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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.

This paper aims to propose a general, yet simple model to estimate interest rate volatility.

The methodology is based on an extended Exponential Generalized ARCH (EGARCH) model that incorporates both interest rate levels as well as past information shocks in the volatility function. More importantly, the model is log‐linear thus eliminating collinearity problems and it can be easily estimated using standard maximum likelihood techniques.

The empirical evidence suggests that the elasticity of volatility to the level of interest rates, although statistically significant, is not as high numerically as previously thought. In fact innovations in the interest rate process are more significant than the level of interest rates. The most important feature of interest rates, however, is the high volatility persistence.

A limitation of the model is that it does not allow for structural shifts in its current form. Extending the model to accommodate possible shifts would probably improve the performance as well the forecasting accuracy.

The findings in this paper have important implications for the accurate pricing of fixed income derivative securities as well as the efficient risk management of fixed income portfolios.

The paper provides a convenient and unifying methodological framework for assessing the importance and forecasting ability of the various volatility components.

The purpose of this paper is to examine the hypothesis of feedback trading along with the short-term return dynamics of three size-based stock portfolios of Athens Stock Exchange during the Greek debt crisis period.

To this end, the authors employ for the first time in the literature two well-known models while the variance equation is modeled by means of a multivariate EGARCH specification. As a robustness test an innovative nested-EGARCH model is also employed.

The assumption that positive feedback trading is an important component of the short-term return movements across the three stock portfolios receives significant support. Moreover, the volatility interdependence, both in magnitude and sign, is almost similar across the three models. Finally, bad news originating from the portfolio of small stock appears to have a higher impact on the volatility of large and medium size stock returns than good news during the Greek debt crisis period.

The methodology is innovative and the authors test for the first time the feedback trading hypothesis across different size stocks. The authors believe that the results might entail significant policy implications for investors and market regulators.

The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility.

The competing models are the autoregressive moving average (ARMA) model and autoregressive fractional integrated moving average (ARFIMA) model for house price returns. For house price volatility, the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model is competing with the fractional integrated GARCH (FIGARCH) and component GARCH (CGARCH) models.

Results reveal that, for modelling Finnish house price returns, the data set under study drives the performance of ARMA or ARFIMA model. The EGARCH model stands as the leading model for Finnish house price volatility modelling. The long memory models (ARFIMA, CGARCH and FIGARCH) provide superior out-of-sample forecasts for house price returns and volatility; they outperform their short memory counterparts in most regions. Additionally, the models’ in-sample fit performances vary from region to region, while in some areas, the models manifest a geographical pattern in their out-of-sample forecasting performances.

The research results have vital implications, namely, portfolio allocation, investment risk assessment and decision-making.

To the best of the author’s knowledge, for Finland, there has yet to be empirical forecasting of either house price returns or/and volatility. Therefore, this study aims to bridge that gap by comparing different models’ performance in modelling, as well as forecasting the house price returns and volatility of the studied market.

The purpose of this paper is to examine whether realized volatility can provide additional information on the volatility process to the GARCH and EGARCH model, based on the data of Chinese stock market.

The realized volatility is defined as the squared overnight return plus the close to open squared return of the period between the morning and afternoon session, to plus the sum of the squared f-minute returns between the trading hours during the relevant trading day. The methodology is a GARCH (EGARCH) model with added explanation variables in the variance equation. The estimation methodology is exact maximum likelihood estimation, using the BHHH algorithms for optimization.

There are some stocks for which realized volatility measures add information in the volatility process, but there are still quite a number of stocks for which they do not contain any additional information. The 30 minutes realized volatility measures outperform measures constructed on other time intervals. The firm size, turnover rate, and amplitude also partially explain the difference in realized volatility ' s explanatory power across firms.

When analyzing the factors determining the role of realized volatility, as the difficulty of getting the data, ownership structure and ultimately ownerships are not taken into account, except for the turnover ratio, amplitude and size.

This study extends firstly this line of inquiry of realized volatility into the emerging Chinese stock market. Due to the unique institutional setting in China, the results of this study have played an important role on pricing warrant for domestic investors in the Chinese market.

This paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.

This study considered daily data from January 2, 2002, to December 31, 2013. The sample period has been further divided into three periods; full sample period (January 2002-December 2013), pre-crisis period (January 2002-October 2007) and post-crisis period (October 2007-December 2013). This study opted Exponential Generalized Autoregressive Heteroskedasticity (EGARCH) model for the purpose of investigating asymmetric volatility spillover.

The results obtained using the EGARCH model imply that volatility spillover dynamics varies from period to period. In full sample period, the results show evidence of significant unidirectional volatility spillover from foreign exchange market to stock market. In pre-crisis period, the results indicate unidirectional volatility spillover from stock market to foreign exchange market. However, in post-crisis period, the results reveal significant bidirectional volatility spillover between stock and foreign exchange market.

The results of the study are important for policy makers because understanding the behavior of the financial markets, i.e. stock and foreign exchange market, would increase the success of policies implemented in a crisis situation. The results would help investors to formulate efficient portfolios.

This study is an important contribution to the existing literature in terms of analyzing volatility spillover between stock and foreign exchange market in an emerging economy, China. Furthermore, this study explored the volatility spillover dynamics between the two markets by considering the pre and post subprime Asian crisis period.

The purpose of this paper is twofold in examining the international transmission of REIT returns volatility. The first purpose is to add to the literature on whether the real estate securities market and the broader equity market are integrated. The second objective of the study is to determine whether geographic risk factors can be transmitted beyond their region of influence.

The study uses the GARCH(1, 1), EGARCH, and GARCH‐M models.

The results show that there are significant international spillovers of REIT returns volatility within the Pacific region. The results also show that there are significant volatility transmissions between the Pacific and the Atlantic regions.

The results are consistent with the implication that the real estate sector and the general equity market are integrated such that geographic risk can be transmitted across national borders. The result will have major implications for international investment strategies.

To date, there has been no published study on the international transmission of REIT returns volatility. This study therefore examines whether the conditional variance of REIT returns of a country is affected by volatility transmission across markets in the same region using four Pacific markets.

This study examines return and volatility spillovers from the US and Japanese stock markets to three South Asian capital markets – (i) the Bombay Stock Exchange, (ii) the Karachi Stock Exchange and (iii) the Colombo Stock Exchange. We construct a univariate EGARCH spillover model that allows the unexpected return of any particular South Asian market to be driven by a local shock, a regional shock from Japan and a global shock from the USA. The study discovers return spillovers in all three markets, and volatility spillovers from the US to the Indian and Sri Lankan markets, and from the Japanese to the Pakistani market. Regional factors seem to exert an influence on these three markets before the Asian financial crisis but the global factor becomes more important in the post-crisis period.

The authors analyze the relationship between exchange rate fluctuations of a number of major currencies and its impact on US stock market returns, as proxied by the S&P 500. Many studies have explored this topic since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This study takes a different look at this hypothesis and investigates the pairwise relationship between various exchange rates and the United States stock market returns (S&P 500 INDEX) from January 2000 to December 2019.

The authors test the data for unit roots using Phillip-Perron method. They use Johansen cointegration model to determine whether returns on S&P 500 are integrated with S&P 500. They use the VAR/VECM analysis to test whether there are any interdependencies between exchange rates and stock market return. Finally, they use various GARCH models, including the EGARCH and TGARCH models, to determine whether there exist volatility spillovers from exchange rate fluctuations in various markets to the volatility in the US stock market.

Using GARCH modeling, the authors find volatility in Australian dollar, Canadian dollar and the euro impact market return, and the volatility of Australian dollars and euro spills over to the volatility of S&P 500. They also find that the spillover is asymmetric for Australian dollars.

One of the limitations could be that the authors use different bivariate GARCH models rather than the MV-GARCH models. For future project(s), they plan to do this analysis from the perspective of a European Union or a British investor and use returns in those markets to see the impact of exchange rates on those markets. It would be interesting to know how the relationship will change during periods of financial crises. This could be achieved by employing structural break methodology.

Many studies have explored the relation between stock market returns and exchange rates since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This paper contributes by adding to the existing literature on impact of exchange rate on stock returns and by providing a detailed and different empirical analysis to support the results.

This paper aims to expand the literature on performance and volatility of Islamic funds and indices in comparison to their conventional unscreened counterparts, by studying the Moroccan case considering the recent introduction of Islamic finance in the country toward the end of 2015.

As there are still no Shariah-compliant indices in Morocco, the authors first applied four Shariah screening methodologies of some of the world leading equity index providers (i.e. Dow Jones, FTSE, S&P and MSCI) to screen the public listed companies in Casablanca Stock Exchange for Shariah compliance. Next, the authors constructed four Islamic float-weighted indexes for which they modeled the dynamic volatility using an extension of the AutoRegressive Conditional Heteroskedasticity models, namely, EGARCH(1,1).

The findings show that the screening process resulted in a well-diversified universe of Shariah-compliant stocks (25.6 per cent) to invest in. Furthermore, it is found that constructed Islamic indices outperformed the broad-based Moroccan All Shares Index (MASI) during the considered period of analysis (January 2013 to December 2014), and their long-run volatility is higher. This indicates that investors in Shariah-compliant stocks do not sacrifice financial performance for their risky investment. The estimates of the model show that volatility for the MASI is more persistent and takes longer time to die, and the leverage effect is positive for all indices, meaning that volatility of indexes’ returns is influenced more by good news than bad news, a result that is in contrast to other studies for developed countries.

On the arrival of the new banking law that introduced Islamic finance for the first time in Morocco, the authors suppose that these results could be very helpful for the Moroccan financial authorities in consideration with the construction of Islamic equity indices for Muslim investors seeking to invest ethically in accordance to their religious convictions but also for index funds managers and other equity market players.

The present study is the first of its kind in Morocco to construct Islamic indices using Shariah screening methodologies for which the volatility is modeled using an EGARCH(1,1) dynamic volatility model.