the entire world and wreaked havoc on global economic and financial systems. The stock market is sensitive to black swan events, and the COVID-19 disaster was no exception. Against this backdrop, this study explores the impact of COVID-19 and economic policy uncertainty (EPU) on Chinese stock markets' returns for the period spanning January 23, 2020 to August 04, 2021. The outcomes of the novel quantile-on-quantile regression analysis revealed that both COVID-19 and EPU had a significant negative impact on both Shanghai and Shenzhen stock market returns, while COVID-19 aggravated the level of economic uncertainty in both financial markets. The quantile causality approach of Troster et al. (2018) validates our main estimations. We conclude that COVID-19 and a high level of EPU enervated the returns of China's leading stock markets. Our study provides key insights to policymakers and market participants to determine the behavior of China's stock market returns vis-à-vis COVID-19 during the peak of the pandemic and beyond. Specifically, our findings apprise portfolio investors to augment their portfolio diversification fronts.

Time-varying effects of fuel prices on stock market returns during COVID-19 outbreak.

This article explores the impact of fuel price movements on the stock market return of 2020 during the COVID-19 disruptions. In doing so, a monthly data of seven selected stock market indices representing developed and emerging economies globally was used for analysis. The study used a time-varying parameter VAR model to examine a time-varying causal association between oil prices and stock market returns and a novel quantile-causality approach to capture the fluctuations of these markets under COVID-19's varying market conditions. The study further utilises the entropy transfer approach to capture the Granger-causal relationship in the presence of nonlinearities of the data series. The results indicate a high information flow from fuel prices to the FTSE-100, Pacific, and European stock indicies, but not the other way round. The results show that, for the FTSE-100 and the European region, there is a two-way information flow between equities and natural gas, and vice-versa. However, a one-way information flow was established from the stock market to the Pacific and emerging economies.

Reactive or Immune: Stock Market Behaviour During Subsequent Waves of the COVID-19 Pandemic

The COVID-19 pandemic, since its onset, has erupted in waves over the past two years. Previous studies investigated the initial impact of the outbreak on stock market returns. This study extends the investigation of the impact on stock market returns during subsequent waves of the pandemic. A panel data regression of stock market returns to covid variables during the three waves indicated that the initial fear of the disease did not persist through the later waves and the fear factor of the disease spread, deaths and lockdowns faded with every subsequent wave. Investors reacted differently to certain COVID variables. The daily count of total cases and daily deaths were the variables of interest for the first wave, whereas, for subsequent waves, the growth in daily new cases was the most prominent. The country-wise analysis over periods of waves of the pandemic revealed that investor behaviours varied among countries with no identifiable pattern indicating the significance of societal behaviours affecting investor decisions, especially during the crises.

Determining the return volatility of the Ghana stock exchange before and during the COVID-19 pandemic using the exponential GARCH model.

In this paper, we utilise daily stock returns for the Ghanaian equity market (GSE) to examine the influence of the COVID-19 pandemic on market volatility. We take return volatility from 2nd January, 2018, to 31st December, 2021, and split it into two periods-the pre-COVID-19 period and the COVID-19 period. Utilising the exponential GARCH (EGARCH) model, we discovered leverage effects in all observed periods. Additionally, the research indicates that the COVID-19 period experienced high volatility with a transient volatility persistence. Furthermore, during the COVID-19 pandemic, positive shocks had a more significant impact on the volatility of the GSE's returns than negative news of comparable magnitude.

Investor sentiments and stock markets during the COVID-19 pandemic.

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.

COVID-19 LED TO PRICE SLUMPS IN THE GERMAN STOCK MARKET. IS SENTIMENT APPLICABLE AS AN EXPLANATORY FACTOR?

Explaining and forecasting returns and other statistical moments of returns in the stock market have always been critical challenges. Recent studies postulate a relation between investor sentiment and future stock market returns. Supported by evidence from other countries, this study explores the statistical moments of stock returns in Germany and analyses to what extent an explanation can be found through investor sentiment. The recent COVID-19 induced market distortions provide an opportunity to investigate the suitability of predictive sentiment-based analyses. These are presented in this study and appear to be meaningful. The main concept behind the sentiment-based return explanation is built on the assumption that stock returns are linked to investor psychology. This theory often serves as an explanation for market movements that cannot be explained by fundamental data which are directly linked to stocks. However, the extraction of various sentiment proxies for further analysis in statistical models remains challenging. Problems occur because sentiment proxies do not have a constant influence and depend greatly on what currently drives the market. Furthermore, the correlation between sentiment indicators varies over time, especially in times of market distress. In this study, 73 sentiment indicators were examined in the aggregate with regard to the explainability of future stock market return distribution moments such as mean, variance, skewness, and kurtosis. This study examines 169 one-month periods from 2006 to 2020 and shows a potential solution to these challenges by applying a neural network based on long short-term memory (LSTM) neurons. The authors were able to identify a good model fit and reasonable forecasting power, which seem to work particularly well in trend forecasting. The results can be valuable in the area of portfolio risk management.

CONTAGION ACROSS FINANCIAL MARKETS DURING COVID-19: A LOOK AT VOLATILITY SPILLOVERS BETWEEN THE STOCK AND FOREIGN EXCHANGE MARKETS IN SOUTH AFRICA

The onset of the novel coronavirus pandemic (COVID-19) and previous financial and currency crises have heightened interest in understanding the nature of the interaction of stock market and exchange rate volatility. This paper aims to investigate the interdependence and volatility transmissions between the stock and foreign exchange markets for South Africa over the period of 1979:01–2021:08, including the effect the COVID-19 pandemic has had on the interdependence and volatility transmissions. Through the use of bivariate Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) modeling, the empirical outcomes from this study provide strong evidence in support of the “stock-orientated” approach, where significant price and volatility spillovers propagate from the stock market into the foreign exchange market, whilst evidence of the “flow-orientated” approach is seen in the second moment and significant shock and asymmetric spillovers from the exchange to stock market are found. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of contagion between stock and foreign exchange markets. These spillovers became more pronounced during the COVID-19 pandemic, confirming heightened contagion in these markets during the periods of crisis. The results heed important implications for not only policymakers who are concerned by the contagion across financial markets and better regulations of these markets to promote economic growth, but also investors and fund managers who seek to hedge investment risks in South Africa.

Covid-19 vaccine approvals and stock market returns: The case of Chinese stocks.

This paper investigates the Chinese stock market reactions to the announcements of Covid-19 vaccine approvals. These announcements generally impacted stock prices, but the impacts appeared to be heterogeneous across sectors. Particularly, firms in the manufacturing, wholesale, retail, and information technology sectors were persistently benefited. We also find that firms with poorer performance, smaller sizes, and greater ages reacted more positively compared to others.

The effect of economic policy uncertainty index on the Indian economy in the wake of COVID-19 pandemic

Purpose The paper tries to analyse empirically the impact of India's economic policy uncertainty (EPU) index on different macro-economic variables of India, like import, export, interest rate, exchange rate, inflation rate and stock market during pre-COVID-19 and COVID-19 era. Design/methodology/approach Although there exist several works where relationship and volatility among the stock markets and macro-economic indicators during the COVID-19 pandemic have been estimated, but till now none of the studies examined the effect of EPU index on different macro-economic variables in the Indian context along with the stock market due to the outbreak of COVID-19 pandemic. This is considered a noteworthy gap and hence opens up a new dimension for examination. To get a clear picture, monthly data from January, 2012 to September, 2021 have been considered where January, 2012-February, 2020 is taken as the pre-COVID-19 period and March, 2020-September, 2021 as COVID-19 period. All the data are converted into log natural. The authors applied DCC-GARCH model to investigate the impact of EPU index on volatility of selected variables over the study period across a multivariate framework and Markov regime-switching model to examine the switching over of the variables. Findings The results of dynamic conditional correlation - multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model indicates the presence of volatility in the dependent variables arising out of economic policy uncertainty considering the segmentation of the study period into pre-COVID-19 and COVID-19. The results of Markov regime-switching model show the variables make a significant move from low-volatility regime to high-volatility regime due to the presence of COVID-19. Research limitations/implications It can be implied that impact of EPU in terms of volatility on the Indian Stock Market will lead to unfavourable investment conditions for the prospective investors. Even, the different macro-economic variables are to suffer from the volatility arising out of EPU across a long time horizon as confirmed from the DCC-MGARCH model. Originality/value The study is original in nature. It adds superior values from the new and significant findings from the study empirically. Application of DCC-MGARCH model and Markov regime switching model makes the study an innovative one in terms of methodology and findings.

Effects of COVID-Induced Public Anxiety on European Stock Markets: Evidence From a Fear-Based Algorithmic Trading System.

The effect of COVID-induced public anxiety on stock markets, particularly in European stock market returns, is examined in this research. The search volumes for the notion of COVID-19 gathered by Google Trends and Wikipedia were used as proxies for COVID-induced public anxiety. COVID-induced public anxiety was shown to be linked with negative returns in European stock markets when a panel data method was used to a sample of data from 14 European stock markets from January 2, 2020 to September 17, 2020. Using an automated trading system, we used this finding to suggest investment methods based on COVID-induced anxiety. The findings of back-testing indicate that these techniques have the potential to generate exceptional profits. These results have significant consequences for government officials, the media, and investors.

The impact of COVID-19 and the stringency of government policy responses on stock market returns worldwide

Purpose: This paper aims to investigate the impact of COVID-19 and the stringency of the government policy response on stock market returns globally and at the regional level. Design/methodology/approach: Pooled-ordinary least squares (OLS) and panel data techniques are used to analyse the daily data set across 88 countries in the Americas, Europe, Asia-Pacific, Middle East and Africa for the period of 1 January 2020 to 10 May 2021. Findings: Using pooled-OLS and panel data techniques, the analyses show that both the daily growth in confirmed cases and deaths caused by COVID-19 have significant negative effects on stock returns across all markets. The effects are non-linear and U-shaped. Stock markets react more to the growth of confirmed cases than to the growth in the number of confirmed deaths. The results, however, vary across regions. More specifically, this study finds that the negative effect of confirmed cases is stronger in the Americas and the Middle East, followed by Europe. The negative direct effect of deaths caused by COVID-19 is stronger in the European region, followed by the Middle East, in relation to the rest of the world. The stock market returns in the African region are not, however, statistically significant. The researcher finds evidence that stringent policy responses lead to a significant increase in the stock market returns, both globally and across regions. Practical implications: The results suggest that the integrity of the government and its interventions complemented by a stable and reliable monetary policy are crucial in providing confidence to firms and households in uncertain times. Originality/value: COVID-19 has a significant impact on national economies and stock markets, triggering various governments’ interventions across all geographic regions. The pandemic has significantly affected all aspects of life, especially the stock markets. However, their empirical impact on stock returns is still unclear. This paper is the first of its kind to fill this gap by providing an in-depth quantitative analysis of the impact of both COVID-19 and stringency of the governmental policy responses on stock market returns globally and at the regional level. It is also the first to use an advanced analytical framework in analysing the effects of daily growth in both total and newly confirmed cases, and the daily growth in both total and new deaths caused by COVID-19 on them. The dynamic nature of the data on COVID-19 is taken into account. The non-linearity of the effects is also considered. © 2021, Emerald Publishing Limited.

Multiscale Partial Correlation Clustering of Stock Market Returns

This study proposes a wavelet procedure for estimating partial correlation coefficients between stock market returns over different time scales. The estimated partial correlations are subsequently used in a cluster analysis to identify, for each time scale, groups of stocks that exhibit distinct market movement characteristics and are therefore useful for portfolio diversification. The proposed procedure is demonstrated using all the major S&P 500 sector indices as well as precious metals and energy sector futures returns during the last decade. The results suggest cluster formations that vary by time scale, which entails different stock selection strategies for investors differing in terms of their investment horizon orientation.

IMPACTS OF GLOBAL AND LOCAL COVID-19 CASES ON EMERGING STOCK MARKETS

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.

COVID-19, government interventions and emerging capital markets performance.

In this study, we explore the impact of government intervention to contain the spread of COVID-19 in emerging countries on the performance of their leading stock indices. We retrieved data on the performance of 25 international capital market indices included in the MSCI Emerging Markets Index and data about the closures, economic, and health measures imposed in each country examined. Overall, our findings show that government restrictions are associated with negative market returns, possibly due to the anticipated adverse effect to the economy. The adverse effect is more evident when closures are imposed. The market response to economic stimulus is mild but varies depending on the type of intervention imposed, much as with the health measures. Public campaigns may raise public awareness about COVID-19, but they can also increase the public's fear of the pandemic, reflected in the negative response in capital markets. The results are essential for understanding the trends and fluctuations in emerging markets during this current crisis and for preparing for crises in the future.

Empirical Examination on the Drivers of the U.S. Equity Returns in the During the COVID-19 Crisis.

This study investigates the drivers of the Standard & Poor's (S&P) 500 equity returns during the COVID-19 crisis era. The paper considers various determinants of the equity returns from December 31, 2019, to February 19, 2021. It is observed that the United States Dollar (USD) and the volatility indices (VIX) negatively affect the S&P 500 equity returns. However, the newspaper-based infectious disease "equity market volatility tracker" is positively associated with the stock market returns. These results are robust to consider both the ordinary least squares (OLS) and the least angle regression (LARS) estimators.