The role of stock markets in the US, Europe, and China on oil prices before and after the COVID-19 announcement

This research investigates the asymmetric effects of the three major stock prices of the US, Europe, and China on WTI and Brent oil futures prices before and after the COVID-19 announcement by covering weekly data from January 2015 to April 2021. The results of the nonlinear autoregressive distributed lag (NARDL) model show that the US stock price has a significant positive effect in both models prior to the COVID-19 announcement but loses its effect on the WTI oil futures price after the COVID-19 announcement. Its impact on the Brent oil futures price remains after the COVID-19 announcement. The Europe stock price has a significant positive effect in all states. China stock price is not significant in the pre-COVID-19 period, but it has a significant effect after the COVID-19 announcement in both models. However, the only positive asymmetric changes in China stock price show a significant effect on the Brent oil futures price. Before COVID-19, the US stock price is the strongest, while the Europe stock price is the strongest after the COVID-19 announcement.

COVID-19 related stringencies and financial market volatility: sectoral evidence from India

Purpose: This study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020–05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques. Design/methodology/approach: For this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility. Findings: Results show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors. Originality/value: The key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework. © 2022, Emerald Publishing Limited.

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.

Assessment of pre-eclampsia and eclampsia health commodities' supply chains in selected hospitals of Lagos State during COVID-19 pandemic

Purpose: Pre-eclampsia and eclampsia (PE/E) are rising in Sub-Saharan Africa, including Nigeria. This study aims to evaluate the availability and logistics management of sixteen items from the Nigerian essential medicine list required for managing these conditions. Design/Methodology/approach: A cross-sectional study in 50 health-care facilities in Lagos State, Nigeria, at the beginning of the COVID-19 pandemic by interviewing the facility's main person in charge of health commodities. Data were recorded during the visit and in the previous six months using the adapted Logistics Indicators Assessment Tool (LIAT). In addition, descriptive analysis was conducted based on the World Health Organization availability index. Findings: The availability of 13 (81%) of the commodities were high, and 3 (19%) were relatively high in the facilities, stock out rate during the visitation and previous six months varied with the commodities: urinalysis strip (22%) and (40%), hydralazine (20%) and (20%), labetalol injection (8%) and (20%), labetalol tablet (24%) and (24%) and sphygmomanometer (8%) and (8%). No stock out was recorded for 11 (69%) commodities. All the facilities observed 9 (75%) out of the 12 storage guidelines, and 36 (72%) had a perfect storage condition score. Limitations/Implications: Current state of PE/E health commodities in the selected facilities is highlighted, and the strengths and weaknesses of the supply chain in these health facilities were identified and discussed. Originality/value: These commodities' availability ranged from reasonably high to very high. Regular supportive supervision is germane to strengthening the logistics management system for these commodities to prevent the negative impact on the health and well-being of the people during the COVID-19 pandemic and post-pandemic. © 2023, Adesola Olalekan, Victor Igweike, Oloruntoba Ekun, Abosede Adegbite and Olayinka Ogunleye.

Connectedness among various financial markets classes under Covid-19 pandemic and 2022 Russo-Ukrainian war: evidence from TVP-VAR approach

PurposeThis paper examines the time-varying return connectedness between renewable energy, oil, precious metals, the Gulf Council Cooperation region and the United States stock markets during two successive crises: the pandemic Covid-19 and the 2022 Russo-Ukrainian war. The main objective is to investigate the effect of the Covid-19 pandemic and the Russo-Ukrainian war on the connectedness between the considered stock markets. Design/methodology/approachThis paper uses the time-varying parameter vector autoregression approach, which represents an extension of the Spillover approach (Diebold and Yilmaz, 2009, 2012, 2014), to examine the time-varying connectedness among stock markets. FindingsThis paper reflects the effect of the two crises on the stock markets in terms of shock transmission degree. We find that the United States and renewable energy stock markets are the main net emitters of shocks during the global period and not just during the two considered crises sub-periods. Oil stock market is both an emitter and a receiver of shocks against Gulf Council Cooperation region and United States markets during the full sample period, which may be due to price fluctuation especially during the two crises sub-periods, which suggests that the future is for renewable energy. Originality/valueThis paper examines the effect of the two recent and successive crises, the Covid-19 pandemic and the 2022 Russo-Ukrainian war, on the connectedness among traditional stock markets (the United States and Gulf Council Cooperation region) and commodities stock markets (renewable energy, oil and precious metals).

Do Banking and Financial Services Sectors Show Herding Behaviour in Indian Stock Market Amid COVID-19 Pandemic? Insights from Quantile Regression Approach

In India, the coronavirus (COVID-19) pandemic-induced country-wide regulatory lockdown and consequential supply-chain disruptions and market instability have all posed serious challenges before the regulators and policymakers. Amid the pandemic, the stock market showed return volatilities primarily due to the unexpected investors' behaviour. One of the behavioural biases is herding, which has the power to wreck the market equilibrium and shatter the market efficiency. Given that the pandemic has generated unprecedented spirals of uncertainties across the globe, thereby creating interruptions in the pattern of stock market investment decisions, this study examined the herding behaviour of 54 stocks of banking and financial services sectors listed in the national stock exchange. In the quantile regression framework, the study provides evidence of the presence of herding for public sector banking and financial services under the bull market conditions during the pandemic in the 90th quantile of the return distribution. This finding has implications for the mispricing of financial assets in these sectors. So, the study suggests removing information asymmetry among the market participants and devising policy initiatives for ensuring market stability. © 2023 Association of Asia Scholars.

Through Running and Integration of Federal Railroad Administration and Federal Transit Administration Regulated Passenger Trains: A Path Toward Mixing Intercity, Commuter, Metro, and Light Rail on the Same Tracks

U.S. rail transit (subways, metros, and light rail) and Federal Railroad Administration (FRA) regulated heavy rail (commu-ter, intercity and regional rail) operate completely separately in revenue service. This necessitates transfers between the modes at terminals. While not unique to the U.S.A., its version of this practice is extreme and prevents the development of robust seamless rail networks. Especially in the post-Covid environment, this leaves commuter rail in search of a mission and rail transit isolated from suburbs. This paper discusses the statutory regulatory scheme that divides the two modes in the U.S.A. It will analyze the justification for the segregation and its history. Such issues include potential collisions, weight, crashworthiness, electrification, signaling, loading gauge, platform height, and operating practices. This paper concludes that the regulatory barrier preventing an FRA-regulated train from going onto a non-FRA railroad are surmountable. Running through trains between the FRA-regulated system and the rail transit network would enhance regional networks. The ‘‘Karlsruhe model'' in Germany and the through running of regional trains onto the Tokyo subway network are two prime examples. Recent technological advances—such as dual mode battery multiple units, robust signaling systems such as Communications Based Train Control and Positive Train Control, and advanced car body designs able to deal with different loading gauges—make through running more practical. With little or no new right-of-way, it is possible to create far more useful rail networks. Potential shared networks at the conceptual level are discussed for Los Angeles, Seattle, Washington, D.C., Dallas, and Sacramento. © National Academy of Sciences: Transportation Research Board 2022.

Climate policy uncertainty and stock market volatility: Evidence from different sectors

This paper mainly investigates whether the climate policy uncertainty index (CPU) can predict the volatility of Chinese stock market volatility considering different sectors. Out-of-sample results show that climate policy uncertainty index can have a greater effect on the utility sector. We also investigate the effects of CPU based on longer horizons, different volatility levels and the COVID-19 pandemic. This paper tries to provide new evidence based on sector stock indices. © 2022

Forecasting global stock market volatilities in an uncertain world

We investigate the predictive relationship between uncertainty and global stock market volatilities from a high-frequency perspective. We show that uncertainty contains information beyond fundamentals (volatility) and strongly affects stock market volatility. Using several crucial uncertainty measures (i.e., uncertainty and implied volatility indices), we prove that the CBOE volatility index (VIX) performs best in point (density) forecasting;the financial stress index (FSI) in directional forecasting. Furthermore, VIX's predictive power improved dramatically after the COVID-19 outbreak, and the VIX-based portfolio strategy enables mean-variance investors to achieve higher returns. There are two empirical properties of VIX: (i) it helps reduce significantly forecast variance rather than bias;and (ii) its forecasts encompass other uncertainty forecasts well. Overall, we highlight the importance of considering uncertainty when exploring the expected stock market volatility. © 2022 Elsevier Inc.

The COVID-19 pandemic and financial stability in Vietnam: evidence from the interbank market

Purpose: This study investigates the impact of the COVID-19 pandemic on financial stability in Vietnam, a developing country characterized by a bank-based financial system. Design/methodology/approach: Using a sample of daily data from January 23, 2020 to June 30, 2022, the VECM and NARDL models are employed to study Vietnam's financial stability in face of the COVID-19 disaster. Following the literature on COVID-19, the authors measure the impact of the pandemic by the number of daily infected cases and the national lockdown. Given the reliance of the Vietnamese government on the banking system to regulate the economy, the authors evaluate financial stability from the interbank market and stock market perspectives. Findings: The authors find that the pandemic imposes a destructive effect on financial stability during the early time of the pandemic;however, the analysis with an extended period indicates that this effect gradually fades in the long term. In addition, from the NARDL results, the authors reveal an asymmetric relationship between the financial market and the COVID-19 pandemic in both short term and long term. Research limitations/implications: An implication drawn from this study is that unprecedented health disasters should be resolved by unprecedented stringent countermeasures when conventional methods are ineffective. Although rigorous remedies may increase short-term liabilities, their implementation quickly ceases disease diffusion and helps an economy enter the recovery stage in a timelier manner. Originality/value: The study is the first to examine the impact of the COVID-19 pandemic on financial stability, via the interbank market lens, in a developing country that relies on the bank-based financial system. © 2023, Emerald Publishing Limited.

How the effective reproductive number impacts global stock markets

The pandemic caused by the novel coronavirus COVID-19 has impact the economies of countries across the world. In a short period of time, researchers have begun to analyse the effect of the pandemic on global stock markets. Although the most known measurements of COVID-19 are the number of new cases and deaths, there are more robust indicators. In particular, the effective reproductive number is one of the most important indicators to analyse the pandemic which indicates the degree to which the spread is under control. In this paper, we assess the impact that the Effective Reproductive Number (Rt) has on 26 countries around the world (32 stock market indexes) comparing the performance of various forms of Generalized AutoRegressive Conditional Heteroskedasticity models. The results demonstrate that of the 32 stock markets analysed, 37.5% had a negative effect with respect to Rt and only in 12.5% of the cases was the effect of the variation of Rt positive. This implies that in more than a third of the stock markets analysed as the pandemic progressed uncontrolled the result was a decrease in the value of the market index. The 11 of the 26 countries analysed had a negative and significant effect (Brazil, Germany, Indonesia, Israel, Italy, Japan, Russia, South Korea, Sweden, Taiwan, and United States). Findings suggest that the Effective Reproductive Number volatility had a significant impact on 10 of the 26 countries analysed (38.5%) (Australia, Brazil, Canada, China, India, Italy, Mexico, Russia, Singapore and United Kingdom). © 2023 John Wiley & Sons Ltd.

CSR and firm value: is CSR valuable during the COVID 19 crisis in the French market?

This study examines the impact of the COVID-19 outbreak on the French stock market and investigates whether companies with a commitment to corporate social responsibility (CSR) were less affected. Examining a sample consisting of 464 French firms, we separate firms that have implemented CSR activities around the event period (considered as active CSR adopters) from CSR-adopters (firms that did not indulge in CSR activities around that period) and non-CSR adopters. The empirical results indicate that active CSR adopters were less affected as some positive returns have been observed around the event date, indicating that their stock prices were relatively resistant to the crisis. The multivariate analysis shows that the French market reacted significantly to CSR strategy and that active CSR adopters are the least affected.

Hybrid optimization enabled deep learning and spark architecture using big data analytics for stock market forecasting

The precise forecasting of stock prices is not possible because of the complexity and uncertainty of stock. The effectual model is needed for the triumphant assessment of upcoming stock prices for several companies. Here, an optimized deep model is utilized to effectively predict the stock market using the spark framework. Here, the data partitioning is done using deep embedded clustering, wherein the tuning of parameters is done using the proposed Jaya Anti Coronavirus Optimization (JACO) algorithm in the master node. The proposed JACO is developed by combining Jaya Algorithm and Anti-Coronavirus Optimization algorithm. Then, important technical indicators are mined from divided data in slave nodes. Here, the technical indicators are considered features for enhanced processing. Then, data augmentation is done to make data suitable for processing in the master node. At last, the prediction was done in the master node using deep long short-term memory (Deep LSTM), and training is performed with the proposed JACO. The proposed JACO-based Deep LSTM attains the smallest mean absolute error of 0.113, mean squared error of 0.095, and root mean squared error of 0.309.

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

What effects will Covid-19 have on the G7 stock markets? New evidence from a cross-quantilogram approach

With several commodity and financial markets allegedly performing poorly during the coronavirus disease (Covid-19) pandemic, the objective of this study is to examine how the pandemic has affected stock markets in the G7 economies. The study applies the recently developed cross-quantilogram model introduced by Han et al. (2016) to investigate quantile dependence between the conditional stock return distributions of G7 countries and the total daily global confirmed Covid-19 cases across investment horizons. The results reveal that the cross-quantile dependence between the confirmed Covid-19 cases and G7 stock returns is most significant in the short and medium term. The interlinkage weakens as the lag period lengthens. These findings imply that, in the short and medium term, stock markets in the G7 countries reacted negatively and disproportionately to the increase in the number of daily verified Covid-19 cases. Besides, cross-quantile correlations calculated from recursive subsamples indicate that they change over time, especially in low and medium quantiles, suggesting that they are prone to jumps and discontinuities in the dependence structures. The findings can aid investors and policymakers in better understanding stock market dynamics, particularly during times of great stress and unknown events.

Impacts of COVID-19 on dynamic return and volatility spillovers between rare earth metals and renewable energy stock markets

We examine the time-frequency co-movements and return and volatility spillovers between the rare earths and six major renewable energy stocks. We employ the wavelet analysis and the spillover index methodology from January 1, 2018 to May 15, 2020. We report that the COVID-19-triggered significant increase in co-movements and spillovers in returns and volatility between the rare earths and renewable energy returns and volatility. The rare earths act as net recipient of both return and volatility spillovers, while the clean energy stocks are net transmitters of return and volatility spillovers before and during the COVID-19 crisis. The solar and wind stocks are net transmitters/receivers of spillovers before/during the pandemic. The remaining markets shift from net spillover receivers to transmitters or vice versa;evidencing the effects of the pandemic. Our results show that cross-market hedge strategies may have their efficiency impaired during the periods of crises implying a necessity of portfolio rebalancing. © 2022 The Authors

Analyzing interconnection among selected commodities in the 2008 global financial crisis and the COVID-19 pandemic

This study investigates the interconnection among several commodities in the advent of two well-known phenomena: the 2008 global financial crisis (GFC) and the COVID-19 pandemic. We use a daily return series for selected commodities: three base metals (copper, zinc, and lead), two benchmark crude oils (WTI and Brent), and gold. Three different methods have been considered to study interconnection: Multifractality, Network theory, and Wavelet coherences. By applying Detrending Moving-average Cross-correlation Analysis (DMCA) method, we witnessed an increase in cross-correlation in the higher time windows in most time series. Generally, we observe that the benchmark crude oils have the highest relationships, and then, in the following positions, we have the dependency among base metals (copper, lead, and zinc) and between the base metals and the crude oils. In the context of the Wavelet analysis, we notice that the significant fluctuations and changes in the extent of interconnections among data could be traced when the two crises occurred, particularly between October 2018 and April 2021, and in the frequency range of 4-128 days. This phenomenon indicates the role of the COVID-19 pandemic in creating a volatile situation in the commodity markets. The findings of this study have significant implications for investors, academic researchers, and policymakers.

Covid-19 pandemic and stock returns in India

This paper examines whether the Covid-19 pandemic has had a homogeneous or heterogeneous effect on stock returns in India. We consider panel data by using 1,318 companies that are listed on the National Stock Exchange of India. We find that the daily growth rate in Covid-19 cases and Covid-19 deaths are negatively associated with stock returns. Further, we observe that the average stock returns during Lockdown 2 are positive and highly significant, while the returns during Lockdowns 3 and 4 are negative. Moreover, our results show that the chemical, technology, and food and beverage industries earn higher returns. In contrast, the banking and finance, automotive, services, and cement and construction industries yield lower returns for the overall period. Interestingly, all industry groupings in this study earn a positive return during the lockdown period. In particular, the chemical, technology, automotive, metals and mining, and food and beverage industries provide higher returns during the lockdown period. Finally, this study supports the claim that the Covid-19 pandemic has had a heterogeneous effect in the Indian stock markets. © 2022, Academy of Economics and Finance.

Can Investors Profit from Utilizing Technical Trading Rules during the COVID-19 Pandemic?

In the past, it was believed that investors may generate abnormal returns (AR) for trading stocks by employing technical trading rules. However, since the COVID-19 pandemic broke out, stock markets around the world seem to suffer a serious impact. Therefore, whether investors can beat the markets by applying technical trading rules during the period of COVID-19 pandemic becomes an important issue for market participants. The purpose of this study is to examine the profitability of trading stocks with the use of technical trading rules under the COVID-19 pandemic. By trading the constituent stocks of DJ 30 and NASDAQ 100, we find that almost all of the trading rules employed in this study fail to beat the market during the COVID-19 pandemic period, which is different from the results in 2019. The revealed findings of this study may shed light on that investors should adopt technical trading with care when stock markets are seriously affected by black swan events like COVID-19. © 2023 World Scientific Publishing Company.

US policy responses to the COVID-19 pandemic and sectoral stock indices: A fractional integration approach

This paper uses fractional integration to assess the impact of US policy responses to the COVID-19 pandemic on 10 US sectoral stock indices from 1 January 2020 to 11 June 2021. The results provide evidence of mean reversion in most cases and suggest that the Effective Federal Funds Rate and monetary and fiscal announcements are the most effective policy tools. © 2022 Informa UK Limited, trading as Taylor & Francis Group.