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The purpose of this paper is to examine volatility transmissions between portfolios of cross‐listed equities and exchange rate differences and also the volatility persistence for home, foreign equities, and exchange rate differences in the UK and German markets.

A primary focus of this paper is to see if there is an impact first on the volatility persistence for foreign equities that are listed in the UK and German markets, second on the respective home portfolios of cross‐listed equities, and third on the exchange rate differences. In addition, whether there are any bilateral spillovers between the following equity portfolios: foreign cross‐listed equities, home cross‐listed equities, and also local or global exchange rate differences are investigated.

The paper finds that the volatility persistence is more prominent than error persistence from cross‐listed equities, foreign or home, and the exchange rate differences. Furthermore, the transmission mechanism indicates a bilateral integration process in some of the cases that were examined. Based on these results, it is concluded that in the UK market the foreign cross‐listings affect less the domestic equities compared to the German market.

This paper examines the interdependence of portfolios of home and foreign equities for cross‐listings that belong to the same stock exchange with two exchange rates, a local and a global one in order to provide more evidence in this area of literature.

The purpose of this paper is to estimate volatility in African stock markets (ASMs), taking account of periodic level shifts in the mean level of volatility, where the regime shifts are determined endogenously.

Volatility estimates are incorporated into standard volatility models to assess the impact of structural breaks on volatility persistence, long memory and forecasting performance for ASMs.

The results presented here indeed suggest that persistence and long memory in volatility are overestimated when regime shifts are not accounted for. In particular, application of breakpoint tests and a moving average procedure suggest that unconditional volatility displays substantial time variation.

A modification of the standard generalised autoregressive conditional heteroscedasticity model to allow for time variation in the unconditional variance generates improved volatility forecasting performance for some African markets.

This paper describes one of the first studies to incorporate endogenously determined regime shifts into volatility estimates and assess the impact of structural breaks on volatility persistence, long memory and forecasting performance for ASMs.

The aim of this study is to compare volatility persistence with daily volatility and to analyze the asymmetry effect of volatilities in stock markets of emerging economies. Using daily observations of stock market indices of selected major emerging countries during the period of January 1, 2002 to December 31, 2018, the authors estimate the persistence, the half-life measure of volatility and the daily volatility of the return series using the GARCH model application. The authors also examine the leverage effect on stock market returns using the EGARCH model estimation. In addition, the authors investigate the impact of the 2008 global financial crisis on various volatility measures and the leverage effect of emerging stock market returns. The authors then examine and compare the different speeds of mean reversion, volatility persistence and leverage effects in the national stock market indices during the pre-crisis, crisis, and post-crisis periods. The authors hereby present evidence that the effects of negative shocks are significantly larger than those of positive shocks in emerging stock markets throughout their different sample periods.

There is growing demand for research approaches that consider the functioning of financial markets in the emerging economy. The current paper aims to examine cointegration and volatility persistence of six Middle East emerging Arabian Gulf Cooperation council (AGCC) equity markets with developed markets.

The study uses the MGARCH and VAR methodology to analyze the cointegration and volatility spillover across emerging AGCC markets and developed markets. Time series stock return data for six AGCC countries from February 2003 to January 2006 are used from Shuaa Capital Market together with MSCI world developed market index.

The study shows that AGCC markets exhibit significant own and cross spillover of innovations and volatility spillover and persistence in these markets. Emerging markets in AGCC derive relatively more of their innovations and volatility persistence from within the domestic market.

The results imply that, emerging AGCC markets are susceptible to conditions within the AGCC region. This increases potential benefits of international diversification for international investors. The study findings have implications for security pricing within AGCC markets, for hedging and other trading strategies, and for regulatory polices conducted within financial markets.

The paper provides empirical evidence and justification for investors, both individual and foreign institutional, to adjust their portfolios through diversification.

This paper aims to analyze and give directions for advancing research in stock market volatility highlighting its features, structural breaks and emerging developments. This study offers a platform to research the benchmark studies to know the research gap and give directions for extending future research.

The author has performed the literature review, and, reference checking as per the snowballing approach. Firstly, the author has started with outlining and simplifying the significance of the subject area, the review illustrating the various elements along with the research gaps and emphasizing the finding.

This work summarizes the studies covering the volatility, its properties and structural breaks on various aspects such as techniques applied, subareas and the markets. From the review’s analysis, no study has clarified the supremacy of any model because of the different market conditions, nature of data and methodological aspects. The outcome of this research work has delivered further magnitude to research the benchmark studies for the upcoming work on stock market volatility. This paper has also proposed the hybrid volatility models combining artificial intelligence with econometric techniques to detect noise, sudden changes and chaotic information easily.

The author has taken the research papers from the scholarly journal published in the English language only and the author may also consider other nonscholarly or other language journals.

To the best of the author’s knowledge, this research work highlights an updated and more comprehensive framework examining the properties and demonstrating the contemporary developments in the field of stock market volatility.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

The purpose of this paper is to examine the nature of equity ownership of state-owned enterprises (SOEs) for over 2,000 listed firms in China. The paper examines both the pattern of state ownership and the dynamics of stock returns and volatility. Firms under the control of SOEs dominate the Chinese stock markets and currently account for over three-quarters of total market capitalisation. Central SOEs are focused in strategic industries, while Local SOEs concentrate on pillar industries relating to consumer goods and services.

The authors obtain firm-level data from the Shanghai and Shenzhen stock markets and using panel estimation techniques examine the dynamics of returns, volatility and their relationship.

The authors report an increase in state control among listed firms compared to earlier reported figures. This is contradictory to the expectation of a lower state influence following China joining of the World Trade Organisation in 2001. In examining the behaviour of stock returns the authors find evidence of daily and monthly autocorrelations that are larger and of a different sign to that reported for western markets. The authors also report evidence of volatility persistence but little evidence of volatility asymmetry, again in contrast to that often reported for other markets. Finally, the authors find evidence of either no or a negative relationship between returns and volatility (risk) that differs from our usual view of risk aversion.

It is hoped, knowledge of these dynamics will increase the understanding of the Chinese equity market, which in turn is important for those engaged in international portfolio management and micro-structure modelling.

The purpose of this paper is to examine the evidence of long-range dependence behaviour in both house price returns and volatility for fifteen main regions in Finland over the period of 1988:Q1 to 2018:Q4. These regions are divided geographically into 45 cities and sub-areas according to their postcode numbers. The studied type of dwellings is apartments (block of flats) divided into one-room, two-rooms, and more than three rooms apartments types.

For each house price return series, both parametric and semiparametric long memory approaches are used to estimate the fractional differencing parameter d in an autoregressive fractional integrated moving average [ARFIMA (p, d, q)] process. Moreover, for cities and sub-areas with significant clustering effects (autoregressive conditional heteroscedasticity [ARCH] effects), the semiparametric long memory method is used to analyse the degree of persistence in the volatility by estimating the fractional differencing parameter d in both squared and absolute price returns.

A higher degree of predictability was found in all three apartments types price returns with the estimates of the long memory parameter constrained in the stationary and invertible interval, implying that the returns of the studied types of dwellings are long-term dependent. This high level of persistence in the house price indices differs from other assets, such as stocks and commodities. Furthermore, the evidence of long-range dependence was discovered in the house price volatility with more than half of the studied samples exhibiting long memory behaviour.

Investigating the long memory behaviour in both returns and volatility of the house prices is crucial for investment, risk and portfolio management. One reason is that the evidence of long-range dependence in the housing market returns suggests a high degree of predictability of the asset. The other reason is that the presence of long memory in the housing market volatility aids in the development of appropriate time series volatility forecasting models in this market. The study outcomes will be used in modelling and forecasting the volatility dynamics of the studied types of dwellings. The quality of the data limits the analysis and the results of the study.

To the best of the authors’ knowledge, this is the first research that assesses the long memory behaviour in the Finnish housing market. Also, it is the first study that evaluates the volatility of the Finnish housing market using data on both municipal and geographical level.

The purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.

To estimate the volatility and capture the stylized facts of fat‐tail distribution, volatility clustering, leverage effect, and mean‐reversion in futures returns, appropriate ARMA‐generalized autoregressive conditional heteroscedastic (GARCH) and ARMA‐EGARCH models with generalized error distribution have been used. The ARMA‐EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time‐varying conditional volatility.

The paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish.

Research findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume‐price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions.

Equity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set.

The purpose of this paper is to examine the short‐term and long‐term stock price volatility changes around bonus and rights issue announcements, using historical volatility estimation and time varying volatility approach.

Changes in volatility around bonus and rights issues have been examined using the following methodologies. First, to capture historical volatility, change in standard deviation for 20 days and 100 days before and after announcement have been examined. Second, change in time varying volatility and unconditional volatility is examined using GARCH (1, 1) model.

The results indicate that the historical volatility has increased after bonus and rights issue announcement. The volatility persistence and unconditional variance have increased after the bonus and rights issue announcements. This evidence, extendable to any other type of issue announcement, is consistent with theories stating that volatility increases after the seasoned capital issue announcements.

This study analyses historical volatility, volatility persistence and unconditional volatility around bonus and rights issue announcements, which has not been observed in the previous literature. This study fills the gap in literature by empirically examining the change in short‐ and long‐term volatility before and after bonus and rights issue announcements. Moreover, measuring volatility using GARCH model overcomes the potential problem of heteroscedasticity associated with cross‐sectional data. The change in volatility persistence and unconditional volatility before and after the announcement are also examined. This study is useful for researchers and practitioners specialized in finance, international business and management, and professionals in the area of commercial policy development in emerging markets.