Corporate ESG and resilience of stock prices in the context of the COVID-19 pandemic in China

The COVID-19 pandemic has had a significant impact on both the financial market and the real economy, leading to widespread concern about the relationship between environmental, social, and governance (ESG) responsibilities and shareholders' wealth. This paper examines the relationship between ESG responsibility and stock returns in the context of the COVID-19 pandemic and investigates the impact of ESG responsibility on stock price resilience. The results indicate that corporate ESG scores have positive impacts on stock returns during and after the COVID-19 crisis, with the positive impacts of ESG being more significant in the post-crisis period. Among the different ESG dimensions, environmental responsibility (ESG_E) has a more significant impact on stock returns, while social responsibility (ESG_S) and governance responsibility (ESG_G) have mixed impacts during the crisis. Furthermore, during and after the outbreak of COVID-19, the positive impacts of ESG are more pronounced among firms located in low-trust regions and firms with lower analyst coverage. Additionally, the study finds that corporate ESG responsibility help restore the resilience of stock prices during the crisis, with better ESG performance leading to stronger stock price resilience. Overall, the results strongly support the conclusion that ESG has acted as an "equity vaccine” during the COVID-19 pandemic. © 2023 Elsevier B.V.

A Wavelet Analysis of the Dynamic Connectedness among Oil Prices, Green Bonds, and CO2 Emissions

Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019-2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019-2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO2 futures' returns present high volatility at low and medium frequencies, expressly in 2015-2016, 2018, the end of 2019-2020, and 2022. WCA's empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO2 futures' returns, in short, medium, and long terms, as inferred from the time-frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO2 futures' returns, with the Green Bond Index leading.

What do we know about the idiosyncratic risk of clean energy equities?

The COVID-19 pandemic stimulated the need to invest in clean energy firms for better returns and climate risk mitigation. This study provides a detailed overview of the impact of idiosyncratic risk (IVOL) on excess returns of 95 clean energy stocks. Overall, investors in clean energy stocks are guided by the pessimist group of investors who underprice the high IVOL stocks and demand high-risk premiums to diversify the firm-specific risk. Further, during the COVID-19 period, there is no significant relationship between clean energy excess stock returns and IVOL. During this period, clean energy stocks were exposed to higher information asymmetry, limiting the arbitrage opportunities and producing a weaker return-IVOL relation indicating that clean energy stocks reflect the properties of technology stocks. IVOL has a low level of persistence which may be helpful in forecasting. This study offers valuable insights for regulators and investors from the investment decisions, asset pricing, and diversification perspective.

Covid‐19 outbreak and stocks return on the West African Economic and Monetary Union's stock market: An empirical analysis of the relationship through the event study approach

This study uses the Wilcoxon's signed ranks test to identify the effect of the Covid‐19 outbreak on the stocks returns of companies listed on the West African Economic and Monetary Union's (WAEMU) stock market by considering two event dates (January 23, 2020 and March 2, 2020). To account for the temporal volatility in the event approach, the study resort to a GARCH model. Empirical findings suggest that January 23, 2020 event (first case of death due to Covid‐19 in China) have had a minor impact on the WAEMU stock market while the event on March 2, 2020 (first case of Covid‐19 in the WAEMU) strongly affected the financial market. This negative impact is much more pronounced for the distribution sectors (−34.16%). Robustness analysis reveals that the main information leading to disruption on the market is the weekly death cases and not the confirmed cases. In addition, government anti‐Covid‐19 measures such as social distancing and governance positively affect the stock return whereas lockdown, public health measures and movement restrictions contribute to a decline in the stock's price.

Analyzing airlines stock price volatility during COVID‐19 pandemic through internet search data

Recent Coronavirus pandemic has prompted many regulations which are affecting the stock market. Especially because of lockdown policies across the world, the airlines industry is suffering. We analyse the stock price movements of three major airlines companies using a new approach which leverages a measure of internet concern on different topics. In this approach, Twitter data and Google Trends are used to create a set of predictors which then leads to an appropriately modified GARCH model. In the analysis, first we show that the ongoing pandemic has an unprecedented severe effect. Then, the proposed model is used to analyse and forecast stock price volatility of the airlines companies. The findings establish that our approach can successfully use the effects of internet concern for different topics on the movement of stock price index and provide good forecasting accuracy. Model confidence set (MCS) procedure further shows that the short‐term volatility forecasts are more accurate for this method than other candidate models. Thus, it can be used to understand the stock market during a pandemic in a better way. Further, the proposed approach is attractive and flexible, and can be extended to other related problems as well.

Covid-19 and informational efficiency in Asian emerging markets: a comparative study of conventional and Shariah-compliant stocks

PurposeThis study aims to provide a comparative insight into the level of informational efficiency and irregularities of Shariah-compliant stocks and conventional stocks in three emerging markets, namely, China, Malaysia and Pakistan. The empirical evidence is provided for pre-crisis and crisis periods caused by the Covid-19 pandemic.Design/methodology/approachInformational efficiency is measured using the variance ratio (VR) Test developed by Kim (2006). The Approximate Entropy (ApEn) Metrics is used to investigate the level of irregularities in stock prices caused by the pandemic.FindingsAll the three emerging markets in the sample are not immune to the crisis caused by Covid-19 pandemic. The level of informational efficiency of both the Shariah-compliant and conventional stock is affected by the crisis. However, the former exhibits relatively high level of informational efficiency and stability in returns as compared to more volatility of conventional stocks.Practical implicationsThis study provides market agents and policy makers with a robust assessment of the impact of the Covid-19 pandemic on informational efficiency of Shariah-compliant and conventional stocks. Relatively high informational efficiency of Shariah-compliant stocks indicates that they are more transparent and that investors can trust the Shariah-compliant stocks more. This higher level of transparency and trust leads to more steady returns and lower levels of risk even during turbulent time like Covid-19. Investors can gain superior returns by conducting fundamental analysis and investing in index funds.Originality/valueTo the best of the authors' knowledge, this is the first study that highlights the difference in informational efficiency of conventional stocks and Shariah-compliant stocks in the crisis period caused by Covid-19. Unlike previous studies, this study uses firm level data which enables firm-wise assessment of informational efficiency.

Gold, crude oil, bitcoin and Indian stock market: recent confirmation from nonlinear ARDL analysis

PurposeThis paper investigates the causality among gold prices, crude oil prices, bitcoin and stock prices by using daily data from January 2014 to December 2021. The study also examines the data during the COVID-19 outbreak from January 2020 to December 2021.Design/methodology/approachTo estimate the long- and short-run causality, this study considers the nonlinear autoregressive distributed lag (NARDL) cointegration test.FindingsThe analysis found the existence of an asymmetric long-run cointegration among selected assets. Findings indicate that positive changes in bitcoin do not affect stock market in the long term. Changes in crude oil prices have a significant impact on stock prices. Moreover, it is observed that variations in the stock prices trigger a negative impact on gold prices. During the COVID-19 period, the study notices the presence of an asymmetric long-term cointegration between selected assets except bitcoin. Besides, findings revealed that negative price adjustments in gold lead to significant positive shocks in stock market.Originality/valueThese results provide critical information for policy performers and researchers to develop new strategies. Policy regulators can also consider the potential effects of the COVID-19 outbreak while developing strategies for investment decisions.

HERDING BEHAVIOR OF BUSINESS GROUPS DURING COVID-19: EVIDENCE IN CHILE

This article investigates whether herding behavior is present in stock returns of business groups during the COVID-19 pandemic. Using series of prices and daily traded volume of the companies that make up the General Index of Stock Prices of the Santiago de Chile Stock Exchange (S & P/CLIGPA) from January 1, 2010 to October 9, 2020 the results show herding behavior during COVID-19. Nevertheless, the herding behavior is weaker in business group firms compared to companies which are not affiliated to business groups. Then, when analyzing how herding behavior evolves in business groups during the presence of COVID-19, it is found that herding behavior changes to reverse herding behavior during May 2020 onwards. When inquiring about this point, it is found that herding behavior in business groups is lower under increasing uncertainty (number of cases and deaths due to COVID-19 increases).Alternate :Este artículo investiga si la conducta de manada está presente en los rendimientos de las acciones de los grupos empresariales durante la pandemia COVID-19. Utilizando series de precios y volumen diario negociado de las empresas que integran el Índice General de Precios de Acciones de la Bolsa de Comercio de Santiago de Chile (S&P/CLIGPA) del 1 de enero de 2010 al 9 de octubre de 2020, los resultados muestran una conducta de manada durante el COVID-19. Sin embargo, esta conducta es más débil en las empresas afiliadas al grupo empresarial, en comparación con las no afiliadas. Es así como encontramos que la conducta de manada para el grupo de interés evoluciona durante el periodo del COVID-19 a tal punto que cambia a lo que se denomina conducta de manada inversa durante mayo de 2020 en adelante. Al analizar este comportamiento nos encontramos con que la conducta de manada en grupos empresariales es menor en presencia de un aumento de la incertidumbre (número de casos de muertes debido al COVID-19).

Le vaccin contre la Covid-19 a-t-il un impact sur le marché financier marocain ?

L'objectif de cet article est d'examiner le co-mouvement et la corrélation dynamique entre l'évolution du taux de vaccination contre la Covid-19 au Maroc et la performance de la bourse de Casablanca, sur la base des données quotidiennes couvrant la période du 1 Mars 2020 au 6 août 2021. Pour ce faire, l'approche de Cohérence en Ondelettes (CEO) a été adopté. Nos résultats empiriques montrent la vulnérabilité de ce marché financier à performer en période de crise sanitaire. De plus, CEO révèle une cohérence forte et significative entre la performance boursière et le taux de vaccination contre la Covid-19, avec une dominance positive de la vaccination sur les rendements.Alternate abstract: The aim of this article is to examine the co-movement and dynamic correlation between the evolution of the COVID-19 vaccination rate in Morocco and the performance of the Casablanca Stock Exchange, based on daily data forecast for the period from March 1, 2020 to March 6, 2020. August 2021. We used the wavelet coherence technique (WCT) for this purpose. Our empirical results reveal the vulnerability of this financial market to perform in times of financial turmoil. In addition, CWT reveals a strong and significant coherence between stock market performance and the COVID-19 vaccination rate, with a positive dominance of vaccination over returns.

Evaluation of the Improvements of Transformer Prediction with Convolution

Proposed and developed 5 years ago, Transformer has been a prevailing machine learning method and is widely used to solve various kinds of practical problems [1]. According to relevant works, Transformer has performed well in both natural language processing and computer vision tasks, so we would like to test its effectiveness in prediction, specifically, time series prediction. Over the past two years, COVID-19 is no doubt one of the major factors that influences the changes in the stock prices, and the medical industry should be among the most significantly affected, which would provide an ideal sample for us to study transformer on time series prediction. In this paper, we not only construct a machine learning model using Transformer to predict the stock prices of one medical company but also add a convolution layer to try to optimize the predictions. The comparison of the outcome from the two models suggests that the convolution layer could improve the performance of the naive transformer in several ways. © 2022 IEEE.

Oil price shocks and tourism stock prices, global evidence

This novel study utilizes nonparametric causality-in-quantile and wavelet coherence analysis to uncover the impact of oil prices on tourism stocks across 12 global leading tourism markets. The findings of nonparametric causality-in-quantile reveal that oil prices impact the tourism stocks only in Germany, Italy, Thailand, and the United States. The overall results of wavelet analysis indicate that oil prices and tourism stocks move in phase with the crucial role of the global economic and financial crisis particularly, the COVID-19 outbreak. Several useful insights for scholars, investors, policymakers, and tourism corporate executives are drawn from this study. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

The Graph Convolutional Networks Framework for Predicting Pandemic Impact on Stock Prices

Covid-19 has dealt an unprecedented hit to the global economy and all industries, with varying degrees of decline from retail to real estate. This volatility is most evident in stock prices. Previous stock price forecasting methods typically used historical data for each stock as a separate input into the system. This paper proposes an attention-based parallel graph convolutional network framework, which consists of two parallel GCNs. The first GCN takes stock features as input, and the second GCN takes other industry features as input, and sets an attention model to reflect the pairwise interactions between networks. Experimental results on selected stock data show that the model outperforms both the LSTM model and the GCN model in accuracy and F1 score. © 2022 IEEE.

Resilience of Environmental and Social Stocks under Stress: Lessons from the COVID‐19 Pandemic

This paper examines whether environmental and social (ES) activities affect the resiliency of firms during the COVID‐19 crisis. We study a sample of 330 firms operating in five developed countries: Canada, France, Japan, the UK and the US. Our analysis shows that US firms with a high ES ranking experienced a significantly lower stock price range volatility during the Covid stock market rundown of February‐March 2020. Such findings also hold for Japanese firms but only later on after the introduction of government support. In terms of returns, compared to their peers with a low ES ranking, Japanese and UK stock prices with a high ES ranking suffered more during and after the market rundown. For other countries, we do not find significant differences in stock price behavior based on ES ratings. Our findings suggest that engaging with ES activities is not associated with a better or worse performance during crisis times, which has important implications for investors and managers.

The spillover effects of the COVID-19 pandemic: Which subsectors of tourism have been affected more?

This paper investigates the effects of COVID-19 pandemic-related uncertainty focusing on the US tourism subsectors, including airlines, hotels, restaurants, and travel companies. Using daily stock price data, we compute connectedness indices that quantify the financial distress in the tourism and hospitality industry and link these indices with a measure of COVID-19-induced uncertainty. Our empirical results show that some subsectors of tourism are affected more than others. The connectedness of tourism companies has severely increased after March 2020. Restaurants are the most heavily influenced subsectors of tourism, while airline companies come the next. Besides, our quantile regression suggests that higher quantile COVID-19 uncertainty index has more effect on the connectedness of tourism companies. Our results guide the policymakers and investors to detect the stress accumulated in each subsectors of tourism and to take more informed and timely decisions.

Do changes in earnings signal future prospects after the global financial crisis and emergence of COVID-19? Evidence from Kazakhstan

This study presents an attempt to examine the reaction of stock prices of selected Kazakhstani firms to the announcement of quarterly earnings increase or decrease between 2012 and 2020 which includes the year of the post-global financial crisis as well as the year marked by the emergence of the virus which hit economies around the world. The event study methodology was applied to seven firms listed on KASE, with estimation and post-estimation windows of 200 and 40 days, respectively between 2012 and 2020. OLS regression was utilised to test the relationship between earnings announcements and stock returns. The findings of this study demonstrate a positive statistically significant price reaction on the next day following the announcement event when considering aggregate returns for a total of 50 earnings events of the sample period. Though, the magnitude and direction of average abnormal returns (AARs) vary when each year is considered separately. Copyright © 2023 Inderscience Enterprises Ltd.

Is ESG-ness the vaccine?

In an attempt to foster debate on whether firms' commitment to ESG policies affects stocks risk-adjusted performance, we analysed the blue-chips of the European countries most affected by COVID-19. We found statistical evidence that companies that follow high ESG standards outperformed low ESG-ranked firms during Phase 1 of COVID-19. In particular, the dampening effect on the downside stock market movement was more evident during the first part of Phase 1 characterized by the sudden crash of stock prices.

Volatility connectedness of GCC stock markets: how global oil price volatility drives volatility spillover in GCC stock markets?

The study investigated the volatility connectedness of GCC stock market return and S&P global oil index returns using Diebold and Yilmaz (2012) method. The current study has also analyzed the possible impact of oil price volatility on net volatility spillover in GCC stock market returns pre- and post-COVID-19 period. The current study results suggest that the GCC stock markets have volatility connectedness with S&P Global Oil Index returns' volatility and across GCC stock markets. The GCC stock markets have greater volatility in their stock markets than volatility spillover from other GCC countries. Further investigation also suggests that global oil price volatility has a divergent causal impact on net spillover in GCC stock markets. Such results would enhance the understanding of GCC stock market connection, spillover, and economic channels through which GCC markets are connected.

COVID-Vaccination and Performance in Five Global Stock Market Indexes

This paper analyses the response of stock markets to vaccine availability. Objective: the objective of this paper is to examine the differential effect of information about the arrival of COVID vaccine on the stock price performance of five main global stock market indexes. Prior work: the paper relies on the prior theory of Efficient Market Hypotheses (EMH). Method: data on stock price performance seven months before vaccine arrival and seven months within the vaccination period were from Trading Economics stock indexes archives for five main market indexes namely (Dow Jones, Shanghai, S&P, FTSE, and EURONEXT). The data were analysed using the t-test of mean difference in stock prices before and during vaccine at 5% alpha level. Findings: results for the five indexes analysis show that stock prices during the arrival of vaccine significantly outweigh the stock prices before vaccine arrival at p-values below 0.01, which are lower than the alpha value of 5%. The mean stock price increases during vaccine arrival ranges from 7% to over 20% for the different indexes. Implications: The paper provides practical information for investors who need to know how sensitive the various indexes are to vaccine information. The paper also provides an avenue for future research to expand on this initial research on vaccine effect on stock prices. Furthermore, the paper presents a veritable case study for economics and finance postgraduate students in the universities. Value: This paper fills existing gap in knowledge by being the first to analyse the effect of COVID vaccine arrival on the stock price of five main global stock indexes and contributes by indicating that stock indexes are sensitive to vaccine production with diverse percentages of sensitivity.

A business model predicting the impact of live-stream marketing on firms' stock price - An event study.

Live stream marketing in China has been in the rage since 2019, and the e-commerce industry has expanded dramatically since the start of the pandemic. Internet celebrities, a growing number of people from different walks of life, movie stars, and TV hosts are now joining as live streamers. In February 2020, China's A-share stock market's Internet celebrity live streaming index rose by more than 20%. However, does adopting live stream marketing really have positive and significant impact on stock prices of listed companies? This study used event study analysis to investigate the impact of live stream marketing on stock prices of listed companies. After computing the normal rate (NR), abnormal rate (AR), cumulative average abnormal return (CAAR) of the subjects using EXCEL and SPSS and conducting a significant analysis of the CAAR, this study found that live stream marketing events have a positive influence on stock prices of listed companies. Live streaming has brought new economic vitality, however, with the existence of chaos phenomenon on the unmatured industry standards, access thresholds, and industry management at the same time. This study tries to organize a conceptual framework for discussion, and from a practical perspective, to summarize the reasons why companies use live stream marketing to influence stock prices: (1) Live stream marketing can boost sales in a short amount of time. (2) The stock price is influenced by live stream marketing's dramatic sales. (3) Brand awareness, which helps forecast the stock price, is promoted. At the same time, live stream provides significant advantages for companies. However, there is no certain supporting business model predicting how live stream marketing significantly affects the companies' stock price. Therefore, the authors, from a theoretical perspective, tried to solve the problem by seeking a stable business model for predicting the influence of live stream marketing on the stock price. In short, the influence of internet celebrity marketing has become a new significant variable and greatly impacted the firm's stock market price and the relevant research regarding this phenomenon is still scarce; it is necessary to study this hot topic at this stage, which is the research motive of this study.

Working online or offline during COVID-19: Which has more impacts on stock price?

Remote work has become increasingly popular and important after the spread of COVID-19, but its impact on the financial market is in dispute. Using a unique dataset of analyst visits in China and multiple regression, we examine the impact of remote work on the financial market by comparing the market reaction to analysts' online and offline visits. Results show that online visits have a significantly greater impact on stock prices than offline visits, as discussion depth, information sharing, and information dissemination are enhanced. Additionally, online visits can predict the changes in funds' holdings and firms' future performance. Overall, our findings suggest that remote work improves the information environment of the financial market during COVID-19.