Integration of Pakistan's stock market with the stock markets of top ten developed economies

This study examines the integration of Pakistan's Stock Market with the stock markets of the top ten largest economies in the world-USA, China, Japan, Germany, the UK, India, France, Italy, Brazil, and Canada-from January 2015 to October 2020. To examine long- and short run integration, this study employed Johansen and Juselius co-integration and pair-wise Granger causality tests. In the long run, the results indicated that Pakistan's Stock Market is not integrated with these markets. This implies that the market is more attractive in portfolio diversification for international investors, and vice versa. In the short run, the results revealed that, except for China, Pakistan's stock market integrates with the remaining nine markets. However, Pakistan's stock market exhibits a bidirectional relationship with the USA, Japan, Germany, the UK, and France in the lead-lag relationship. However, its relationship with India, Italy, Brazil, and Canada is unidirectional, with Pakistan's stock market leading, while these markets are following. For Pakistani investors, China is the optimal market, and vice versa. Importantly, our findings help policymakers to comprehend Pakistan's dynamic relationship with its trading partners. To the best of our knowledge, no prior study has employed advanced techniques to address the time-varying correlation among the selected markets. By determining Pakistan's stock market integration with its trading partners, this study aimed to fill this empirical literature gap.

The link between electricity consumption and stock market during the pandemic in Türkiye: a novel high-frequency approach

This article examines the relationship between electricity consumption and the stock market in the Turkish economy during the COVID-19 pandemic. A novel high-frequency model is used, incorporating the hourly energy consumption and Borsa Istanbul (BIST) National stock market index variables. To determine the effect of electricity consumption on the stock market index and vice versa, a high-frequency VAR-based spillover approach, time-varying Granger causality, and time-varying Bayesian VAR analysis are employed. The findings reveal a positive and weak relationship between electricity consumption and the stock market but it has a time-varying nature in an emerging market context in the post-COVID-19 period in the Turkish economy.

Interplay of multifractal dynamics between shadow policy rates and stock markets

Stock markets are generally perceived as a barometer of the economy and respond to international monetary policies even before economic activities. Many central banks have turned to unconventional policy measures in response to various financial crises such as the global financial crisis of 2007-2009 or the recent crisis caused by COVID-19. To examine the cross-correlation of overall international monetary policies with stock markets, we employ the daily shadow short rate (SSR), which has the advantage of allowing comparison across unconventional and conventional regimes. The analysis is made through a multifractal context using multifractal detrended cross correlation analysis (MF-DXA), considering daily data from 1st January 2000 to 31st March 2022 and country specific SSR and the stock markets of eight developed economies. The main empirical findings are the following: (i) all the country specific pairs of SSR with stock markets have significant multifractal characteristics (ii) the pairs of NZ-SSR/NZX50, US-SSR/DJIA, and CN-SSR/S&P TSX have the highest multifractal patterns while EU-SSR/Euro-area Index has the lowest multifractal patterns (iii) Australian and New Zealand stock markets exhibit anti-persistent cross-correlation with SSR while the remainder have persistent cross-correlation in their multifractality. Lastly, the findings of this study have several important implications for central banks and stock market participants.

Quantile VAR network evidence for spillover effects and connectivity between China's stock markets, green commodities, and Bitcoin

Numerous economic and financial crises, particularly the present crisis in the healthcare sector, have pushed major shock spillover channels over stock marketplaces. This research studied how the shock spillover system is affected by three significant factors: Bitcoins, unpredictability, and the China stock market between 2014 and 2021. While much earlier empirical research has looked at risk dispersion in different financial markets, this article will zero in on green markets. This investigation seeks to accomplish something that has never been done before: determine whether or not green commodities, Bitcoin, and uncertainty impact the performance of the China stock market. The following are significant results based on a quantile vector autoregressive (VAR) connection. (i) A static spillover system indicates that information was widely shared across markets during intense market circumstances. (ii) The global green economy and clean energy marketplaces are the primary sources of knowledge spillover in adverse market conditions. This research elucidates the asymmetrical influence of green products, Bitcoin, and market volatility in China. This is vital due to the dynamic nature of international and regional connections. Recent studies have shown that shock spillovers are excellent for cryptocurrencies such as Bitcoin (BTC), uncertainty indices, and global carbon indexes, but bad for most eco-friendly products.

Examining the interconnectedness of green finance: an analysis of dynamic spillover effects among green bonds, renewable energy, and carbon markets

There is growing importance of green finance as a means to finance sustainable projects and reduce carbon emissions. Green bonds have emerged as an important financing tool in this context, and there is a need to understand how they are interconnected with other components of the green finance ecosystem, such as renewable energy and carbon markets. This study investigates the interconnectivity of green finance by analyzing the dynamic spillover effects among green bonds, renewable energy stocks, and carbon markets. Using daily data spanning from January 2010 to December 2020, vector autoregressive models and time-varying parameter models are applied to examine the transmission channels of shocks among these assets. The results reveal significant dynamic spillover effects between green bonds and renewable energy stocks, as well as between carbon markets and renewable energy stocks. Additionally, the findings suggest a complementary relationship between green bonds and carbon markets. This study provides insights into the interdependence of different green financial instruments and their role in promoting sustainable development. The outcomes of the research can guide policymakers, investors, and other stakeholders in making informed decisions regarding green finance.

Co-movement between Covid-19 and G20 stock market returns: A time and frequency analysis

In our study, we employ DCC-GARCH and Wavelet coherence analysis to examine the co-movement between global covid-19 indicators (cases, recoveries and deaths) and stock returns of main equity markets in G20 countries using daily data spanning between February 2, 2020 and August 28, 2021. Our empirical results show that the co-movement between COVID-19 and G20 stock returns has been switching between negative and positive correlations across the entire time window. The wavelet coherence analysis further reveal that negative (positive) co-movements predominantly exist as lower (higher frequencies) for cases and deaths and are more mixed for recoveries. The findings also show that the short-frequency components correspond to periods around the initial announcement of the initial pandemic and also around the announced of subsequent variants of the COVID-19 virus. Policy and market implications from our study are also discussed.

Machine learning sentiment analysis, COVID-19 news and stock market reactions

The recent COVID-19 pandemic represents an unprecedented worldwide event to study the influence of related news on the financial markets, especially during the early stage of the pandemic when information on the new threat came rapidly and was complex for investors to process. In this paper, we investigate whether the flow of news on COVID-19 had an impact on forming market expectations. We analyze 203,886 online articles dealing with COVID-19 and published on three news platforms (MarketWatch.com, NYTimes.com, and Reuters.com) in the period from January to June 2020. Using machine learning techniques, we extract the news sentiment through a financial market-adapted BERT model that enables recognizing the context of each word in a given item. Our results show that there is a statistically significant and positive relationship between sentiment scores and S&P 500 market. Furthermore, we provide evidence that sentiment components and news categories on NYTimes.com were differently related to market returns.

STTM: an efficient approach to estimating news impact on stock movement direction

Open text data, such as financial news, are thought to be able to affect or to describe stock market behavior, however, there are no widely accepted algorithms for extracting the relationship between stock quotes time series and fast-growing textual representation of economic information. The field remains challenging and understudied. In particular, topic modeling as a powerful tool for interpretable dimensionality reduction has been hardly ever used for such tasks. We present a topic modeling framework for assessing the relationship between financial news stream and stock prices in order to maximize trader's gain. To do so, we use a dataset of economic news sections of three Russian national media sources (Kommersant, Vedomosti, and RIA Novosti) containing 197,678 economic articles. They are used to predict 39 time series of the most liquid Russian stocks collected over eight years, from 2013 to 2021. Our approach shows the ability to detect significant return-predictive signals and outperforms 26 existing models in terms of Sharpe ratio and annual return of simple long strategy. In particular, it shows a significant Granger causal relationship for more than 70% of portfolio stocks. Furthermore, the approach produces highly interpretable results, requires no domain-specific dictionaries, and, unlike most existing industrial solutions, can be calibrated for individual time series. This makes it directly usable for trading strategies and analytical tasks. Finally, since topic modeling shows its efficiency for most European languages, our approach is expected to be transferrable to European stock markets as well.

COVID19: A blessing in disguise for European stock markets?

This study aims to bridge the gap that has remained unfilled after the initial scrutiny and reporting of the damaging effects of Covid-19 on financial markets. The study analyzes 10 European stock markets and compares their pre and post covid return dynamics. Our findings are surprisingly pleasant, albeit counterintuitive to some. We observe a quick and unprecedented recovery in the European stock market, yielding significantly higher returns post covid, given a reasonably large holding period. We also observe an alteration and change in the status quo of countries while transmitting or receiving cross-market spillovers.

COVID-19 vaccines and global stock markets

Global stock markets react positively when different phases of human clinical trials on COVID-19 vaccines begin. The average abnormal stock return on the first day of the trials is both statistically and economically significant at 8.08 basis points. The increase in the average abnormal stock return is threefold higher for leading vaccine candidates. The positive reaction is more pronounced upon the start of phase III trials, and it is also stronger for vaccine candidates developed by the U.S. and China.

COVID-19 vaccines and global stock markets

Global stock markets react positively when different phases of human clinical trials on COVID-19 vaccines begin. The average abnormal stock return on the first day of the trials is both statistically and economically significant at 8.08 basis points. The increase in the average abnormal stock return is threefold higher for leading vaccine candidates. The positive reaction is more pronounced upon the start of phase III trials, and it is also stronger for vaccine candidates developed by the U.S. and China.

Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets

The present study investigates the degree of market responses through the scope of investors' sentiment during the COVID-19 pandemic across G20 markets by constructing a novel positive search volume index for COVID-19 (COVID19⁺). Our key findings, obtained using a Panel-GARCH model, indicate that an increased COVID19⁺ index suggests that investors decrease their COVID-19 related crisis sentiment by escalating their Google searches for positively associated COVID-19 related keywords. Specifically, we explore the predictive power of the newly constructed index on stock returns and volatility. According to our findings, investor sentiment positively (negatively) predicts the stock return (volatility) during the COVID-19. This is the first study assessing global sentiment by proposing a novel proxy and its impacts on the G20 equity market.

The role of precious metals in portfolio diversification during the Covid19 pandemic: A wavelet-based quantile approach

In this study the relation between stock markets and precious metals during first wave of Covid-19 pandemic are investigated. We use a wavelet-based quantile procedure to investigate correlation between major stock markets of emerging countries (BRIC) and the United States. Our procedure reveals that precious metals offer market diversification opportunities during the period under consideration. In particular, it is found the gold, silver, platinum, and palladium, all serve as safe-haven assets during periods of market distress across short, medium and long investment horizons.

Stock market reactions to COVID-19 lockdown: A global analysis

The COVID-19 pandemic has caused dramatic changes in the way people around the globe live, and has had a profound negative impact on the global economy. Much of this negative impact did not result from the disease itself, but from the lockdown restrictions imposed to contain the spread of the virus. We investigate how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020. We find that lockdown restrictions led to different reactions in our sample of OECD and BRICS countries: there was a general negative effect resulting from the increase in lockdown restrictions, but we find strong evidence for underreaction during the lockdown announcement, followed by some overreaction that is corrected subsequently. This under-/overreaction pattern, however, is observed mostly during the first half of our time series, pointing to learning effects. Relaxation of the lockdown restrictions, on the other hand, had a positive effect on markets only during the second half of our sample, while for the first half of the sample, the effect is negative.

Does the Covid-19 pandemic affect faith-based investments? Evidence from global sectoral indices

In this paper, we aim to investigate the influence of the Covid-19 on the behavior of the S&P 1200 Shariah and non-Shariah sectoral indices over the period from 1st October 2010 to 29th October 2020. We contribute to the global literature by examining the financial impact of the Covid-19 on the Shariah and non-Shariah sectoral indices. We find that the S&P 1200 Shariah Communication, consumer staples, financials, healthcare, industrials, IT, materials, and utility sectors earn higher average returns than their counterpart sectoral indices during the Covid-19 period. The study reports that on average, the volatility of the Shariah indices is less than their counterpart indices. Moreover, we further document that on average the S&P Shariah sectoral indices offer a higher return with low risk even during the Covid-19 global pandemic. We suggest that ethical investments are the best alternatives to retail, institutional, and foreign investors.

Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic

This study sets out to provide fresh evidence on the dynamic interrelationships, at both return and volatility levels, between global equity, gold, and energy markets prior to and during the outbreak of the novel coronavirus. We undertake our analysis within a bivariate GARCH(p, q) framework, after orthogonalizing raw returns with respect to a rich set of relevant universal factors. Under the COVID-19 regime, we find bidirectional return spillover effects between equity and gold markets, and unidirectional mean spillovers from energy markets to the equity and gold counterparts. The results also suggest the presence of large reciprocal shock spillovers between equity and both of energy and gold markets, and cross-shock spillovers from energy to gold markets. Most probably driven by the recent oil price collapse, energy markets appear to have a substantial cross-volatility spillover impact on the others. Our results offer implications for policymakers and investors.

The day after tomorrow: financial repercussions of COVID-19 on systemic risk

In this paper, we study the financial repercussions of COVID-19 and the effect of anti-epidemic measures on financial markets. By using a composite dataset containing stock market indices of 10 countries characterized by heterogeneous levels of contagion, the daily COVID-19 cases and the 108 more restrictive measures implemented to limit the virus from 31/12/2019 to 13/03/2020, we examine the emergence of financial systemic risk, its speed of propagation and the effectiveness of the policies implemented to curb it. On the one hand, the spread of contagion and its transmission on financial markets are investigated via a lagged cross-correlation analysis. Our results show the emergence of systemic risk characterized by a high speed of diffusion. On the other hand, an augmented AR(1)-EGARCH(1,1) model is applied to examine the impact of anti-COVID-19 "policies on financial markets. We show that, regardless of the level of contagion, the restrictive measures are not able to contain the virus-induced investors panic in the first months of the epidemic.

Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets

The SARS-CoV-2 epidemics outbreak has shocked global financial markets, inducing policymakers to put in place unprecedented interventions to inject liquidity and to counterbalance the negative impact on worldwide financial systems. Through the lens of statistical physics, we examine the financial volatility of the reference stock and bond markets of the United States, United Kingdom, Spain, France, Germany and Italy to quantify the effects of country-specific socio-economic and political announcements related to the epidemics. Main results show that financial markets exhibit heterogeneous behaviours towards news on the epidemics, with the Italian and German bond markets responding with major delays to shocks. Additionally, credit markets tend to be slower than equity markets in adjusting prices after shocks, hence being slower at incorporating the effects of such news.

Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic

This research examines the behaviour of cryptocurrencies and stock markets during the COVID-19 pandemic through the wavelet coherence approach and Markov switching autoregressive model. Our results show a financial contagion in March, since both cryptocurrency and stock prices fell steeply. Despite this turn-down, cryptocurrencies promptly rebounded, while stock markets are trapped in the bear phase. In other words, we observe that the price dynamics during the pandemic depends on the type of the market. These findings are relevant for investors since some hedging properties can be found in the cryptocurrency response to such a drastic event.

Stock market comovements: Evidence from the COVID-19 pandemic

The COVID-19 pandemic shock has harmed the US and East Asian stock markets. Focusing on measuring the inherent correlation, this paper employs a GARCH-Copula CoVaR approach to address the debate on the extreme risk spillovers from the US to China, Japan, Hong Kong, and South Korea stock returns. The results show a large spillover effect from the US to East Asian stock markets. Compared to the tranquil period, these spillovers become stronger in the COVID-19 period. The findings show that indirect spillovers on the Chinese stock market are heavier than direct spillovers, and impacts deluge only via Hong Kong. The study contrasts spillover' features of the US COVID-19 shock and the Chinese 2015 crisis. These findings provide useful support for policymakers and risk managers involved in the East Asian stock markets.

Stock price reaction to appointment of a chief health officer during COVID-19

This study examines how appointing a chief health officer (CHO) at the corporate-board level during the COVID-19 outbreak affects the stock returns of US firms. As the COVID-19 progressed, the negative abnormal return (CAR) is -7.5%. In contrast, shares of firms that had appointed a CHO before or during the window surrounding the date of the first reported COVID-19 case (the WHO declaration) exhibited positive CAR of ＋6.29% (＋0.136%). CARs surrounding the exact CHO appointment date once the COVID-19 had already broken out the effect was even stronger, ＋6.91%. Size, leverage, growth, and R&D intensity influence significantly returns during the outbreak.

Investor attention on COVID-19 and African stock returns

We examine the financial consequences of rising global investor attention or risk attitude related to the COVID-19 pandemic for African stock markets. Using daily investor attention indices, which are based on global COVD-19-related google search queries, and stock return indices for 14 African stock markets, we show that investor attention is an important determinant of stock returns. Our estimates suggest that an increase in investor attention consistently reduces stock returns in three stock markets, namely Botswana, Nigeria, and Zambia. In contrast, an increase in investor attention may enhance stock returns in Ghana and Tanzania. Our estimates imply that, in uncertain times like the current pandemic, stock markets like those of Ghana and Tanzania may offer potential diversification benefits to investors. We demonstrate that our estimates are broadly robust using a composite measure of investor attention.•

We built a direct and unambiguous measure of investor attention or risk attitude related to the COVID-19 pandemic.

•

In an exponential generalised autoregressive heteroskedasticity of order one (i.e. EGARCH(1,1)) framework, we regressed stock returns on their first lags, investor attention, exchange rate returns, and commodity returns, and controlled for investor attention in the variance equation.

World equity markets and COVID-19: Immediate response and recovery prospects

Following the spread of the COVID-19 pandemic, most global equity market indices experienced significant falls. Recognizing the severe economic impacts of the pandemic, starting from mid-March, many governments announced unprecedented economic rescue packages, which appear to restore investors' confidence, given the recoveries recorded in most stock markets. However, the recovery performance significantly varies across countries. This paper provides an empirical analysis on what may explain this variation in the recovery performance observed in equity markets across countries. We find that among different types, fiscal stimulus supports seem to be strongly and positively associated with higher recovery that may justify more targeted fiscal supports for the real sector firms to restore investors' confidence. We also find that the severity of the outbreak, reliance more on natural resource and tourism revenues are negatively associated with countries' stock market recovery performance.

Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter?

This study investigates the dynamic connectedness between stock indices and the effect of economic policy uncertainty (EPU) in eight countries where COVID-19 was most widespread (China, Italy, France, Germany, Spain, Russia, the US, and the UK) by implementing the time-varying VAR (TVP-VAR) model for daily data over the period spanning from 01/01/2015 to 05/18/2020. Results showed that stock markets were highly connected during the entire period, but the dynamic spillovers reached unprecedented heights during the COVID-19 pandemic in the first quarter of 2020. Moreover, we found that the European stock markets (except Italy) transmitted more spillovers to all other stock markets than they received, primarily during the COVID-19 outbreak. Further analysis using a nonlinear framework showed that the dynamic connectedness was more pronounced for negative than for positive returns. Also, findings showed that the direction of the EPU effect on net connectedness changed during the pandemic onset, indicating that information spillovers from a given market may signal either good or bad news for other markets, depending on the prevailing economic situation. These results have important implications for individual investors, portfolio managers, policymakers, investment banks, and central banks.

The unprecedented reaction of equity and commodity markets to COVID-19

Using a drifting spillover index approach (Diebold and Yilmaz, 2012) and a continuous time-frequency tool (Torrence and Webster, 1999), this paper attempts an empirical investigation of the spillovers and co-movements among commodity and stock prices in the major oil-producing and consuming countries. While our results point to the existence of a significant interdependence among the markets considered, Chinese and Saudi Arabian stock markets seem to be weakly integrated into the world market. Moreover, the spillovers are time-varying and reached their highest levels during the COVID-19 medical shock.

Stock markets and the COVID-19 fractal contagion effects

This article investigates the fractal contagion effect of the COVID-19 pandemic on the stock markets. The stock market information of the top 32 coronavirus affected economies (as of 31st March 2020) was sampled for ex-ante and ex-post COVID-19 outbreak analysis using the Detrended Moving Cross-Correlation Analysis (DMCA) and Detrended Cross-Correlation Analysis (DCCA) techniques. The results confirm a fractal contagion effect of the COVID-19 pandemic on the stock markets. Furthermore, this fractal contagion effect fizzles out over time (in the middle and long run) for both the stock markets return and volatility. Therefore, this article provides pieces of evidence for the COVID-19 fractal contagion effect on the stock markets.

COVID-19 lockdowns, stimulus packages, travel bans, and stock returns

This paper examines the effect of government responses of G7 countries to the coronavirus pandemic (COVID-19) on stock market returns. Using time-series data, we show that lockdowns, travel bans, and economic stimulus packages all had a positive effect on the G7 stock markets. However, lockdowns were most effective in cushioning the effects of COVID-19. Our results are robust to different measures of returns and controls for other factors of returns.

Regime Shifts in the Behaviour of International Currency and Equity Markets: A Markov-Switching Analysis

This paper examines regime switching behaviour and dynamic linkages among currency and equity markets of Eurozone, India, Japan and U.S. using a Markov-switching framework. First, we seek to characterize the market specific and common regime shifts in international stock and currency markets. Second, we aim to study regime-dependent conditional correlations across these markets. We estimate state-dependent models for the financial markets in a univariate Markov-switching Autoregression (MS-AR) as well as a multivariate Markov-switching Vector Autoregression (MS-VAR) framework. The paper utilizes weekly data from July, 1999 to October, 2020 to model the interactions among the markets. Our univariate results identify two-states viz. bull state (bear state) characterized by high returns (low returns) and low volatility (high volatility) for the stock market indices and Euro/USD and INR/USD returns. For the Yen/USD market the bull state corresponds to depreciation accompanied by low volatility. Further, we employ a multivariate formulation to study the regimes across asset classes which provides additional insights into the common states across the markets. Using the MS-VAR model encompassing stocks and currencies, we find a tranquil regime characterized by lower volatility and higher returns and a turbulent regime depicted by higher volatility and lower returns. Contemporaneous correlations among asset market pairs are sharper during the crises. Some of the turbulent periods highlighted in the analysis include the dot-com bubble burst, South American crisis, 9/11, Iraq war, housing bubble burst, global financial crisis, Eurozone debt crisis, Taper Tantrum, Brexit, U.S. Federal Government Shutdown, U.S.-China Trade War and the recent COVID-19 pandemic.

Predicting the European stock market during COVID-19: A machine learning approach

This research attempts to explore the total of 21 potential internal and external shocks to the European market during the Covid-19 Crisis. Using the time series of 1 Jan 2020 to 26 June 2020, I employ a machine learning technique, i.e. Least Absolute Shrinkage and Selection Operator (LASSO) to examine the research question for its benefits over the traditional regression methods. This further allows me to cater to the issue of limited data during the crisis and at the same time, allows both variable selection and regularization in the analysis. Additionally, LASSO is not susceptible to and sensitive to outliers and multi-collinearity. The European market is mostly affected by indices belonging to Singapore, Switzerland, Spain, France, Germany, and the S&P500 index. There is a significant difference in the predictors before and after the pandemic announcement by WHO. Before the Pandemic period announcement by WHO, Europe was hit by the gold market, EUR/USD exchange rate, Dow Jones index, Switzerland, Spain, France, Italy, Germany, and Turkey and after the announcement by WHO, only France and Germany were selected by the lasso approach. It is found that Germany and France are the most predictors in the European market.•A LASSO approach is used to predict the European stock market index during COVID-19•European market is mostly affected by the indices belonging to Singapore, Switzerland, Spain, France, Germany, and the S&P500 index.•There is a significant difference in the predictors before and after the pandemic announcement by WHO.

The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets

We explore the evolution of the informational efficiency in 45 cryptocurrency markets and 16 international stock markets before and during COVID-19 pandemic. The measures of Largest Lyapunov Exponent (LLE) based on the Rosenstein's method and Approximate Entropy (ApEn), which are robust to small samples, are applied to price time series in order to estimate degrees of stability and irregularity in cryptocurrency and international stock markets. The amount of regularity infers on the unpredictability of fluctuations. The t-test and F-test are performed on estimated LLE and ApEn. In total, 36 statistical tests are performed to check for differences between time periods (pre- versus during COVID-19 pandemic samples) on the one hand, as well as check for differences between markets (cryptocurrencies versus stocks), on the other hand. During the COVID-19 pandemic period it was found that (a) the level of stability in cryptocurrency markets has significantly diminished while the irregularity level significantly augmented, (b) the level of stability in international equity markets has not changed but gained more irregularity, (c) cryptocurrencies became more volatile, (d) the variability in stability and irregularity in equities has not been affected, (e) cryptocurrency and stock markets exhibit a similar degree of stability in price dynamics, whilst finally (f) cryptocurrency exhibit a low level of regularity compared to international equity markets. We find that cryptos showed more instability and more irregularity during the COVID-19 pandemic compared to international stock markets. Thus, from an informational efficiency perspective, investing in digital assets during big crises as the COVID-19 pandemic, could be considered riskier as opposed to equities.

Examining the asymmetric effects of stock markets and exchange rate volatility on Pakistan's environmental pollution

The purpose of this study is to observe the effects of stock markets and exchange rate volatility on environmental pollution in Pakistan during the period 1985-2018. A nonlinear autoregressive distributed lag (ARDL) model is applied to get this objective. In general, the short-term results revealed that the positive and negative shocks in stock markets reducing the carbon emissions. In adverse, positive shocks in exchange rate volatility reduces the carbon emissions while negative shocks in exchange rate volatility have a positive significant effect on carbon emissions in Pakistan. Moreover, the positive and negative shocks in the stock market have a positive significant effect on Pakistan's carbon emissions but positive and negative shocks in exchange rate volatility negative influence on carbon emissions in the long run. The findings further show that positive and negative shocks of the stock markets and exchange rate volatility have the same effects in sign but different in magnitude in the long run. Based on these findings, some policy recommendations proposed in the context of Pakistan as well as for other developing countries.

Dynamic links between the Nigerian equity market and those of selected regional and developed countries

The dynamic and growing interdependent nature of equity markets across the world has elicited the interest of investors and researchers alike. This study examines the dynamic interactions between the Nigerian stock market and selected regional and global equity markets spanning eight years, from 2011 to 2018, using daily index data. The generalised impulse response function was used alongside the Toda and Yamamoto Granger causality test to investigate the short-run dynamic linkages, while the normalized Johansen vector error correction estimates served to assess the long-run linkages given the existence of cointegration. Findings from the study revealed that the UK and the Ghanaian stock markets exert significant long-run impact on the Nigerian stock market, while vagaries from the US tend to exert more influence on the Nigerian stock market in the short-run. The study recommends that more regional efforts are needed to enhance the integration of stock markets in West Africa. The findings have implications for national and regional policymakers as well as portfolio investors.

Do industrial incidents in the chemical sector create equity market contagion?

INTRODUCTION

This paper examines a number of US chemical industry incidents and their effect on equity prices of the incident company. Furthermore, this paper then examines the contagion effect of this incident on direct competitors.

METHOD

Event study methodology is used to assess the impact of chemical incidents on both incident and competitor companies.

RESULTS

This paper finds that the incident company experiences deeper negative abnormal returns as the number of injuries and fatalities as a result of the incident increases. The equity value of the competitor companies suffer substantial losses stemming from contagion effects when disasters that occur cause ten or more injuries and fatalities, but benefit from the incident through increasing equity value when the level of injury and fatality is minor.

CONCLUSIONS

Presence of contagion suggests collective action may reduce value destruction brought about by safety incidents that result in significant injury or loss of life.

PRACTICAL APPLICATIONS

This research can be used as a resource to promote and justify the cost of safety mechanisms within the chemical industry, as incidents have been shown to negatively affect the equity value of the not just the incident company, but also their direct competitors.