Impact of Pandemic Outbreak and Targeted Required Reserve Ratio Cut Policy on Stock Return Rate: Evidence from China

This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.

The role of categorical EPU indices in predicting stock-market returns

This study investigates the predictive ability of categorical economic-policy uncertainty (EPU) indices for stock-market returns. The results indicate that some categorical EPU indices have superior predictive ability for stock returns and even achieve higher realized utility than the original EPU index and popular predictors. Furthermore, the diffusion indices based on EPU categories, especially those that use partial least squares (PLS) to extract the principal components, more effectively use the forecast information contained in categorical EPU indices, resulting in improved forecast performance, including reduced forecast errors and increased economic value for investors. In addition, the categorical EPU indices show superior forecasting performance during economic-expansion, the China-US trade-war, and COVID-19 pandemic periods.

The Effect of COVID-19 Pandemic on Stock Return of Kompas 100 Index

The COVID-19 pandemic has had a huge impact on all aspects of the company's life cycle. Some companies are even unable to maintain optimal performance like before during the pandemic. Corporate social responsibility activities that are considered to provide good faith to the good name of the company that contribute to increasing stock returns. However, corporate social responsibility activities are maximized because the costs are chosen for activities around the environment carried out by large-scale companies on the Compass Index 100. This study aims to determine the effect of corporate social responsibility and company size on stock returns through Return on Equity in companies listed on Kompas 100 Index after the COVID-19 Pandemic. The population in this study covers all companies that are members of the Kompas 100 Index and are registered with Indonesia Stock Exchange (IDX). The sample method used is purposive sampling. The data analysis technique used is Structural Equation Modeling (SEM) analysis. The results showed that corporate social responsibility and company size affect Return on Equity and stock returns, and Return on Equity affects stock returns. The demand for shares of companies listed on the Kompas 100 Index is classified as the most consistent because it takes into account the company's sustainability in the future by allocating corporate social responsibility costs to build the company's good name. Corporate social responsibility activities are the example of the company's concern for the surrounding environment which aims to be able to increase the company's Return on Equity. In line with the higher level of Return on Equity, the size of the company as measured by total assets has also increased. © 2023 WITPress. All rights reserved.

Making better IS security investment decisions: discovering the cost of data breach announcements during the COVID-19 pandemic

PurposeStock price reactions have often been used to evaluate the cost of data breaches in the current information systems (IS) security literature. To further this line of research, this study examines the impact of data breaches on stock returns, information asymmetry and unsystematic firm risk in the context of COVID-19.Design/methodology/approachThis paper employs an event study methodology and examines data breach events released in public databases, spanning pre- and post-COVID settings. This study investigated 283 data breaches of the US publicly traded firms, and the economic cost was measured by cumulative abnormal returns (CARs), trading volume, bid-ask spread and unsystematic risk.FindingsThe authors observe that data breaches during the COVID pandemic make investors react more negatively to data breach announcements, as reflected in the significantly negative difference in CARs between breached firms before COVID and those after COVID. The findings also indicate that, after the disclosure of data breach incidents, information asymmetry is reduced to a lesser extent compared with that in the pre-COVID setting. The authors also find that data breach events lead to an increase in the unsystematic risk of breached companies in the pre-COVID era but no change in the post-COVID era.Originality/valueThis study is the first effort to examine the economic consequences of data breaches by investigating the effects in the form of trading activities and risk measurement in the COVID setting.

Spillover effects from news to travel and leisure stocks during the COVID-19 pandemic: Evidence from the time and frequency domains

The impact of the COVID-19 pandemic on tourism has received general attention in the literature, while the role of news during the pandemic has been ignored. Using a time-frequency connectedness approach, this paper focuses on the spillover effects of COVID-19-related news on the return and volatility of four regional travel and leisure (T&L) stocks. The results in the time domain reveal significant spillovers from news to T&L stocks. Specifically, in the return system, T&L stocks are mainly affected by media hype, while in the volatility system, they are mainly affected by panic sentiment. This paper also finds two risk contagion paths. The contagion index and Global T&L stock are the sources of these paths. The results in the frequency domain indicate that the shocks in the T&L industry are mainly driven by short-term fluctuations. The spillovers from news to T&L stocks and among these T&L stocks are stronger within 1 month.

Impact of geo-political risk on stocks, oil, and gold returns during GFC, COVID-19, and Russian–Ukraine War

The study uses wavelet power spectrum and wavelet coherence transformation methodologies to examine how geopolitical risk affected the returns on stocks, oil, and gold during the GFC, COVID-19, and Russia-Ukraine war-three disruptive events that affected the world's financial markets. For better diversification benefits during the turbulent times, we further investigate the degree of co-movement in frequency and time domains. We observe that GPR has high variations during Russia-Ukraine war period compared to COVID-19 period and is shown to have least variation during the GFC period. WTI crude oil and DJGI indexes are observed to have high variations during GFC, and COVID-19 periods followed by Russia-Ukraine war. We further observe that GOLD offers better diversification opportunity as well as leading movement against WTI and DJGI during disruptive events in financial markets. The results provide new understanding of how geopolitical risk affects financial assets for international investors, fund managers, and regulators, which would further aid to find risky and safer haven possibilities during the turmoil periods. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Stock valuation during the COVID-19 pandemic: An explanation using option-based discount rates.

Changes in short-term expected market returns (discount rates) were a significant driver behind the unprecedented fluctuations in equity markets during the first 4 months of the COVID-19 pandemic. Using option-based estimates of the expected market risk premium for 13 international markets, we find that approximately 40% of the change in market values during the COVID-19 pandemic can be attributed to changes in short-term discount rates. We also document sharply downward sloping term structures of equity risk premia at the start of the pandemic, consistent with Hasler and Marfè (2016). Finally, we document a significant increase in the correlation between index returns and changes in the short-term discount rate during the pandemic compared to the period before the pandemic.

The effect of vaccination during the COVID-19 for the restaurant industry.

The purpose of the study is to determine whether vaccination rates and the use of franchising have an impact on the volatility of stock returns in the restaurant industry. Based on the agency and resource scarcity theories, this study first examines the effect of vaccinations against COVID-19 on a restaurant firm's stock return volatilities caused by uncertainty during a crisis. The study further investigates whether firm-specific vaccination rates more greatly reduce stock return volatilities as the degree of franchising increases. With a two-way fixed-effects model, the study finds that the firm-specific vaccination rate reduces volatilities of the firm's stock returns. However, the study also finds an opposite direction to the moderating effect of franchising in that the more a restaurant firm franchises, the further the risk-reduction effect of its vaccination rate diminishes. Theoretical and practical implications along with limitations are discussed.

Do the Outbreak of COVID-19 Influence the China Stock Market?

This study aims at the impact outbreak of COVID-19 influence Chinese currency and stock market over the period December 2, 2019, to January 04, 2021. The Generalized Autoregressive Conditional Homoscedastic approach captures the most common stylized fact about index returns (such as multivariate to capture the Shanghai and Shenzhen stock exchange). Our finding shows the explosive process and risk premium for the Shenzhen stock exchange (SSE) and Shanghai stock exchange (SZSE) index. And the standard deviation depreciation of the Chinese currency during the COVID-19 equivalent to 0.46% improved stock market return by 81% average returns. These results explain that high volatility of index returns is present in the Chinese stock market over the sample period. According to the analysis results, it can be concluded that the number of new cases and the number of recent deaths have a significant effect on the stock market, causing uncertainty in the sustainability.

Assessing oil price volatility co-movement with stock market volatility through quantile regression approach

In times of financial crisis as well as during the COVID-19 era, gold and crude oil are the two commodities that have the most influence on global stock markets and the real economy. But research has mostly focused on the effects of these commodities' prices on their own, and the volatility of these commodities' prices as a whole hasn't gotten much attention. This research paper evaluates the impacts of crude oil prices volatility on shares marketplaces. This research examines the impact of crude oil uncertainty on the overall market returns in several economic sectors (China, Japan, the USA, France, and Germany) between 2000 and 2020 using the importance of the crude oil prices volatility index by applying a Quantile-on-Quantile regression(Q-Q), including dynamic copula with Markov-Switching. The results depict that because the effect of the OVX changes crosswise every single quantile level of stock return, it is cumbersome to ascertain the changes within the adverse impacts under varied stock market circumstances. Equally, to derive a comprehensive understanding of the correlation between crude costs volatility and stock returns, we utilize twofold quantile regression and quantile-quantile regression methods. We interpret these different features' impacts by applying the quantile regression approximates. Our experiential findings show that crude costs uncertainty has lop-sided impacts on stock returns;more so, these disproportionate performances alternate based not merely on the level of shares returns nonetheless equally crude market circumstances. More so, greater values match a robust risk decrease. Further, we observed heterogenous hedging effectiveness among the varied United States stock sectors. The findings demonstrate that growing crude prices volatility obtains an adverse impact on stock returns when the dual crude costs volatility and stock returns are minimal. Nevertheless, when shares returns are greater plus crude prices, volatility is minimal;growing crude volatility increases stock returns.

The Impact of the COVID-19 Pandemic on the Performance and Risk Profile of Airline Stocks

The COVID-19 outbreak dealt a severe blow to the global economy, especially to the airline industry, due to worldwide lockdown measures implemented by the authorities. This paper aims to investigate the impact of the COVID-19 pandemic on the airline stock performance of seven markets in Asia and three other markets in Australia, Germany and the United States. The data is collected from 42 airline firms from 2019 to 2020. The research outcomes indicate that: (a) COVID-19 only temporarily impacts stock returns;(b) Market values plunge immediately after the first confirmed case, and it still shows no evidence of returning to the price levels before the outbreak;(c) COVID-19 has a significant impact on stock volatility;(d) Most stocks do not illustrate any higher exposure to systematic risks. © 2022, University of Economics and Human Sciences in Warsaw. All rights reserved.

Return prediction for healthcare sector stocks by using Long Short-Term Memory Algorithm

The research is conducted during the rage of COVID-19 throughout the world. The world meets new challenges from COVID-19 from every dimension, especially the economical world. In the economic world, the most related part for the influence that springs from COVID-19 is the stocks belonging to the healthcare sector. Aiming at doing the return prediction for healthcare sector stocks, the study chooses Long Short-Term Memory (LSTM) Algorithm to introduce machines to adapt the pattern and make predictions. The study selects 6 less volatile while keeping high average trading volume stocks from the healthcare sector. Using the LSTM learning model to learn the past 5 years’ data and make the prediction to the future 5 days. The data consist of 65% of the company's data from five years ago as the training set, and the last 35% of the data as the test set. The study compares the actual data to the predicted data and sees the error by calculating root mean square error (RMSE). The result draws the conclusion that the model will perform more precise prediction when the picked stock has a clear price trend and less fluctuation. The application for this study is to provide a short-term trading strategy and manage the risk for short-term stock investment by using the LSTM model. © 2022 SPIE.

Does CSR performance improve corporate immunity to the COVID-19 pandemic? Evidence from China's stock market.

This paper studies the role of corporate social responsibility (CSR) performance on corporate financial performance during the COVID-19 by examining a sample of Chinese listed firms. Based on the PSM-DID methodology, we find that the pandemic-induced decline in stock returns is stronger with more CSR engagement. The results remain robust even after the dynamic effect test and placebo test. It means CSR performance does not improve Chinese corporate immunity to the pandemic. This inadequate response of CSR could be due to the "relatively few good things effect". Furthermore, our study indicates that increasing awareness of responsible investment and improving the quality of CSR disclosure could facilitate CSR engagement in China.

An Analysis of the Effects of Tourism Demand, Yield Curve, and Stock Returns on Economic Growth of Thailand: A Comparison Between the Bayesian DCC-GARCH and Bayesian Change-Point Methods

In this paper, the Bayesian DCC-GARCH model is applied to find the relationship among economic growth, tourism demand, yield curve, and stock return in Thailand from 2013 to 2020, based on 30 quarterly observations. Only the time-varying correlation between real GDP and US tourist arrivals is positive and the volatility significantly increased around quarter 25 to quarter 28. The Bayesian change-point method is used to detect the sudden changes in the dependent variable time-series. There is one change point at quarter 28. Both methodologies provide similar evidence in that there exists a time-varying correlation, and a change-point in quarter 28 (July–October 2020) which coincides with the reopening time of Thailand after the Covid-19 lockdown. Even though two approaches are different, similar results are obtained in the relationship of various explanatory variables with economic growth. return from stocks, yield curve, and tourism demand are found to positively affect economic growth. Moreover, it is advised that the two methods could be used in future study to describe the real-world situation with different characteristics of the data set to provide more evidence. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Long-horizon stock valuation and return forecasts based on demographic projections

We incorporate low-frequency information from demographic variables into a simple predictive model to forecast stock valuations and returns using demographic projections. The demographics appear to be an important determinant of stock valuations, such as the dividend-price ratio. The availability of long-term demographic projections allows us to provide (very) long-horizon forecasts of stock market valuations and returns. We also exploit the strong contemporaneous correlation between returns and valuations to improve return forecasts — something which is not possible in a predictive regression with only lagged predictors. Extensive pseudo out-of-sample forecast comparisons and tests demonstrate the predictive value that an accurate demographic projection can deliver. Although the availability of historical Census Bureau projections is limited, we demonstrate that they could have been employed in real time to improve true long-horizon stock return prediction. We show how the model can be used to adjust predictions under alternative demographic assumptions, incorporating, for example, the demographic impact of COVID-19 or recent changes to immigration policy.

Do the Outbreak of COVID-19 Influence the China Stock Market?

This study aims at the impact outbreak of COVID-19 influence Chinese currency and stock market over the period December 2, 2019, to January 04, 2021. The Generalized Autoregressive Conditional Homoscedastic approach captures the most common stylized fact about index returns (such as multivariate to capture the Shanghai and Shenzhen stock exchange). Our finding shows the explosive process and risk premium for the Shenzhen stock exchange (SSE) and Shanghai stock exchange (SZSE) index. And the standard deviation depreciation of the Chinese currency during the COVID-19 equivalent to 0.46% improved stock market return by 81% average returns. These results explain that high volatility of index returns is present in the Chinese stock market over the sample period. According to the analysis results, it can be concluded that the number of new cases and the number of recent deaths have a significant effect on the stock market, causing uncertainty in the sustainability. [ FROM AUTHOR] Copyright of Problemy Ekorozwoju is the property of Faculty of Environmental Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Is cash flow growth helping stock performance during the COVID-19 outbreak? Evidence from Indonesia

The COVID-19 pandemic is an unexpected event that causes stock market investors to panic so that their value drops drastically. Operating cash flow and free cash flow are indicators of a company's financial statements that are used as a reference for investors' decision making in the stock market. A firm's cash flows reflect real changes in the firm's value for money. Cash flow growth can provide information on how well the firm's performance is in generating incremental cash inflows that can increase firm value. This study aims to explore the relationship between cash flow growth before the COVID-19 pandemic and after the COVID-19 outbreak on stock price performance. This study uses the OLS regression method with a total sample of 426 companies in the Indonesian capital market in the period March 2, 2020 to March 2, 2021. The results show that cash flow growth from operations and free cash flow growth had no significant effect on stock return after COVID-19 outbreaks in years 2020 to 2021. Sales growth, market capitalization and stock return before the COVID-19 outbreak from 2019 to 2020 had a significant negative correlation with the post COVID-19 outbreak stock return. Then, sectors whose stock performance is positively correlated after the COVID-19 outbreak are basic industry, chemicals, miscellaneous industry and infrastructure. This shows that the economic crisis caused by COVID-19 is an anomaly in the stock market. Therefore, cash flow is not relevant information for investors in predicting a company's performance during the COVID-19 pandemic crisis. © 2022 LLC CPC Business Perspectives. All rights reserved.

Using Patent Drawings to Differentiate Stock Return Rate of China Listed Companies. A Study on China Patent Species of Invention Grant

Patent is an important outcome of technological innovation. Though patent claim always caught attention when considering patent quality, it had to be supported by the drawings according to the patent examination criteria. However, patent drawing was seldom discussed. Based on the company integrated database, more than 50% of China listed companies of RMB common stocks (A-shares) from 2017Q1 to 2021Q4 were selected as effective samples. The effect of China invention grant patent’s drawing count for differentiating A-share’s stock return rate was thoroughly discussed via analysis of variation (ANOVA). The average drawing count of invention grants significantly increased over previous years. However, the total drawing count of invention grants was found to be an appropriate patent indicator for differentiating A-share’s stock return rate whereas the average drawing count of invention grants was not. The A-shares in the highest total drawing count groups of invention grants showed significantly higher stock return rate means while the A-shares in the lower total drawing count groups of invention grants showed significantly lower stock return rate means in most quarters from 2017 to 2021. The finding also proved that the patent quantity still mattered in China stock market.

The Role of Return on Asset Mediation in Influencing Corporate Social Responsibility on Stock Returns in Manufacturing Companies

The condition of manufacturing companies that experienced a bad impact due to the weak value of operational activities resulted in a decrease in company profits so that the impact on the portion of corporate social responsibility disclosure was reduced. The Covid-19 pandemic has caused several manufacturing companies to be unable to generate profits that have been determined at the General Meeting of Shareholders (GMS) so that the return on investment is lower. This study aims to examine in depth the systematic risk that will affect stock returns in changing the relationship between investor sentiment, trading activity, market factors and stock return responses during the Covid 19 Pandemic. The population used in this study are manufacturing companies listed on the Indonesia Stock Exchange. as many as 169 companies. Of the 169 companies listed on the Indonesia Stock Exchange, there were 39 companies that were delisted during 2020 and 45 companies that did not have complete data on the required research variables, so the number of sample companies used was 85 companies. The data analysis technique uses Structural Equation Modeling (SEM) analysis with PLS smart software. The results of the study show that CSR has a negative effect on ROA with a significance level of 0.000. CSR has a positive effect on stock returns with a significance level of 0.000. ROA has a positive effect on Stock Return with a significance level of 0.000.

The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods

MCDM perspektifinden COVÍD-19 pandemi koşulları göz önüne alındığında, şirketlerin pandemi koşulları öncesi ve sırasındaki sıralama pozisyonlarındaki değişiklik, birçok araştırmacı ve özellikle finansal karar vericiler için daha kritik hale gelmiştir. Bu çalışmada yöntemsel prosedür açısından diğer çalışmalardan farklı olarak yeni bir yol izlenmiştir. Ílk defa objektif bir bakış açısıyla alternatifler arasından bir MCDM yöntemi seçilerek uygulamaya devam edilmiştir. Başka bir ifadeyle nihai performans değerlendirmesi, seçilen bu yöntemin sonuçlarına dayandırılmıştır. Ílk adımda çalışmanın uygulama sahası olan BIST KOBÍ Sanayi’de işlem gören firmaların finansal performansı üç farklı MCDM yöntemiyle (MOORA, MABAC, FUCA) hesaplanmıştır. Íkinci adımda hesaplanan finansal performans puanlarıyla cari dönemdeki hisse getirileri ile olan sıralama korelasyonları Spearman yöntemiyle karşılaştırılmıştır. Üçüncü adımda bu dolaylı objektif referans doğrulama sonucu baz alınarak (en uygun ve başarılı olduğu için) FUCA yöntemi ile gerekli finansal analizler yapılmıştır. Elde edilen bulgulara göre FUCA yöntemi diğer MCDM yöntemlerine kıyasla hem salgın öncesi ve salgın sürecindeki dönemlerde hisse getirisi ile daha yüksek bir korelasyon üretmiştir. Bu sonuçlara göre, salgın süreci ile öncesindeki normal dönem için bir performans karşılaştırması yapıldığında üç konuda değişim göze çarpar: en başarılı firmalar, firmaların genel sıralaması ve gözde olan sektörler baz dönemler için tamamen değişmiştir. Bu yenilikçi prosedür literatürde ilk defa önerilmiştir ve başarılı bir şekilde uygulanmıştır.Alternate : Considering COVID-19 pandemic conditions from an MCDM perspective, the change in the ranking positions of the companies before and during the pandemic conditions has become more critical for many researchers and especially financial decision-makers. In this study, different from other studies, a new methodological procedure was followed. For the first time, an MCDM method was chosen among the alternatives with an objective point of view, and the application was continued. In other words, the final performance evaluation is based on the results of this chosen method. In the first step, the financial performance of companies traded in the BIST SME Industry, which is the application area of the study, was calculated with three different MCDM methods (MOORA, MABAC and FUCA). In the second step, the ranking correlations between the calculated financial performance scores and the stock return in the current period were compared with the Spearman method. Finally, in the third step, based on this indirect objective reference verification result (as it is the most appropriate and successful), the necessary financial analyzes were made with the FUCA method. According to the findings, the FUCA method correlated higher with the stock return before and during the pandemic than the other MCDM methods. According to these results, when a performance comparison is made between before and during pandemic conditions, three changes become prominent: the most successful companies, the companies' overall ranking, and the favourite sectors have entirely changed for the base periods. This innovative procedure has been proposed for the first time in the literature and has been successfully applied.