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The purpose of this paper is to investigate the short‐run return and volatility spill‐overs across three major international copper futures markets: London Metal Exchange (LME), New York Mercantile Exchange (NYMEX), and Shanghai Futures Exchange (SHFE).

The analysis utilizes a dynamic conditional correlation GARCH model to explore the return and volatility relationships.

The return and volatility spill‐overs between the two developed markets, LME and NYMEX, are bi‐directional and significantly stronger when the NYMEX operates an electronic trading system. In addition, significant bi‐directional return spill‐over between the LME (developed market) and the SHFE (emerging market) and significant uni‐directional volatility spill‐over from the LME to the SHFE are documented.

The evidence suggests that degree of market integration and trading mechanism play crucial roles in the return and volatility transmission across the three major copper futures markets. Higher level of market integration and easy access to trading information lead to faster information dissemination and help to establish stronger relationships of returns and volatility across the markets. This is consistent with the findings in the equity markets.

The study provides empirical evidence of short‐run information transmission between developed and emerging copper futures markets.

This paper aims to examine the dynamic of volatility of Malaysian listed property companies within pan-Asian public property markets based on different volatility perspective over the past 18 years, especially during the global financial crisis (GFC).

This study uses several statistical methods and formulas for analysing the dynamic of volatility of Malaysian listed property companies such as exponential generalised autoregressive conditional heteroscedasticity (EGARCH) and Markov-switching (MS) EGARCH. The MS-EGARCH model provides new insights on the volatility dynamics of Malaysian listed property companies compared to conventional volatility modelling techniques, particularly EGARCH. Additionally, this paper will analyse the volatility movement based on three different sub-periods such as pre-GFC, GFC and post-GFC.

The findings reveal that the markets perform differently under different volatility conditions. Moreover, the application of MS-EGARCH provides a different view on the volatility dynamics compared to the conventional EGARCH model, as MS-EGARCH provides more comprehensive findings, especially during extreme market conditions.

This study contributes to the literature on the dynamics of Malaysian listed property companies within pan-Asian countries, as the approach for assessing the volatility performance based on different volatility conditions is less explored by previous researchers.

We analyze the dynamic behavior of the volatility of KTB futures price through GARCH models. In conducting this analysis we use two type data. Using dailly data we analyze the return and volatility spill-over effect between KTB spot and futures. Through 15-minute and 5-minute data we analyze return and volatility spill-over effect between KTB futures and won/dollar futures. We find that ARCH and GARCH effect exists in the volatility of KTB futures, but leverage effect does not exist in this data. Volatility spill-over effect was found only in 15-minute data. Lead and lag effect was found in 15-minute data of dollar and KTB futures where dollar return leads KTB futures and KTB volatility leads dollar volatility. In the daily data we found that KTB futures return lead KTB spot return while mutual spill-over existed between spot and futures in volatility data. Since conditional heteroscedasticity exists in KTB futures we need to consider the these effects in building up systems for arbitrage, valuation and risk management.

The purpose of this article is to examine the impact of panic and hysteria news on the volatility of microchip stocks during Covid-19.

The authors use the P-GARCH (1,1) and random effects regression to model/examine the impact of Covid-19 panic and hysteria news on the overall microchip sector and individual firms. They further utilize the SVAR model to examine volatility spill-over from the microchip sector to the automobile and main technology sectors. Their time frame ranges from 6th January 2020 to 30th June 2021 to capture the effects of both waves of Covid-19.

The study results firstly reveal that Covid-19 panic and hysteria news have tremendous potential to model the volatility of microchip sector stock thus confirming the information discovery hypothesis. The authors secondly demonstrate the influence of Covid-19 cases, deaths and policy stringency on stock returns of individual microchip companies in different countries. Finally the authors confirm the presence of volatility spill-over from the microchip sector to other technology sectors.

The authors provide evidence to support the profundity of bad news in predicting stock behavior. The study results depict how Covid-19 has affected microchip stocks so that policy initiatives can be taken to protect the industry. The presence of volatility spill-over signifies the importance of diversifying portfolios by mixing technology and non-technology stocks.

The research strand on Covid-19 and individual sectoral stocks has received limited scholarly attention despite unparallel effects of the pandemic on different sectors.

BRICS (Brazil, Russia, India, China, and South Africa) a group of five emerging nations that are expected to lead the global economy by the year 2050. The growth potential of these nations attracts investors from all over the world who are in search of maximizing the return on their investments and limiting the losses to the lowest possible level. The purpose of this research study is to determine whether or not Indian stock market investors can diversify their stock market portfolios into other BRICS economies.

A daily frequency of stock market closing data for the BRICS nations over a period of 2013–2021 has been considered and several econometric techniques have been applied. Starting with the Granger causality test for checking the direction of causality. The VAR technique is applied to find out whether the movement in the Indian stock market is influenced by its own past values or the past values of the other BRICS nations, and lastly, the DCC-MGARCH technique is applied to check the degree of integration or the volatility spillover from the Indian stock market to the stock markets of other BRICS nations.

The results of the study indicated that in both the short term and long term, stock market volatility is spilling over from the Indian stock market to the stock markets of other BRICS nations. Hence, the study suggests that BRICS nations cannot be a destination for portfolio diversification for Indian stock market investors.

The stock markets of emerging nations experience high volatility, which creates confusion for investors as to whether to invest or to abstain from portfolio diversification. At present, there is a gap in the existing literature to capture the stock market volatility of BRICS nations. This research study fills this research gap and confirms that BRICS nations cannot be a destination for portfolio diversification. Moreover, equity market experts, portfolio managers and researchers can all take advantage of this study.

The purpose of this paper is to investigate the linkages among equity exchange traded funds (ETF) returns and transmission of volatilities of the USA, Europe and key emerging countries’ stock markets. Standard & Poor’s 500 (spy) and iShares Europe are used to represent the USA and European stock markets, the emerging market part of the data set consists of daily returns of equity ETF representing broad equity market indices of the BRIC countries (Brazil, Russia, India and China); the mist countries (Mexico, Indonesia, South Korea and Turkey) and South Africa and covers the period of February 3, 2012-February 28, 2014.

The paper utilizes multi-variate auto-regressive moving-averages (MARMA) methodology to study equity market returns and spillovers. Second, generalized auto-regressive conditional heteroskadasticity (GARCH) modeling is employed to model volatility persistence and transmissions.

The findings include the existence of significant co-movement of returns among all country ETFs; however, despite increasing interdependencies among the global stock markets there are still very good opportunities for diversification. For example, USA and Europe based investors may do well to ignore opportunities in each other’s markets but can realize diversification benefits by investing in ETFs representing China, South Africa and Turkey. As far as volatilities are concerned, the findings indicate that no ETF volatility is transmitted from the sample countries to USA, Brazil, China and South African stock markets. Also, US market volatility is transmitted to India, Russia, Mexico and Turkey while European volatility spills over to Mexico and South Korea. The presence of spillovers among stock markets’ return series and persistence of volatilities are useful to investors interested in diversifying their portfolios and to traders/fund managers who are interested in maximizing returns.

The implications include: first, investors should not only rely on current domestic news to guide their investment decisions, but also take into consideration international news for there are substantial spillovers. Second, given that volatilities can proxy for risk, there are lessons for both individual and institutional investors in terms of further examining pricing securities, hedging and other trading strategies as well as framing regulatory policies. Third, investors should be able to ride the financial cycle by following closely monetary policies of the FED and European Central Bank and resulting credit expansion or contraction since research indicates (and as corroborated in this study) equity prices are linked to VIX which is also correlated with capital flows and credit expansion and interest rates. Limitations include: first, the investigation could be expanded to include individual countries in Europe instead of using one Europe-wide ETF. As ETFs for other emerging markets become available it is also possible to include additional countries. Second, ETFs may not be the best vehicles for diversification.

Methodology (MARMA and GARCH) is widely used for analyzing financial data. The use of BRIC and MIST countries and the interaction among them may be novel. Spillovers among emerging financial markets is a fairly new area. Typically, the authors see studies of spillovers from the developed countries to the developing ones. The data period is important since it covers both credit expansion and contraction (or the start of it) by the FED and is current.

The purpose of this paper is to investigate the volatility linkage between global oil market and major South Asian equity markets.

In order to serve the purpose, the authors employ a recently developed vector autoregressive-generalized autoregressive conditional heteroskedastic model to examine whether shocks and volatility spill over from the oil market to various equity markets under consideration.

The findings of the empirical analysis suggest that all the markets studied do receive volatility from the oil market. Not surprisingly, the authors do not find any significant evidence of volatility transmission from the equity markets to the global oil market. Additionally, while computing the optimal portfolio weights and hedge ratios, the authors document that inclusion of oil in the portfolio of stocks tends to reduce the risk of the resultant portfolio.

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This study aims to test the mean and volatility spill over from the environmental, social, and governance (ESG) market to the stock markets of G7 countries. The study used ARMA-GARCH model to predict the results. The findings of the study reveal that as the spill over exists in the markets, however the mean volatility does not exist showing efficiency of the market as significant results depict that past prices cannot predict the future prices. It provides new insights for the international portfolio investors and policymakers by shedding light on how cross-markets correlate in two different markets.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.

This study analyzes the maturity structure of the volatility in the KOSPI200 index and futures returns. Using bivariate GARCH model, we obtain the empirical evidences that the maturity structure of the volatility is U-shaped unlike the well-known Samuelson effect. Remarkably. U-shaped structures are found not only in the futures market but also in the spot market These evidences imply that returns are more volatile around tile futures maturity date in both markets.

Some explanations are suggested about U-shaped maturity structures. First, under Samuelson hypothesis it is possible to show that the volatilities are high around the maturity date because of the volatility clustering and the volatility spill-over. Second, we try the regression of the volatility on variables such as the proportion of the individual investors, the foreign investors, and the program trading. These variables are U-shaped or inverse U-shaped due to the remaining maturity. Only before 2000, it is found that the proportions of the foreign investors and the program trading are compatible with U-shaped volatility structures.