Pandemics and the emerging stock markets

The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets

The outbreak of the novel corona virus has heightened concerns surrounding the adverse financial effects of the outbreak on stock market liquidity and economic policies. This paper contributes to the emerging strand of studies examining the adverse effects of the virus on varied aspect of global markets. The paper examines the causality and co-movements between COVID-19 and the aggregate stock market liquidity of China, Australia and the G7 countries (Canada, France, Italy, Japan, Germany, the UK and the US), using daily three liquidity proxies (Amihud, Spread and Traded Value) over the period December 2019 to July 2020. Our empirical analysis encompasses wavelet coherence and phase-differences as well as a linear Granger causality test. Linear causality test results suggest that a causal relationship exists between the number of cases of COVID 19 infections and stock market liquidity. To quantitatively examine the degree of causality between COVID-19 outbreak and stock market liquidity, we employ the continuous wavelet coherence approach with results revealing the unprecedented impact of COVID-19 on stock market liquidity during the low frequency bands for countries that were hard hit with the COVID-19 outbreak, i.e., Italy, Germany, France, the UK and the US. Further, evidence shows that there is a heterogeneous lead-lag nexus across scales for the entire period of the study.

The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements

We use daily data of the Google search engine volume index (GSVI) to capture the pandemic uncertainty and examine its effect on stock market activity (return, volatility, and illiquidity) of major world economies while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index. We use a time–frequency based wavelet approach comprising wavelet coherence and phase difference for our empirical assessment. During the early spread of the COVID-19, our results suggest that pandemic uncertainty, and FEARS sentiment strongly co-move, and increased pandemic uncertainty leads to pessimistic investor sentiment. Furthermore, our partial wavelet analysis results indicate a synchronization relationship between pandemic uncertainty and stock market activities across G7 countries and the world market. Our results are robust to the inclusion of alternative pandemic fear measure in the form of equity market volatility infectious disease tracker. The pandemic uncertainty and associated sentiment implications could be one plausible reason for increased volatility and illiquidity in the market, and hence, policymakers should look upon this issue for the financial market stability perspective.

The effects of daily growth in COVID-19 deaths, cases, and governments' response policies on stock markets of emerging economies

Since the beginning of COVID-19, human beings have been threatened by various aspects. As of February 14, 2022, this global pandemic has caused about 412 million cases and 5.8 million deaths worldwide. Stock markets are one of the most agile economic indicators. In this context, this study investigates how daily growth in deaths, daily growth in cases, and governmental interventions affect stock market returns in 21 emerging economies from January 22 to December 31, 2020. Our results indicate that government response policies to Covid-19 positively impact stock returns. Besides, the daily growths in deaths and cases negatively affect stock market returns. The results also indicate that government response policies also have an indirect positive effect on stock market returns by weakening the negative impact of the daily growth in COVID-19 confirmed cases and deaths.

Impact of the twin pandemics: COVID-19 and oil crash on Saudi exchange index

This study aims to explore the effects of COVID-19 indicators and the oil price crash on the Saudi Exchange (Tadawul) Trading Volume and Tadawul Index (TASI) for the period from January 1, 2020, to December 2, 2020. The independent variable is oil price, and the COVID-19 indicators are lockdown, first and second decreases of Repo and Reverse Repo rates, Saudi government response, and cumulative deceased cases. The study adopts two phases. In the first phase, linear regression is used to identify the most influential variables affecting Trading volume and TASI. According to the results, the trading volume model is significant with an adjusted R2 of 65.5% and a standard error of 81. The findings of this model indicate a positive effect of cumulative deceased cases and first decrease of Repo and Reverse Repo rates and a negative effect of oil prices on Trading Volume. The TASI model is significant with an adjusted R2 of 86% and a standard error of 270. The results of this model indicate that lockdown and first decrease of Repo and Reverse Repo rates have a significant negative effect on TASI while the cumulative decrease in cases and oil prices have a positive effect on TASI. In the second phase, linear regression, and neural network predictors (with and without validation) are applied to predict the future TASI values. The neural network model indicates that the neural networks can achieve the best results if all independent variables are used together. By combining the collected results, the study finds that oil price has the most substantial effect on the changes in TASI as compared to the COVID-19 indicators. The results indicate that TASI rapidly follows the changes in oil prices.

The impact and role of COVID-19 uncertainty: A global industry analysis

The novel 2019 coronavirus (COVID-19) has resulted in uncertainty that permeates every aspect of life and business. In this study we undertake a comprehensive analysis of the impact of COVID-19 related uncertainty on global industry returns and volatility using a sample of 68 global industries and Google Trends search data to measure COVID-19 related uncertainty. The results indicate that COVID-19 related uncertainty negatively impacts returns on all industries and generally leads to higher volatility. We interpret these findings as uncertainty related to the future financial performance of firms and emerging opportunities for some industries. Certain industries are more resilient than others and increased uncertainty is not only necessarily associated with industries that experienced the largest negative returns. We also find that new factors emerged in the return generating process during the COVID-19 period. We show that despite an uncertain climate, some industries performed well, yielding positive cumulative abnormal returns that at times are greater than during the pre-COVID-19 period. The implications of our findings for investors are discussed.

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.

Consequences of COVID-19 on Banking Sector Index: Artificial Neural Network Model

The World Health Organization officially declared COVID-19 a global pandemic on 11 March 2020. In this study, we examine the effect of COVID-19 indicators and policy response on the Saudi banking index. COVID-19 variables that were applied are: new confirmed and fatal COVID-19 cases in Saudi Arabia; lockdowns; first and second decreases in interest rates; regulations, and oil prices. We implemented the analysis by running a stepwise regression analysis then building an artificial neural network (ANN) model. According to regression findings, oil prices and new confirmed cases have had a significant positive effect on the Saudi banking index. Nevertheless, the lockdown announcements in Saudi Arabia and the first decrease in interest rates had a significant negative effect on the Saudi banking index. To enhance the performance of the linear regression model, the ANN model was built. Findings showed that the ranking of the variables in terms of their importance is: oil price, number of confirmed cases, lockdown announcements, decrease in interest rates, and lastly, regulations.

COVID-19 Pandemic and Romanian Stock Market Volatility: A GARCH Approach

This paper investigates the volatility of daily returns on the Romanian stock market between January 2020 and April 2021. Volatility is analyzed by means of the representative index for Bucharest Stock Exchange (BSE), namely, the Bucharest Exchange Trading (BET) index, along with twelve companies traded on BSE. The quantitative investigation was performed using GARCH approach. In the survey, the GARCH model (1,1) was applied to explore the volatility of the BET and BSE traded shares. Conditional volatility for the daily return series showed noticeable evidence of volatility that shifts over the explored period. In the first quarter of 2020, the Romanian equity market volatility increased to a level very close to that recorded during the global financial crisis of 2007–2009. Over the next two quarters, volatility had a downward trend. Besides, after VAR estimation, no causal connection was found among the COVID-19 variables and the BET index.

The impact of COVID-19 pandemic on Islamic versus conventional stock markets: international evidence from financial markets

This study employs sample t-tests and panel pooled OLS regression to investigate the impact of COVID-19 pandemic on Islamic versus conventional stock markets returns. The study uses daily data from 15 countries over the period of September 01, 2019–April 30, 2020, which covers two main periods and over four sub-periods. Findings reveal that the returns of Islamic indices begun to be positive instead of negative by mid-April 2020, while returns of conventional ones remain negative throughout the periods. Furthermore, the results suggest a negative and statistically significant impact of COVID-19 on the performance of both stock indices. Nevertheless, this impact is weak on the Islamic indices and strong on the conventional ones. Overall, the findings indicate that Islamic stock markets perform better before and during COVID-19 than the conventional ones, and the adverse impact of the pandemic on the stock markets is relatively lesser for the Islamic indices.