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[EN] Volatility spillovers are a characteristic of interconnected electricity markets. We use high-frequency prices to analyze the transmission of volatility across five Australian regional electricity markets. We propose several models: The first includes only realized variances; the second adds realized covariances; the last two include positive and negative realized semi(co)variances, separately, obtained from the decomposition of the realized covariance matrix into components based on the sign of the underlying returns. We carry out the analysis for both static and dynamic frameworks and relate the behavior of spillovers to major events and policies affecting the markets. Results show that ignoring covariances results in spillovers being underestimated and highlight the importance of the role of semi(co)variances in detecting asymmetric spillovers. Finally, we discuss implications for short-run market participants and long-term planning by regulators.

[EN] Volatility spillovers are a characteristic of interconnected electricity markets. We use high-frequency prices to analyze the transmission of volatility across five Australian regional electricity markets. We propose several models: The first includes only realized variances; the second adds realized covariances; the last two include positive and negative realized semi(co)variances, separately, obtained from the decomposition of the realized covariance matrix into components based on the sign of the underlying returns. We carry out the analysis for both static and dynamic frameworks and relate the behavior of spillovers to major events and policies affecting the markets. Results show that ignoring covariances results in spillovers being underestimated and highlight the importance of the role of semi(co)variances in detecting asymmetric spillovers. Finally, we discuss implications for short-run market participants and long-term planning by regulators.

In 2005, the European Union launched its Emissions Trading System (ETS), the first and one of the largest international carbon markets aimed at reducing member states' CO2 emissions. Policymakers tend to use the carbon price as an indicator of the “health” and effectiveness of the ETS mechanism, although this measure is influenced by many other energy and climate policies, energy market fundamentals, and speculative shocks. This paper develops a model that links the energy sector (oil, natural gas, coal, electricity prices, and the share of fossil fuels in electricity generation), economic activity, and the carbon price. The model can be used as a monitoring tool for carbon price dynamics. We represent the model empirically through a Structural Vector Autoregression and use frequency-domain analysis to distinguish the effects of changes in fundamental factors from shocks to market microstructure. Our empirical results show that up to 90% (65% on average) of the fluctuations in the carbon price, adjusted for supply effects, are explained by fluctuations in fundamental market variables; however, the individual contributions are not stable. Overall, our results suggest that the ETS has started to work well.

This study employs a bivariate E-GARCH-M model at one lag on weekly returns of major REITs markets in six countries including Australia, Hong Kong, Japan, Singapore, the UK and the US during and after the crises periods of the Sub-prime Mortgage Crisis, Global Financial Crisis and European Debt Crisis. The results found cross-market linkages vary with countries and changed significantly after the crises period. We find the returns of REITs in Australia, the UK and US to be segmented, and interdependence for Hong Kong, Japan and Singapore markets. In terms of volatility spillovers, the size effect impacts weekly volatility of the three Asian markets. We also find significant asymmetric effects of volatility spillovers between markets during the crises period, but this only persists for the Australian and Singaporean markets following in the post-crisis period. Past volatility has a persistent explanatory effect on current volatility in all the markets examined. Our findings have implications for investors looking to build a diversified portfolio of international real estate investments.

This paper analyses the effects of newspaper coverage of macro news on the spread between the yield on the 10-year German Bund and on sovereign bonds in eight countries belonging to the euro area (Belgium, France, Greece, Ireland, Italy, the Netherlands, Portugal and Spain) using daily data for the period 1999–2014. The econometric analysis is based on the estimation of a VAR-GARCH model. The results can be summarized as follows. Negative news have significant positive effects on yield spreads in all GIIPS (Greece, Ireland, Italy, Portugal and Spain) countries but Italy before September 2008; markets respond more to negative news, and their reaction has increased during the recent financial crisis. News volatility has a significant impact on yield spread volatility, the effects being more pronounced in the case of negative news and bigger in the most recent crisis period, especially in the GIIPS countries. Further, the conditional correlations between yield spreads and negative news increase in absolute value during the financial crisis (especially in the GIIPS countries), indicating a higher sensitivity of the former to the latter.

This study employs a bivariate E-GARCH-M model at one lag on weekly returns of major REITs markets in six countries including Australia, Hong Kong, Japan, Singapore, the UK and the US during and after the crises periods of the Sub-prime Mortgage Crisis, Global Financial Crisis and European Debt Crisis. The results found cross-market linkages vary with countries and changed significantly after the crises period. We find the returns of REITs in Australia, the UK and US to be segmented, and interdependence for Hong Kong, Japan and Singapore markets. In terms of volatility spillovers, the size effect impacts weekly volatility of the three Asian markets. We also find significant asymmetric effects of volatility spillovers between markets during the crises period, but this only persists for the Australian and Singaporean markets following in the post-crisis period. Past volatility has a persistent explanatory effect on current volatility in all the markets examined. Our findings have implications for investors looking to build a diversified portfolio of international real estate investments.

Asset price movements play credible role as leading indicator for activity, financial distress and general economic wellbeing, and as such, are closely monitored by investors and policymakers alike. All assets’ prices are expressed in a unit of account, usually the home currency of the jurisdiction in which the asset is domiciled, and the values of these currencies continually vary, depending on the balance of demand and supply. The continuous variation in the value of currencies suggests that, at best, they can only be an inappropriate unit of measure of an asset. This dissertation aims to shed more light on why single currencies are inaccurate units of measure of asset prices. Our first study investigates how the currency of valuation affects the outcome of the return and volatility spillovers between the stock market and the foreign exchange (FX) market. Evidence from our study suggests the presence of exchange rate premium in asset prices, which in turn significantly affects the nature of the relationship between the equity and FX markets when asset prices are measured in an aggregate unit of account rather than pair-wise or single currency. In our second study, we examine the currency effect on the predictability of stock returns in the short term. Although previous studies have concentrated on investigating the factors or models that best predict asset returns, our study investigates the effect of currency of valuation on stock return predictability. Our results suggest that reducing the volatility of the variables by valuing them in an aggregate unit of account improves the predictability of stock returns on the short horizon. Our last study investigates the currency effect on the long-term relationship between the stock market and macroeconomic variables. Our results show evidence of significant changes in the relations between the stock market and macroeconomic variables with the introduction of the aggregate currency factor, marked by reducing the effect o

The aim of this thesis is to look at volatility spillovers between the exchange rate changes and the stock market returns. The theoretical relationship between the exchange rate and stock market is covered with focus on two basic models, the stock oriented model and the flow oriented model. The relationship between the two variables is positive in the stock oriented model while it is negative in the flow oriented model. An empirical study is done on Brazil, Canada, Mexico and the United States from 1999-2014 using a GARCH-BEKK model. Three results from the model are obtained, the whole sample and before and after the financial crisis in 2008. According to the study there are significant spillovers between the exchange rate and stock market for some periods and countries but it is not consistent throughout. In general the spillovers are strongest after the crisis in 2008 for all countries. In the United States and Canada the spillovers are stronger from the stock market to the exchange rate while the spillover for Mexico and Brazil are stronger from the exchange rate to the stock market.

This paper analyzes the performance of multiple steps estimators of vector autoregressive multivariate conditional correlation GARCH models by means of Monte Carlo experiments. We show that if innovations are Gaussian, estimating the parameters in multiple steps is a reasonable alternative to the maximization of the full likelihood function. Our results also suggest that for the sample sizes usually encountered in financial econometrics, the differences between the volatility and correlation estimates obtained with the more efficient estimator and the multiple steps estimators are negligible. However, when innovations are distributed as a Student-t, using multiple steps estimators might not be a good idea.

The aim of this thesis is to look at volatility spillovers between the exchange rate changes and the stock market returns. The theoretical relationship between the exchange rate and stock market is covered with focus on two basic models, the stock oriented model and the flow oriented model. The relationship between the two variables is positive in the stock oriented model while it is negative in the flow oriented model. An empirical study is done on Brazil, Canada, Mexico and the United States from 1999-2014 using a GARCH-BEKK model. Three results from the model are obtained, the whole sample and before and after the financial crisis in 2008. According to the study there are significant spillovers between the exchange rate and stock market for some periods and countries but it is not consistent throughout. In general the spillovers are strongest after the crisis in 2008 for all countries. In the United States and Canada the spillovers are stronger from the stock market to the exchange rate while the spillover for Mexico and Brazil are stronger from the exchange rate to the stock market.

This thesis contributes four essays to the economic literature on the multivariate modeling of the variance-covariance dynamics in the financial time series data, covering the issues of dynamic hedging, international volatility spillovers and financial integration, where applying the Multivariate GARCH models leads to the efficient resolution of a number of ongoing empirical issues. The first essay addresses the portfolio hedging problem for a range of commodities and proposes an alternative way of accounting the asymmetric effect in the volatility by including the asymmetric term in a multivariate GARCH model. By in- and out-of-sample forecast we show that hedging using the asymmetric model outperforms other alternatives. The second essay aims to investigate the cross-border effect of the monetary policy rate announcements on the comovements of the world's major stock markets. The news component of the announcements is extracted from the interest rate futures data. Both the effect of the magnitude and sign of the news are considered. It is demonstrated how these effects may alter the asset allocation decisions. The third essay contributes to the better understanding of the financial integration and volatility, i.e. the risk, transmission across European stock markets and provides comprehensive evidence by using a fully flexible multivariate model. The results are of high practical importance, since the high degree of integration implies higher vulnerability of a country to external risks. On the other, they have considerable implications for financial market participants who are involved in hedging and/or portfolio diversification., (POLS - Sciences politiques et sociales) -- UCL, 2013

This study examines volatility spillovers from developed markets of the United States and Japan to emerging markets in Asian-Pacific region during the period of two crises: 1997 Asian currency crisis and 2007 subprime credit crisis. Using recently developed bivariate multiplicative error model to examine volatility spillovers between the two stock markets, we find that the US market is more influential than the Japanese market for volatility transmissions to the Asian markets even though volatility spillovers from both the US and Japan to Asian countries are statistically significant. Additionally, the increasing spillovers of volatility from the US and Asian markets to Japan could be found as a result of the recent subprime financial crisis, while Japanese stock market is independent of other markets over the other three sub-periods. In addition, the volatility spillovers vary over time as they increase substantially after 1997 Asian currency crisis and their directions change dramatically after 2007 subprime credit crisis.

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes via Gaussian mixture models, GFC-robust risk management under the Basel Accord using extreme value methodologies, volatility spillovers from the Chinese stock market to economic neighbours, a detailed comparison of Value-at-Risk estimates, the dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value-at-risk with a duration-based POT method, and extreme market risk and extreme value theory.

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on "Risk Modelling and Management" (RMM2011). The papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes via Gaussian mixture models, GFC-robust risk management under the Basel Accord using extreme value methodologies, volatility spillovers from the Chinese stock market to economic neighbours, a detailed comparison of Value-at-Risk estimates, the dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value-at-risk with a duration-based POT method, and extreme market risk and extreme value theory.

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes via Gaussian mixture models, GFC-robust risk management under the Basel Accord using extreme value methodologies, volatility spillovers from the Chinese stock market to economic neighbours, a detailed comparison of Value-at-Risk estimates, the dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value-at-risk with a duration-based POT method, and extreme market risk and extreme value theory.

In this paper we investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for in- vestment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages (spillovers) are analyzed using a dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk.

This paper investigates the price discovery mechanism in the Hang Seng Index markets. The analysis is based on the cross-market volatility spillover effects by using the daily sets of Hang Seng Index (HSI), Hang Seng Finance Index (HSFIN), and Hang Seng Index futures (HSCIS00). In order to testify the influence of 2007 financial tsunami on the volatility spillover effect, the study employs the vector autoregressive model (VAR) and the bivariate GARCH model based on the BEKK parameterization. The testing period has been divided into the pre-crisis (1 April, 2003 to 31 July, 2007) and the crisis & recovery period (1 August, 2007 to 1 April, 2013). The empirical results depict that there exists bi-directional volatility spillover effect between HSI and HSCIS00 for the whole testing period. In contrast, a strong bi-directional volatility spillover effect between HSFIN and HSCIS00 is only recognized after the outbreak of the 2007 financial crisis.

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on "Risk Modelling and Management" (RMM2011). The papers cover the following topics: currency hedging strategies using dynamic multivariate GARCH, risk management of risk under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes via Gaussian mixture models, GFC-robust risk management under the Basel Accord using extreme value methodologies, volatility spillovers from the Chinese stock market to economic neighbours, a detailed comparison of Value-at-Risk estimates, the dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value-at-risk with a duration-based POT method, and extreme market risk and extreme value theory.

This paper examines whether there is evidence of spillovers of volatility from the Chinese stock market to its neighbours and trading partners, including Australia, Hong Kong, Singapore, Japan and USA. China's increasing integration into the global market may have important consequences for investors in related markets. In order to capture these potential effects, we explore these issues using an Autoregressive Moving Average (ARMA) return equation. A univariate GARCH model is then adopted to test for the persistence of volatility in stock market returns, as represented by stock market indices. Finally, univariate GARCH, multivariate VARMA-GARCH, and multivariate VARMA-AGARCH models are used to test for constant conditional correlations and volatility spillover effects across these markets. Each model is used to calculate the conditional volatility between both the Shenzhen and Shanghai Chinese markets and several other markets around the Pacific Basin Area, including Australia, Hong Kong, Japan, Taiwan and Singapore, during four distinct periods, beginning 27 August 1991 and ending 17 November 2010. The empirical results show some evidence of volatility spillovers across these markets in the pre-GFC periods, but there is little evidence of spillover effects from China to related markets during the GFC. We undertook some additional analysis for this period featuring an exploration of whether there was any spillover effect in the mean equations as well as in the variance equations. We used a bimean equation to model the conditional mean in the individual markets plus an ARMA model to capture volatility spillovers from China to the five markets considered. This augmented model showed much greater evidence of spillovers. We also suspected that the correlations were not constant and applied a moving window of 120 days of daily observations to explore time-varying conditional and fitted correlations. There was evidence of non-constant correlations and even a period of ne

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets. © 2013 Elsevier B.V.

In this paper we investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for in- vestment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages (spillovers) are analyzed using a dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk.

This paper investigates the price discovery mechanism in the Hang Seng Index markets. The analysis is based on the cross-market volatility spillover effects by using the daily sets of Hang Seng Index (HSI), Hang Seng Finance Index (HSFIN), and Hang Seng Index futures (HSCIS00). In order to testify the influence of 2007 financial tsunami on the volatility spillover effect, the study employs the vector autoregressive model (VAR) and the bivariate GARCH model based on the BEKK parameterization. The testing period has been divided into the pre-crisis (1 April, 2003 to 31 July, 2007) and the crisis & recovery period (1 August, 2007 to 1 April, 2013). The empirical results depict that there exists bi-directional volatility spillover effect between HSI and HSCIS00 for the whole testing period. In contrast, a strong bi-directional volatility spillover effect between HSFIN and HSCIS00 is only recognized after the outbreak of the 2007 financial crisis.

In this paper we investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for in- vestment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages (spillovers) are analyzed using a dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk.

Spillover and contagion effects have gained significant interest in the recent years of financial crisis. Attention has not only been directed to relations between returns of financial variables, but to spillovers in risk as well. I use the family of Constant Conditional Correlation GARCH models to model the risk associated with financial time series and to make inferences about Granger causal relations between second conditional moments. The restrictions for second-order Granger noncausality between two vectors of variables are derived. To assess the credibility of the noncausality hypotheses, I employ posterior odds ratios. This Bayesian method constitutes an alternative for classical tests that makes such testing possible, regardless of the form of the restrictions on the parameters of the model. Moreover, it relaxes the assumptions about the existence of higher-order moments of the processes required in classical tests. In the empirical example, I find that the pound-to-Euro exchange rate second-order causes the US dollar-to-Euro exchange rate, which confirms the meteor shower hypothesis of Engle, Ito & Lin (1990).

Spillover and contagion effects have gained significant interest in the recent years of financial crisis. Attention has not only been directed to relations between returns of financial variables, but to spillovers in risk as well. I use the family of Constant Conditional Correlation GARCH models to model the risk associated with financial time series and to make inferences about Granger causal relations between second conditional moments. The restrictions for second-order Granger noncausality between two vectors of variables are derived. To assess the credibility of the noncausality hypotheses, I employ posterior odds ratios. This Bayesian method constitutes an alternative for classical tests that makes such testing possible, regardless of the form of the restrictions on the parameters of the model. Moreover, it relaxes the assumptions about the existence of higher-order moments of the processes required in classical tests. In the empirical example, I find that the pound-to-Euro exchange rate second-order causes the US dollar-to-Euro exchange rate, which confirms the meteor shower hypothesis of Engle, Ito & Lin (1990).

This paper models the mean and volatility spillovers of prices within the integrated Iberian and the interconnected Spanish and French electricity markets. Using the constant (CCC) and dynamic conditional correlation (DCC) bivariate models with three different specifications of the univariate variance processes, we study the extent to which increasing interconnection and harmonization in regulation have favoured price convergence. The data consist of daily prices calculated as the arithmetic mean of the hourly prices over a span from July 1st 2007 until February 29th 2012. The DCC model in which the variances of the univariate processes are specified with a VARMA(1,1) fits the data best for the integrated MIBEL whereas a CCC model with a GARCH(1,1) specification for the univariate variance processes is selected to model the price series in Spain and France. Results show that there are significant mean and volatility spillovers in the MIBEL, indicating strong interdependence between the two markets, while there is a weaker evidence of integration between the Spanish and French markets. We provide new evidence that the EU target of achieving a single electricity market largely depends on increasing trade between countries and homogeneous rules of market functioning.

The paper investigates the mean and volatility spillover effects from U.S and EU stock markets as well as oil price market into national stock markets of eight European countries. The study finds strong indication of volatility spillover effects from global US, regional EU, and world factor oil towards individual stock markets. While both mean and volatility spillover transmissions from the U.S are found to be significant, E.U mean spillover effects are negligible. To evaluate the volatility spillovers, the variance ratios are computed and the results draw to attention that the individual emerging countries’ stock returns are mostly influenced by the U.S volatility spillovers rather than the EU or oil markets. Additionally, examination of only global and regional stock markets spillover transmissions into European stock markets also confirms the dominating presence of U.S spillover transmissions. Furthermore, I also implement asymmetric tests on stock returns of eight markets. Some evidences of asymmetric effects are reported. In particular, the stock markets of Hungary, Poland, Russia and Ukraine are found to respond asymmetrically to negative and positive shocks in the U.S stock returns. The weak evidence of asymmetric effects with respect to oil market shocks is found only in the case of Russia and the quantified variance ratios indicate that presence of oil market shocks are relatively higher for Russia. Moreover, a model with dummy variable confirms the effect of European Union enlargement on stock returns only for Romania. Finally, a conditional model suggests that the spillover effects are partially explained by instrumental macroeconomic variables, out of which exchange rate fluctuations play a key role in explaining the spillover parameters rather than total trade to GDP ratios in most investigated countries.

This paper models the mean and volatility spillovers of prices within the integrated Iberian and the interconnected Spanish and French electricity markets. Using the constant (CCC) and dynamic conditional correlation (DCC) bivariate models with three different specifications of the univariate variance processes, we study the extent to which increasing interconnection and harmonization in regulation have favoured price convergence. The data consist of daily prices calculated as the arithmetic mean of the hourly prices over a span from July 1st 2007 until February 29th 2012. The DCC model in which the variances of the univariate processes are specified with a VARMA(1,1) fits the data best for the integrated MIBEL whereas a CCC model with a GARCH(1,1) specification for the univariate variance processes is selected to model the price series in Spain and France. Results show that there are significant mean and volatility spillovers in the MIBEL, indicating strong interdependence between the two markets, while there is a weaker evidence of integration between the Spanish and French markets. We provide new evidence that the EU target of achieving a single electricity market largely depends on increasing trade between countries and homogeneous rules of market functioning.

This paper models the mean and volatility spillovers of prices within the integrated Iberian and the interconnected Spanish and French electricity markets. Using the constant (CCC) and dynamic conditional correlation (DCC) bivariate models with three different specifications of the univariate variance processes, we study the extent to which increasing interconnection and harmonization in regulation have favoured price convergence. The data consist of daily prices calculated as the arithmetic mean of the hourly prices over a span from July 1st 2007 until February 29th 2012. The DCC model in which the variances of the univariate processes are specified with a VARMA(1,1) fits the data best for the integrated MIBEL whereas a CCC model with a GARCH(1,1) specification for the univariate variance processes is selected to model the price series in Spain and France. Results show that there are significant mean and volatility spillovers in the MIBEL, indicating strong interdependence between the two markets, while there is a weaker evidence of integration between the Spanish and French markets. We provide new evidence that the EU target of achieving a single electricity market largely depends on increasing trade between countries and homogeneous rules of market functioning.

The paper investigates the mean and volatility spillover effects from U.S and EU stock markets as well as oil price market into national stock markets of eight European countries. The study finds strong indication of volatility spillover effects from global US, regional EU, and world factor oil towards individual stock markets. While both mean and volatility spillover transmissions from the U.S are found to be significant, E.U mean spillover effects are negligible. To evaluate the volatility spillovers, the variance ratios are computed and the results draw to attention that the individual emerging countries’ stock returns are mostly influenced by the U.S volatility spillovers rather than the EU or oil markets. Additionally, examination of only global and regional stock markets spillover transmissions into European stock markets also confirms the dominating presence of U.S spillover transmissions. Furthermore, I also implement asymmetric tests on stock returns of eight markets. Some evidences of asymmetric effects are reported. In particular, the stock markets of Hungary, Poland, Russia and Ukraine are found to respond asymmetrically to negative and positive shocks in the U.S stock returns. The weak evidence of asymmetric effects with respect to oil market shocks is found only in the case of Russia and the quantified variance ratios indicate that presence of oil market shocks are relatively higher for Russia. Moreover, a model with dummy variable confirms the effect of European Union enlargement on stock returns only for Romania. Finally, a conditional model suggests that the spillover effects are partially explained by instrumental macroeconomic variables, out of which exchange rate fluctuations play a key role in explaining the spillover parameters rather than total trade to GDP ratios in most investigated countries.

This paper examines whether there is evidence of spillovers of volatility from the Chinese stock market to its neighbours and trading partners, including Australia, Hong Kong, Singapore, Japan and USA. China’s increasing integration into the global market may have important consequences for investors in related markets. In order to capture these potential effects, we explore these issues using an Autoregressive Moving Average (ARMA) return equation. A univariate GARCH model is then adopted to test for the persistence of volatility in stock market returns, as represented by stock market indices. Finally, univariate GARCH, multivariate VARMA-GARCH, and multivariate VARMA-AGARCH models are used to test for constant conditional correlations and volatility spillover effects across these markets. Each model is used to calculate the conditional volatility between both the Shenzhen and Shanghai Chinese markets and several other markets around the Pacific Basin Area, including Australia, Hong Kong, Japan, Taiwan and Singapore, during four distinct periods, beginning 27 August 1991 and ending 17 November 2010. The empirical results show some evidence of volatility spillovers across these markets in the pre-GFC periods, but there is little evidence of spillover effects from China to relate

This essay examines the volatility spillover effects from oil price shocks across different US and EU industries, using a GJR-GARCH(1,1) model. We conclude that the European industries are much more sensitive to oil and stock market shocks compared to their US counterparts. In US, oil news have significant effect only on Basic Materials, Industrials, Utilities and Consumer Services and coefficient significance depends much on the estimation sample. In contrast, all the EU industry returns are significantly influenced by oil shocks. The most sensitive are Basic Materials and Industrials, while the least affected are Telecommunications, Healthcare and Consumer Goods. However, variance ratios show that the share of oil shocks in an industry’s total volatility remains very small (0-0.46% for US sectors and 0.23-1.55% for EU) compared to the innovations from the broad US and EU stock markets. For futures contracts these ratios are higher, and namely 0.03-2.73% and 0.21-4.66% respectively.

In recent years the volatility of exchange rate exposure and its associated risk have become a hot issue in international financial management. It is often assumed that a firm’s future operating cash flows is proxied by its market value, and the exposure coe fficient would be able to ef ficiently measure the impact of exchange rate changes on a firm’s return and its se nsitivity to the changes. Recen tly, some studies begin to investigate whether exchange rate exposure is asymmetric between currency appreciations and depreciations. By far most existing studies on exchange rate exposure assume that the variances of a firm’s returns and exchange rates changes are time-invariant. In this paper, we assess empirically the validity of this assumption, and argue that the conven iently defined exchange rate exposure is inadequate for measuring the entire impact of exchange rate changes on a firm’s future operating cash flows in cases of time-varying variances. There are at least four alternative routes through which a firm’s returns are exposed to foreign exchange risks when the vari ances are time-variant. The four aspects of exchange rate exposure or the mu lti-elements of exchange rate exposure are defines as follows: • the first route is that a firm’s stock returns are e xposed to the exchange rate changes either directly or indirectly through its business linkages with other firms. • the second route captures the exposure to the volatility of exchange rate changes, namely, the sensitivity of a firm’s value to the degree of fluctuations of exchange rates. If the degree of fluctuations is time-varying, the firm may react to change its marketing, production location and hedging strategies. • the third level of exchange rate exposure measures the sensitivity of conditional variance of the returns to the volatility of exchange rate changes. Even if the second relationship is absent, as long as the conditional variances of returns are exposed to volatility of exchange rate c

This essay examines the volatility spillover effects from oil price shocks across different US and EU industries, using a GJR-GARCH(1,1) model. We conclude that the European industries are much more sensitive to oil and stock market shocks compared to their US counterparts. In US, oil news have significant effect only on Basic Materials, Industrials, Utilities and Consumer Services and coefficient significance depends much on the estimation sample. In contrast, all the EU industry returns are significantly influenced by oil shocks. The most sensitive are Basic Materials and Industrials, while the least affected are Telecommunications, Healthcare and Consumer Goods. However, variance ratios show that the share of oil shocks in an industry’s total volatility remains very small (0-0.46% for US sectors and 0.23-1.55% for EU) compared to the innovations from the broad US and EU stock markets. For futures contracts these ratios are higher, and namely 0.03-2.73% and 0.21-4.66% respectively.

This paper investigates the conditional correlations and volatility spillovers between crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.

This paper explores and compares the effects of two financial crises (the 1997 Asian Financial Crisis and the 2007-2010 Subprime Financial Crisis) on short-run and long-run linkages between equity markets in China (mainland and Hong Kong) and US. In particular, we not only investigate the return causality relationships by applying vector autoregressive (VAR) analysis, but we also examine the volatility spillover effects by using a multivariate GARCH - BEKK model. The empirical findings indicate that, although the financial markets in mainland China have gradually opened and become more liberalized, the mainland stock indices are not cointegrated with US and Hong Kong in the long run. However, in the short run, the spillover effects on return and volatility exist between different groups of equity markets. Overall, compared to the Asian Crisis, the dynamic interactions between China and US have increased during the Subprime Crisis.

Asia is presently the most important market for the production and consumption of natural rubber. World prices of rubber are not only subject to changes in demand, but also to speculation regarding future markets. Japan and Singapore are the major futures markets for rubber, while Thailand is one of the world’s largest producers of rubber. As rubber prices are influenced by external markets, it is important to analyse the relationship between the relevant markets in Thailand, Japan and Singapore. The analysis is conducted using several alternative multivariate GARCH models. The empirical results indicate that the constant conditional correlations arising from the CCC model of Bollerslev (1990) lie in the low to medium range. The results from the VARMA-GARCH model of Ling and McAleer (2003) and the VARMA-AGARCH model of McAleer et al. (2009) suggest the presence of volatility spillovers and asymmetric effects of positive and negative return shocks on conditional volatility. Finally, the DCC model of Engle (2002) suggests that the conditional correlations can vary dramatically over time. In general, the dynamic conditional correlations in rubber spot and futures returns shocks can be independent or interdependent.

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover effects across and within the four markets, using three multivariate GARCH models, namely the CCC, VARMA-GARCH and VARMA-AGARCH models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecasted conditional correlations between pairs of crude oil returns have both positive and negative trends.

International and domestic tourism are leading economic activities in the world today. Tourism has been known to generate goods and services directly and indirectly, attract foreign currency, stimulate employment, and provide opportunities for investment. It has also been recognized as an important means for achieving economic development. Substantial research has been conducted to evaluate the role of international tourism, and its associated volatility, within and across various economies. This paper applies several recently developed models of multivariate conditional volatility to investigate the interdependence of international tourism demand, as measured by international tourist arrivals, and its associated volatility in the four leading destinations in ASEAN, namely Indonesia, Malaysia, Singapore and Thailand. Each of these countries has attractive tourism characteristics, such as significant cultural and natural resources. Shocks to international tourism demand volatility could affect, positively or negatively, the volatility in tourism demand of neighbouring countries. The empirical results should encourage regional co-operation in tourism development among ASEAN member countries, and also mobilize international and regional organizations to provide appropriate policy actions.

Yong, J., & Do, A. (2017). Interdependence of REIT market volatility under an E-GARCH-M framework. In Proceedings of the 2nd Business Doctorl and Emerging Scholars Conference (pp. 64-72). Available here

This paper investigates the channels of volatility transmission across stock index futures in 6 major developed and emerging markets in Asia. We analyse whether the popular volatility spillovers tests are susceptible to the choice of range volatility estimators. Our results demonstrate strong linkages between markets within the Asian region, indicating that the signal receiving markets are sensitive to both negative and positive volatility shocks, which reveals the asymmetric nature of volatility transmission channels. We find that some markets play a destabilizing role while other countries - contrary to popular belief - have a stabilizing effect on other markets in Asia.