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The act of modeling and forecasting stock market volatility has become essential to risk management practice; it has emerged as one of the most popular themes in financial econometrics and has been mainly and constantly used in the valuation of financial assets and the Value at Risk, as well as the pricing of options and derivatives, are all part of the process. The purpose of this paper is to contrast the GARCH (Generalized Auto Regressive Conditional Heteroscedasticity) family models -- GARCH, PGARCH, EGARCH, GJR-GARCH, MGARCH, and IGARCH -- with the EWMA (Exponentially Weighted Moving Average) models in the prospect of establishing the best algorithm to forecast TSEC volatility weighted index from Taiwan stock market. We employ daily returns for the range between July 1997 and July 2023. The sample data spans a long time period i.e. 26 years of data with 6375 observations, which includes dramatic events such as the financial crisis of 2008, the COVID-19 epidemic, and the war between Russia and Ukraine. We observe that the asymmetric model PGARCH with a Student's t distribution develops the best model for assessing the volatility of the chosen index, but PGARCH with a normal error distribution produces the best estimating performance outcomes and hence outperforms the EWMA model. The present empirical investigation also seeks to illustrate the potential for investment returns as well as the associated risk. Our findings may have implications for risk management in Taiwan, together with a deeper exploration of the TSEC weighted index from Taiwan stock market volatility dynamics, given the scarcity of prior such studies. [ABSTRACT FROM AUTHOR]

The present study aims to investigate the volatility spillover effects in the international financial markets before and during the Russia–Ukraine conflict. The subject of this paper is the study of the influence of the recent war between Russia and Ukraine on the transmission of volatility between the American, European and Chinese stock markets using the DY methodology. The sample period for daily data is from 1 June 2019 to 1 June 2022, excluding holidays. The volatility spillover index increased during the war period, but this increase remains insignificant compared to that recorded during the COVID-19 pandemic crisis. According to the empirical results, we also found varying levels of dependence and spillover effects between the European, American and Chinese stock indices before and during the Russia–Ukraine conflict. [ABSTRACT FROM AUTHOR]

This paper investigates the nature of volatility spillovers between stock returns and hedge funds returns in twelve Asia Pacific countries in the 1997–2018 period. The sample period encompasses sub periods, 1997 Asia financial crisis, 2008 Global financial crisis and 2010 Eurozone crisis; these sub periods were characterised by financial upheavals. We apply the EGARCH methodology to model volatility and volatility spillovers in and between the markets. Our results show that the volatility of stock returns does not affect the volatility of hedge funds returns; however, there are inconsistent evidence of unidirectional volatility spillover from hedge funds to stock market returns. [ABSTRACT FROM AUTHOR]

This paper provides a comparative analysis of how the energy-sector stocks of 20 regional blocs (Americas, Australasia, BRIC, Southeast Asia, Scandinavia, Southern Europe, Far East, Europe, European Union, Emerging Europe, Asia, G7, G12, Economic and Monetary Union (EMU), CCARBNS, Latin America, North America, PIIGS, Asia-Pacific and NORCS) are connected from 5 July 1994 to 21 April 2020. It uses various techniques: Diebold and Yilmaz (2014)(DY 2014, hereafter) spillover indices and TVP-VAR, LASSO-VAR. Our main results are as follows: First, the DY approach results show that the biggest net contributor of volatility is the CCARBNS region, followed by the G12 and G7 regions, while the biggest receiver of volatility is the Southeast Asia region. Second, the TVP-VAR and LASSO-VAR results reveal that Scandinavia, Far East, and America's regions are net receivers of energy shocks, with net transmitters being CCARBNS, G7, G12 and Emerging European regions. Third, during the 2007–2008 financial crisis and recent COVID-19 outbreak, energy stock market spillovers have reached unprecedented high levels. Fourth, the world policy uncertainty greatly influenced the magnitude of volatility spillovers across regional energy stock markets. [ABSTRACT FROM AUTHOR]

Uncovering the risk-transmitting path within economic sectors in China is crucial for understanding the stability of the Chinese economic system, especially under the current situation of the China–US trade conflicts. In this paper, we aim to uncover the risk spreading channels by means of volatility spillovers within the Chinese sectors using stock market data. By applying the generalized variance decomposition framework based on the VAR model and the rolling window approach, a set of connectedness matrices is obtained to reveal the overall and dynamic spillovers within sectors. We find that 17 sectors (mechanical equipment, electrical equipment, utilities, and so on) are risk transmitters and 11 sectors (national defense, bank, non-bank finance, and so on) are risk takers during the whole period. Under the extreme risk events (i.e., the global financial crisis, the Chinese interbank liquidity crisis, the Chinese stock market crash, and the China–US trade war), the connectedness measures significantly increase and the financial sectors play a buffer role in stabilizing the economic system. Our results are robust to changes of the model parameters. Our study not only uncovers the spillover effects within the Chinese sectors, but also highlights the deep understanding of the risk contagion patterns in the Chinese stock markets. [ABSTRACT FROM AUTHOR]

This paper investigates the reaction of equity markets to the 2016 US presidential elections in Canada, China, Mexico and Russia, and their interaction with the US market. This objective is carried out by studying the magnitude and direction of return and volatility transmission across the major stock indices of these countries. Daily data provided by Exchange Traded Funds, (ETFs) as well as country stock indices are utilized 2 years before and 2 years after the November 2016 elections. We use the VECH specification of the multivariate GARCH model. The results indicate the existence of significant co‐movement of returns although some important differences before and after the elections are noted. Lagged values of the US returns significantly affect all other market returns in the pre‐election period, but not in the post‐election period. There is also evidence of volatility spillovers. Implications such as diversification opportunities for investors are discussed and the critical importance of understanding the transmission process between markets for risk management and economic policy are indicated. [ABSTRACT FROM AUTHOR]

This paper studies volatility transmission effects between the US stock market and the COVID-19. Using BEKK-multivariate GARCH model, we find the US stock market volatility depends both its own past shocks and past COVID-19 shocks. Further, we find the US stock market volatility is positively affected by the death rate (bad news) while the recovered rate (good news) has a negative impact on the US stock market volatility. In addition, we find there is an asymmetric volatility impact of COVID-19 on the US stock market: the bad news affects the current US stock market much more than the good news. Our fixed effect panel regression results support the volatility spillover effects. [ABSTRACT FROM AUTHOR]

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China's stock market and Russia's stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets. [ABSTRACT FROM AUTHOR]

This work reinvestigates the interrelationship between crude oil prices and stock market returns in Saudi Arabia by taking into account volatility spillovers that are exemplified by second-moment effects. Using weekly data from 2001 to 2018 and time-varying causality-in-mean and causality-in-variance tests and taking into account structural breaks, we model each series as an APARCH process to capture any leverage effects in the volatility of returns. Empirical results suggest the existence of a bidirectional causality relationship between stock and oil performance series. While we fail to document significant spillover effects stemming from the stock market to the oil market, we detected substantial spillover effects running from crude oil price changes to stock market returns. We also find evidence in favor of the presence of risk spillovers between crude oil price and stock market. In this context, unexpected loses in the oil market can be predicted by using sudden past declines in the Saudi Arabian stock market and a substantial increase in the oil price seems to have significant predictive power for a rise in the stock market in the future. These results suggest that government policies must take into account risk spillover effects between markets and that investors are better off monitoring crude oil markets in portfolio allocation decisions. [ABSTRACT FROM AUTHOR]

Do index futures still lead the spot market over government intervention or under trading restrictions? This intriguing question can be explored in the context of the 2015 Chinese market turmoil with frequent government interventions and its aftermath when unprecedentedly severe restrictions were imposed on the trading of the CSI 300 index futures. The intraday price discovery, studied via VECM, became weakly bidirectional over the boom phase from October 2014 to June 2015, in contract to the index futures' strong leading before the boom. The futures' leading status weakened drastically over the crash phase between June and September 2015, probably due to the government's interference with the stock market. Surprisingly, the futures under severe trading restrictions after the crash from September 2015 to June 2016 still led the spot weakly, and the volatility spillover to the index was somewhat significant. Policywise, the empirical findings imply that government interventions or trading restrictions weaken the functioning of markets. [ABSTRACT FROM AUTHOR]

The study implies VARX‐DCC‐MEGARCH model to investigate the returns transmission, volatility spillovers, asymmetry effect and the dynamic correlation between China and U.S. stock markets, as well as their local stock markets. We found that daytime returns of U.S. stock markets affect the overnight returns of Chinese stock markets. However, overnight returns transmission from the United States to China (daytime) was insignificant. Returns transmissions from Chinese stock markets to the United States are not significant. Daytime volatility of U.S. stock markets significantly spillovers the overnight volatility of Chinese stock markets and daytime volatility of Chinese stock markets spillovers the overnight volatility of U.S. stock markets. Moreover, during financial crises period, negative daily returns of Chinese stock markets significantly transmit to U.S. stock markets. Additionally, returns and volatility spillovers between local markets of the United States was also significant. During the financial crisis, the volatility spillovers between local stocks market of China was significant on one hand and leverage effect for U.S. and Chinese stock markets were also significant on the other hand. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to investigate volatility spillover effects, the impact of past volatility on present market movements, the reaction to positive and negative news, among selected financial markets. The sample stock markets are geographically dispersed on different continents, respectively North America, Europe and Asia. We also investigate whether selected emerging stock markets capture the volatility patterns of developed stock markets located in the same region. The empirical analysis is focused on seven developed stock market indices, i.e. IBEX35 (Spain), DJIA (USA), FTSE100 (UK), TSX Composite (Canada), NIKKEI225 (Japan), DAX (Germany), CAC40 (France) and five emerging stock market indices, i.e. BET (Romania), WIG20 (Poland), BSE (India), SSE Composite (China) and BUX (Hungary) from January 2000 to June 2018. The econometric framework includes symmetric and asymmetric GARCH models i.e. EGARCH and GJR which are performed in order to capture asymmetric volatility clustering, interdependence, correlations, financial integration and leptokurtosis. Symmetric and asymmetric GARCH models revealed that all selected financial markets are highly volatile, including the presence of leverage effect. The stock markets in Hungary, USA, Germany, India and Canada exhibit high positive volatility after global financial crisis. [ABSTRACT FROM AUTHOR]

In this article, we use partial correlations to derive bi‐directional connections between major firms listed in the Moscow Stock Exchange. We obtain coefficients of partial correlation from the correlation estimates of the Constant Conditional Correlation GARCH (CCC‐GARCH) and the consistent Dynamic Conditional Correlation GARCH (cDCC‐GARCH) models. We map the graph of partial correlations using the Gaussian Graphical Model and apply network analysis to identify the most central firms in terms of both shock propagation and connectedness with others. Moreover we analyze some network characteristics over time and based on these we construct a measure of system vulnerability to external shocks. Our findings suggest that during the crisis interconnectedness between firms strengthens and becomes polarized and the system becomes more vulnerable to systemic shocks. In addition, we found that the most connected firms are the state‐owned firms Sberbank and Gazprom and the private oil company Lukoil, while in terms of the top most central systemic risk contributors, Sberbank gave its place to the NLMK Group. [ABSTRACT FROM AUTHOR]

In this study we construct volatility spillover indexes for some of the major stock market indexes in the world. We use a DCC-GARCH framework for modeling the multivariate relationships of volatility among markets. Extending the framework of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) we compute spillover indexes directly from the series of returns considering the time-variant structure of their covariance matrices. Our spillover indexes use daily stock market data of Australia, Canada, China, Germany, Japan, the UK, and the USA, for the period April 1996–June 2017. We obtain several relevant results. First, total spillovers exhibit substantial time series variation, being higher in moments of market turbulence. Second, the net position of each country (transmitter or receiver) does not change during the sample period. However, their intensities exhibit important time variation. Finally, transmission originates in the most developed markets, as expected. Of special relevance, even though the Chinese stock market has grown importantly over time, it is still a net receiver of volatility spillovers. However, the magnitude of net volatility reception has decreased over the last few years. [ABSTRACT FROM AUTHOR]

In this article, we use high frequency data and an identification via changes in volatility approach to assess the volatility spillovers among oil and the US and Saudi Arabian stock markets. We document the existence of asymmetry in contemporaneous spillover effects. Particularly, during the times when oil's trading hours overlap with the US and Saudi Arabian stock markets, the volatility spillover from oil to the stock markets is higher than the other way around. We highlight the importance of taking into consideration the information present during continuous trading hours of oil, especially during simultaneous trading hours with the stock markets. We compare our findings based on our structural VAR with those of a traditional reduced-form VAR, and observe that contemporaneous and intraday effects are necessary to be taken into account since the indirect transmission of volatility occurs through them. [ABSTRACT FROM AUTHOR]

In this article, we examine the dynamic currency linkages for BRIS (Brazil, Russia, India and South Africa) and 15 other emerging market economies (EMEs) using weekly data from 2001 to 2018. Using the asymmetric dynamic conditional correlation (ADCC)-EGRARCH framework, we find that the average correlation between BRIS currencies in the pre-crisis period is low and stood at 0.29, which rose to 0.39 in the post-crisis period implying contagion effects. Based on both ADCC results and Diebold-Yilmaz, Vector Autoregressive (VAR)framework enhanced by Greenwood-Nimmo block aggregation technique, we find that Brazil is a net transmitter while Russia, India and South Africa seem to be net receivers of information based on the first two moments. We further find empirical support for expanding BRIS into a larger economic block. Based on prior research findings on equity market linkages on BRICS and EMEs as well as our work on currency market linkages, we suggest Mexico, Poland and Hungary as potential candidates to be included in this economic block in the first phase. Turkey, Chile, Columbia and Romania may be included in the next phase as they dominate BRIS in either stock or currency markets of BRIS. This study is pertinent for global policymakers, international monetary agencies, currency investors and academia. [ABSTRACT FROM AUTHOR]

Flow of information and volatility coming from stock markets of other countries have significant impact on the stock market of a country. Volatility is even higher in the case the countries enjoy good economic conditions among themselves. The present manuscript aims to probe into the spread of impacts over a large range of returns and volatility in four major equity markets of Asia viz. India, China, Hongkong and Japan for a period of 18 years ranging from 2000 to 2017. The study uses VAR based GARCH model to determine the volatility spillover among the chosen countries for the period under assessment. The empirical outcomes of the study present that all selected markets have responded to their own lag of conditional volatility along with news shocks. The impact of conditional variance is higher in comparison to shocks which is an indication that markets fundamentals are stronger than corrections or shocks. The results of cross country spillover show that volatility of Shanghai Stock Exchange of China and shocks from Japan and Hongkong markets assert a significant effect over volatility of Indian equity market. Volatility of stock markets of Japan and China is not affected by the cross market volatility and shocks spillover from India. In contrast, volatility of Hongkong market is affected by shocks and volatility of Indian equity markets. Findings of the research have meaningful insights for the Governments and regulators, academicians, researchers, investors and fund managers in framing investment strategies in the chosen markets. [ABSTRACT FROM AUTHOR]

This paper employs a multivariate constant conditional correlation (CCC) GARCH model and the VAR-AGARCH model to examine whether the U.S. equity and money market have a volatility spillover effect on the returns of the most important agricultural export products of Latin America over the turbulent 2005–2016 period. These results indicate the strengthening of crossmarket linkages between U.S. equity and money market and agricultural raw material commodities (notably sugar and soy) during the period of an upward trend and financial turmoil. [ABSTRACT FROM AUTHOR]

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This study examines volatility spillover between stock markets in the West African region, and with the United States of America (US) and United Kingdom (UK) stock markets using the Exponential Generalized Autoregressive Conditional Heteroscedastic (E-GARCH). Daily stock market index returns from 2008-2016 were analysed considering two sub-sample periods representing periods of turbulence and tranquil. Findings from the study reveal that there is the presence of significant volatility spillover effects between stock markets in the West African region and also with major global markets of US and UK. Significant changes are also observed in the direction, magnitude and sign of impact during the period of crises and in the post crises period. The results of this study is important to local, regional and international investors, market participants and regulatory bodies as it implicates on portfolio diversification strategies, capital controls policies and efforts towards regional stock market integration. [ABSTRACT FROM AUTHOR]

In our network analysis of 40 developed, emerging and frontier stock markets during the 2006–2014 period, we describe and model volatility spillovers during both the global financial crisis and tranquil periods. The resulting market interconnectedness is depicted by fitting a spatial model incorporating several exogenous characteristics. We document the presence of significant temporal proximity effects between markets and somewhat weaker temporal effects with regard to the US equity market — volatility spillovers decrease when markets are characterized by greater temporal proximity. Volatility spillovers also present a high degree of interconnectedness, which is measured by high spatial autocorrelation. This finding is confirmed by spatial regression models showing that indirect effects are much stronger than direct effects; i.e., market-related changes in ‘neighboring’ markets (within a network) affect volatility spillovers more than changes in the given market alone, suggesting that spatial effects simply cannot be ignored when modeling stock market relationships. Our results also link spillovers of escalating magnitude with increasing market size, market liquidity and economic openness. [ABSTRACT FROM AUTHOR]

Diebold–Yilmaz spillover indexes are computed for weekly return volatilities based on daily benchmark stock indexes of the US, the UK, and 10 Asian countries. We found (i) the strengthening of overall volatility spillovers is not a temporary surge but persisted after the crisis; (ii) the susceptibility of individual Asian stock markets to inward volatility transfers is linked to its degree of openness; and (iii) the Asian bourses are becoming more important emitters of financial shocks since the crisis. Rolling regressions on volatility linkages reveal the relative dominance of the US over the Japanese and Chinese bourses, and the level of influence on Asian stock markets from the Chinese bourse has risen to that of Japan. [ABSTRACT FROM PUBLISHER]

This paper focused on measuring the volatility spillovers and parametric Value-at-Risk (VaR) models for hedge fund strategies. In reference to the first, a volatility spillover index was created to measure the connectedness and relationships between strategies. Results suggest that during periods of distress, volatility spillovers tend to increase across strategies. Equity-Hedge and Event-Driven strategies seem to be the most connected, while the Equity-Market-Neutral strategy exhibits the least connectedness with other strategies. With regard the second, unconditional and conditional parametric VaR models under Gaussian and t-distributions were measured. In general, conditional GARCH-type models outperform their unconditional counterparts, particularly at the onset of the recent financial crisis. This suggests that GARCH-type VaRs are better in protecting against downside risk. Moreover, conditional Gaussian models are more suitable for mild periods, while those under the t-distribution effectively capture risk in extremely volatile period. Finally, to unravel the connection between the two measures, common hits between hedge fund strategies were examined. The results validate the results of the volatility spillover index. [ABSTRACT FROM AUTHOR]

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets. [ABSTRACT FROM PUBLISHER]

We use high frequency data and the 'identification through heteroskedasticity' approach of Rigobon (2003) to capture the contemporaneous volatility spillover effects between the U.S. and U.K. equity markets. We demonstrate the relevance of taking into account the information present during simultaneous trading hours by comparing the results generated by our structural vector autoregression with those of a traditional reduced-form vector autoregression. Our findings clearly demonstrate that contemporaneous relations matter and that ignoring them leads to inappropriate conclusions regarding the magnitude and direction of volatility spillover. [ABSTRACT FROM AUTHOR]

The paper investigates the volatility spillovers among five major Latin American (LA) stock markets under the presence of the structural breaks in variance. We employ a multivariate dynamic conditional correlation (DCC GARCH) model allowing for structural breaks in variance. The dynamic correlations show that volatility spillover effects among the markets are not strong. Causality in mean tests indicate one way causality from BOVESPA to all markets, whereas causality in variance tests indicate one way causality only from BOVESPA to IPSA. These findings suggest that while the markets in the sample are interdependent, there is not enough statistical evidence to infer the contagion effects among the markets. [ABSTRACT FROM AUTHOR]

This paper examines the risk transmissions across the green economy indices of three major regions which include US, Europe and Asia. The econometric analyses are conducted using DCC-GARCH and TVP-VAR connectedness approach to evaluate potential spillover effects within the context of oil and gold. Results indicate that green economy indices of US-Europe exhibit the greatest time-varying correlations among the three pairs during much of 2010–2022 consistent with that of the general equity market. However, co-movements during the COVID-19 pandemic period seem to display a change in pattern for green economy indices. The strength of the co-movements between the US and Europe displayed a declining trend, while that between US and Asia was strengthened, suggesting greater interdependence between these two markets. TVP-VAR connectedness analysis revealed that US and Europe dominate the transmission of the shocks across the years in the green economy, similar to that of the equity markets. However, during the pandemic a pronounced shift occurred in green economies when considering the risk transmissions within the context of commodities: oil and gold. While Asian green economy index was persistently a receiver of risk transmission from oil unlike the other two regions, since pandemic, oil displayed an asymmetric effect and has become the net transmitter of risk in negative returns of the green economies of US and Europe. This may reflect the diversion in environmental policies of the two regions in the recent past, and point to the dominance of energy sector in the green economy. These findings have substantial implications for the development of green economy policies and from an investment perspective. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the dynamics of volatility spillovers between the US economic policy uncertainty and the BRIC equity markets. To do so, we perform the cross correlation function suggested by Cheung–Ng (1996) within a rolling approach. Although the mean return spillover between the BRIC stock indices and US uncertainty is negative, the volatility spillover is found to oscillate between negative and positive values. Therefore, it is highly risky for investors to invest in the US and BRIC stock markets simultaneously. In addition, we find that there is strong evidence of a time-varying correlation between US economic uncertainty and stock market volatility. Furthermore, the correlation is found to be highly volatile during periods of global economic instability. So, market participants in the BRIC stock markets do closely monitor the US economic policy conditions. [ABSTRACT FROM AUTHOR]

What is the relationship between the two largest emerging financial markets of Eastern Europe, Russia and Poland, and how do they impact the region's stock markets? The purpose of this paper is to examine the role of these two countries in regional volatility by examining their effect on two separate phenomena: financial volatility, defined here as long-term interrelations, and contagion, a more short-term phenomenon. Utilizing bivariate DCC-GARCH modeling, this paper estimates long-term volatility spillover effects and short-term contagion effects and their origins during several periods of financial crisis in the Central and Eastern European region. Our results show that the long-term impact of volatility in the Russian market is much more substantial than that of Poland in Central and Eastern Europe, with this disparate impact corresponding to each country's level of market capitalization. Additionally, our results show that Russia served as a source of short-term contagion for neighboring countries during its banking crisis in 2004 and during the Russian stock market fall in 2008. Poland had comparatively less effect on the region during the Global Financial Crisis. Moreover, the entrance of Poland into the European Union in May 2004 had no impact on stock markets in the region in terms of enhancing contagion. [ABSTRACT FROM AUTHOR]

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines the dynamic and switching effects of volatility spillovers arising from US stock market returns and GDP growth on those of Australia, Canada and the UK. For this purpose, we use quarterly data (1961q1–2013q1) and a constant probability Markov regime switching model. We found that the US stock market volatility significantly affects the stock market volatility of all three countries at least in one of the two specified regimes over time. However, the stock market volatilities in none of the three countries are contemporaneously influenced by the US output volatility even after allowing for two distinct regimes. On the other hand, the US stock market volatility exerts significant influences on the output volatilities of both Australia and the UK. Compared with Australia and the UK, Canada and the US show substantial output volatility co-movements, thereby confirming the close association between the two neighbouring economies through the NAFTA (North American Free Trade Agreement). We conclude that shocks emanating from the US stock market have unequivocal flow-on effects on the output and return volatilities of the other economies. [ABSTRACT FROM AUTHOR]

We investigate returns, volatilities, and correlations across mature, dominant regional, and frontier equity markets. Standard & Poor's 500 is chosen as a mature equity market; India is chosen as a dominant regional market; and Bangladesh, Pakistan, and Sri Lanka are chosen as frontier markets. Our empirical tests show that the frontier markets remain fundamentally decoupled from the mature markets during normal market periods. During turbulent times, the contagion effects from the mature to the frontier markets become more pronounced. The results suggest that the dominant regional market plays a key role in disseminating shocks across the frontier markets during normal periods; during the turbulent recent financial crisis period, a similar contagion is not observed. [ABSTRACT FROM AUTHOR]

We investigate volatility spillovers between two stock markets: Turkey and Brazil. Using a misspecification-robust causality-in-variance test, we find evidence supporting volatility spillovers from the São Paulo Stock Exchange to the Istanbul Stock Exchange. Moreover, the results imply that financial crises may change the nature of volatility spillovers between the two markets by adding an additional channel of volatility transmission from Turkey to Brazil. [ABSTRACT FROM AUTHOR]

Copyright of Arab Journal of Administrative Sciences is the property of Kuwait University, Academic Publication Council and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines volatility transmission and conditional correlations behaviour between the US and the Asian stock markets considering the effect of the Global Financial crisis. One Asian mature market and 10 emerging markets are included in the sample. To carry out the analysis, we use a multivariate asymmetric GARCH model. Results show that there exists volatility transmission between the US and the Asian markets. Moreover, it is found that, after the crisis, volatility transmission patterns have barely changed. Finally, results suggest that the lower the country‘s level of development, the lower the correlation with the USA. [ABSTRACT FROM PUBLISHER]

This paper estimates a trivariate VAR-GARCH(1,1) model to examine volatility linkages between the stock markets of three Central and Eastern European countries (CEECs), namely the Czech Republic, Hungary and Poland. The empirical .findings suggest that following the EU accession regional linkages have become even stronger, and that therefore portfolio diversification within the region has become an even less effective investment strategy. This can be plausibly interpreted as reflecting deeper integration with the 'old' EU economies, and has important implications for appropriate policy responses to shocks originating in those countries and affecting the .financial stability of the CEECs.JEL Classification: C32, F36, G15 [ABSTRACT FROM AUTHOR]

Using Spanish stock market data, this paper examines volatility spillovers between large and small firms and their impact on expected returns. By using a conditional capital asset pricing model (CAPM) with an asymmetric multivariate GARCH-M covariance structure, it is shown that there exist bidirectional volatility spillovers between both types of companies, especially after bad news. After estimating the model, a positive and significant price of risk is obtained. This result is consistent with the volatility feedback effect, one of the most popular explanations of the asymmetric volatility phenomenon, and explains why risk premiums are much more sensitive to negative return shocks coming from the whole market or other related markets. [ABSTRACT FROM AUTHOR]

During the deepest financial crisis in mid 2007-2009, increasing volatility of Indonesian stock market index were captured. Increasing volatility of the series is a common event since the volatility of financial market around the globe is increasing likewise. Yet, whether it is a sign of volatility spillover or comovement still emerges as a mystery. This paper seeks to explain the causes of the increasing volatility in domestic currency and stock market. To investigates the hypothesis in tranquil and crisis periods, the observation period of January 2, 2003 to May 31, 2010 is splitted into two sub-periods with different levels of volatility. Using VAR-EGARCH on daily stock market index of Indonesia (IDX), S&P 500, and the bilateral exchange rate, we documented the existence of meteor shower and heatwaves in Indonesia stock market and exchange rate during crisis period. This finding implies that in crisis period, Indonesian stock market and exchange rate volatility were not only affected by market specific factors, but were also affected by volatility of the major stock market. We also captured asymmetric affects in the model which suggests that negative shock in the major stock market will increase the volatility of domestic stock market more than positive shock will. [ABSTRACT FROM AUTHOR]

This paper examines the short-run dynamic relationships between stock market and real activity, within a country, for the UK and the US. The Cross Correlation Function testing procedure is applied to test for causality in mean and in variance between the stock market and the real economic sector. Besides variance causation, volatility spillover effects are examined through the multivariate specification form of the Exponential GARCH model. There is evidence of significant reciprocal volatility spillovers between the two sectors within a country, implying stronger interdependencies in the UK rather than in the US and asymmetric behavior only in the case of the UK. [ABSTRACT FROM AUTHOR]

In this study volatility spillover effects in preselected cointegrated European stock markets are investigated. The data generating processes are estimated by applying Vector-Auto Regression (VAR) models. Thereby, the impacts of volatility spillovers are measured by a new concept being denoted here as Volatility Impulse Response Density Functions (VIRDF) being an advancement of the Volatility Impulse Response Functions (VIRF) methodology. A sample-split analysis covering daily data from 26.11.1990-05.10.2000 and 06.10.2000-28.05.2010 reveals that the volatility spillover impact from the German stock market to the Swedish and British stock markets have increased by 73.87%, respectively, 15.52%. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines global (mature market) and regional (emerging market) spillovers in local emerging stock markets. Tri-variate VAR-GARCH(1,1)-in-mean models are estimated for 41 emerging market economies (EMEs) in Asia, Europe, Latin America, and the Middle East. The models capture a range of possible transmission channels: spillovers in mean returns, volatility, and cross-market GARCH-in-mean effects. Hypotheses about the importance of different channels are tested. The results suggest that spillovers from regional and global markets are present in the vast majority of EMEs. However, the nature of cross-market linkages varies across countries and regions. While spillovers in mean returns dominate in emerging Asia and Latin America, spillovers in variance appear to play a key role in emerging Europe. There is also some evidence of cross-market GARCH-in-mean effects. The relative importance of regional and global spillovers varies too, with global spillovers dominating in Asia, and regional spillovers in Latin America and the Middle East. [Copyright &y& Elsevier]

Abstract: The paper empirically analyzes the dynamic relationship between Renminbi (RMB) real effective exchange rate and stock price with VAR and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models using monthly data from January 1991 to June 2009. The results show that there is not a stable long-term equilibrium relationship between RMB real effective exchange rate and stock price. There are also not mean spillovers between the foreign exchange and stock markets. Furthermore, the paper examines the cross-volatility effects between foreign exchange and stock markets using likelihood ratio statistic. There exist the bidirection volatility spillovers effects between the two markets, indicating the past innovations in stock market have the great effect on future volatility in foreign exchange market, and vice versa. [Copyright &y& Elsevier]

Abstract: This study considers the linkage of the Russian equity market to the world market, examining the international transmission of the Russia''s 1998 financial crisis utilizing the GARCH–BEKK model proposed by Engle and Kroner [Engle, R.F., Kroner, K.F., 1995. Multivariate simultaneous generalized ARCH. Economet. Theor. 11, 122–150]. We find evidence of direct linkage between the Russian equity market with regards to returns and volatility, while the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market. At the time of the crisis, evidence of contagion is clear. [Copyright &y& Elsevier]

This paper analyzes stock returns and volatility relations between the Istanbul Stock Exchange (ISE) and the global market as represented by stock markets in the US, the UK, Japan and Germany. Results from monthly data and multivariate cointegration tests suggest that the ISE became significantly integrated in the global market only in the period following market liberalization in late 1989. We also find evidence based on GARCH estimations that capital liberalization actually mitigated, rather than intensified, volatility in the ISE. Our results further suggest that the Asian crisis in mid-1997 and the consequent Russian economic meltdown in mid-1998 are partly responsible for the recent excessive volatility in the Turkish market. The results also identify the US and the UK markets as dominate sources of volatility spillovers for the ISE, even in the period following the Asian-Russian crises. Consequently, it appears that the two matured markets of the US and the UK shoulder significant responsibility for the stability and financial health of smaller emerging markets like the ISE. [ABSTRACT FROM AUTHOR]

This paper quantitatively investigates the return transmission, volatility spillovers, dynamic correlations, and financial risks between corn, soybean, and crude oil futures and US and European equities. Specifically, by applying our newly extended quinquevariate dynamic conditional correlation (DCC) system with asymmetric spillovers and skew- t errors, we obtain the following new evidence. First, during our recent sample period, the nexuses and dynamic interactions between corn, soybean, and crude oil futures and US and European equities have tightened. Second, we find strong return transmission from US equities to corn, soybean, and crude oil futures and European equities. Third, we clarify significant volatility spillovers that are tied to the leverage effect, from US and European equities to corn and crude oil futures, indicating that downside risk in equity markets is important when considering volatility spillovers to fuel and energy markets. Using the conditional variances and covariances from our new system, we further derive more precise time-varying optimal hedge ratios and optimal portfolio weights. These newly find that for the three asset classes of biofuel crops, crude oil, and equities, hedging one asset class with the other asset classes is effective, and well-balanced portfolios constructed using the three asset classes are optimal. [ABSTRACT FROM AUTHOR]

This paper investigates linkages among equity market returns and volatility spillovers in the following countries: Germany, United Kingdom, China, Russia, and Turkey. MARMA, GARCH, GARCH-in-mean, and exponential GARCH (EGARCH) methodologies are applied to daily data on country exchange-traded funds (ETF) based on the MSCI indices from 31 March 2011 to 11 March 2016. The results of the analysis show the existence of significant co-movements of returns among the countries in the sample. ETF returns in Germany, UK, and Russia affect returns in all of the other sample countries. Implications of these findings are explored in terms of portfolio diversification. In addition, the highest volatilities are exhibited by Russia and Turkey. On the other hand, the UK and the Chinese markets have the lowest volatilities. Also, there is a strong evidence of volatility spillovers. All of the countries in the sample, with the exception of UK and Turkey, experience volatility spillovers from other markets. Finally, because of the risk-return trade-off, we analyzed the effect of volatility of the market on its returns and found that only in the UK volatility of the market had a positive effect on its future returns: that an increase in volatility leads to a rise in future ETF returns in the UK. [ABSTRACT FROM AUTHOR]