Alessandro Gnoatto, M. Grasselli, J. D. da Fonseca
We present a flexible approach for the valuation of interest rate derivatives based on affine processes. We extend the methodology proposed in Keller-Ressel et al. (in press) by changing the choice of the state space. We provide semi-closed-form solutions for the pricing of caps and floors. We then show that it is possible to price swaptions in this multifactor setting with a good degree of analytical tractability. This is done via the Edgeworth expansion approach developed in Collin-Dufresne and Goldstein (2002). A numerical exercise illustrates the flexibility of Wishart Libor model in describing the movements of the implied volatility surface.
{"title":"A Flexible Matrix Libor Model with Smiles","authors":"Alessandro Gnoatto, M. Grasselli, J. D. da Fonseca","doi":"10.2139/ssrn.2027034","DOIUrl":"https://doi.org/10.2139/ssrn.2027034","url":null,"abstract":"We present a flexible approach for the valuation of interest rate derivatives based on affine processes. We extend the methodology proposed in Keller-Ressel et al. (in press) by changing the choice of the state space. We provide semi-closed-form solutions for the pricing of caps and floors. We then show that it is possible to price swaptions in this multifactor setting with a good degree of analytical tractability. This is done via the Edgeworth expansion approach developed in Collin-Dufresne and Goldstein (2002). A numerical exercise illustrates the flexibility of Wishart Libor model in describing the movements of the implied volatility surface.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134072008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I identify a global currency skewness risk factor. Currency portfolios that have higher average excess returns co-vary more positively with this risk factor. They suffer losses in bad times for currency investors when high interest rate investment currencies have a greater tendency to depreciate sharply as a group relative to low interest rate funding currencies. Consequently, they earn higher average excess returns as reward for exposure to this risk. I create three sets of sorted currency portfolios reflecting three distinct sources of variation in average excess currency returns. The first set sorts currencies based on interest rate differentials. The second set sorts currencies based on currency momentum. The third set sorts currencies based on currency undervaluedness relative to the benchmark purchasing power parity (PPP) implied exchange rates. Within these sets of sorted currency portfolios, currencies with higher interest rates earn higher average excess returns. Secondly, currencies that are higher momentum currencies (currencies with higher recent excess returns) earn higher average excess returns. Thirdly, currencies that are more undervalued relative to the PPP implied level earn higher average excess returns. I find that differences in exposure to the global currency skewness risk factor can explain the systematic variation in average excess currency returns within all three groups of portfolios much better than existing foreign exchange risk factors in the literature.
{"title":"Currency Returns, Skewness and Crash Risk","authors":"B. Rafferty","doi":"10.2139/ssrn.2022920","DOIUrl":"https://doi.org/10.2139/ssrn.2022920","url":null,"abstract":"I identify a global currency skewness risk factor. Currency portfolios that have higher average excess returns co-vary more positively with this risk factor. They suffer losses in bad times for currency investors when high interest rate investment currencies have a greater tendency to depreciate sharply as a group relative to low interest rate funding currencies. Consequently, they earn higher average excess returns as reward for exposure to this risk. I create three sets of sorted currency portfolios reflecting three distinct sources of variation in average excess currency returns. The first set sorts currencies based on interest rate differentials. The second set sorts currencies based on currency momentum. The third set sorts currencies based on currency undervaluedness relative to the benchmark purchasing power parity (PPP) implied exchange rates. Within these sets of sorted currency portfolios, currencies with higher interest rates earn higher average excess returns. Secondly, currencies that are higher momentum currencies (currencies with higher recent excess returns) earn higher average excess returns. Thirdly, currencies that are more undervalued relative to the PPP implied level earn higher average excess returns. I find that differences in exposure to the global currency skewness risk factor can explain the systematic variation in average excess currency returns within all three groups of portfolios much better than existing foreign exchange risk factors in the literature.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125016450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper assesses the effects of domestic football teams’ performances against foreign rivals on stock market returns as well as on the return-volatility relationship. The data from Chile, Spain, Turkey and the United Kingdom support the propositions that the results of football teams in international cups affect (i) stock market returns and (ii) the risk-return relationship. Evidence from Spain and the UK (countries considered football powerhouses) suggest that losses are associated with lower returns and higher risk aversion (agents become less risk loving) but the evidence from Chile and Turkey (where football is the most important sport but the teams are not as successful) reveals that wins are associated with higher returns and lower risk aversion (agents become more risk loving).
{"title":"Effects of Football on Stock Markets: Return-Volatility Relationship","authors":"H. Berument, N. Ceylan","doi":"10.2139/ssrn.2020971","DOIUrl":"https://doi.org/10.2139/ssrn.2020971","url":null,"abstract":"This paper assesses the effects of domestic football teams’ performances against foreign rivals on stock market returns as well as on the return-volatility relationship. The data from Chile, Spain, Turkey and the United Kingdom support the propositions that the results of football teams in international cups affect (i) stock market returns and (ii) the risk-return relationship. Evidence from Spain and the UK (countries considered football powerhouses) suggest that losses are associated with lower returns and higher risk aversion (agents become less risk loving) but the evidence from Chile and Turkey (where football is the most important sport but the teams are not as successful) reveals that wins are associated with higher returns and lower risk aversion (agents become more risk loving).","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126576392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for structural change in α. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans a wide variety of long-term developed and emerging financial asset returns. Somewhat surprisingly, the tail behavior of emerging stock markets is not more strongly inclined to structural change than their developed counterparts. Emerging currencies, on the contrary, are more prone to shifts in the tail behavior than developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks or in assessing the (changing) propensity to financial crises can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds. However, our break results also indicate it is advisable to use shorter estimation windows when applying EVT methods to emerging currency portfolios.
{"title":"Long-Term Asset Tail Risk in Developed and Emerging Markets","authors":"S. Straetmans, B. Candelon","doi":"10.2139/ssrn.2020746","DOIUrl":"https://doi.org/10.2139/ssrn.2020746","url":null,"abstract":"The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for structural change in α. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans a wide variety of long-term developed and emerging financial asset returns. Somewhat surprisingly, the tail behavior of emerging stock markets is not more strongly inclined to structural change than their developed counterparts. Emerging currencies, on the contrary, are more prone to shifts in the tail behavior than developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks or in assessing the (changing) propensity to financial crises can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds. However, our break results also indicate it is advisable to use shorter estimation windows when applying EVT methods to emerging currency portfolios.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126385893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-08DOI: 10.7835/JCC-BERJ-2012-0069
M. Dash, Jay H. Dagha, P. Sharma, Rashmi Singhal
Derivatives have become widely accepted as tools for hedging and risk-management, as well as speculation to some extent. A more recent trend has been gaining ground, namely, arbitrage in derivatives. The critical parameter in derivatives pricing is the volatility of the underlying asset. Exchanges often overestimate volatility in order to cover any sudden changes in market behavior, leading to systematic overpricing of derivatives. Accurate forecasting of volatility would expose systematic overpricing. Unfortunately, volatility is not an easy phenomenon to predict or forecast. One class of models that have proved successful in forecasting volatility in many situations is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family of models. The objective of the present study is to analyze systematic bias in the pricing of options derivatives. In order to perform the analysis, data were collected for a sample of stock options traded on the National Stock Exchange (NSE) of India and their underlying stocks. In the study, GARCH models are used to forecast underlying stock volatility, and the forecasted volatility is used in the Black-Scholes model in order to determine whether the corresponding options were fairly priced. Any systematic bias in options pricing would provide evidence for arbitrage opportunities.
{"title":"An Application of GARCH Models in Detecting Systematic Bias in Options Pricing and Determining Arbitrage in Options","authors":"M. Dash, Jay H. Dagha, P. Sharma, Rashmi Singhal","doi":"10.7835/JCC-BERJ-2012-0069","DOIUrl":"https://doi.org/10.7835/JCC-BERJ-2012-0069","url":null,"abstract":"Derivatives have become widely accepted as tools for hedging and risk-management, as well as speculation to some extent. A more recent trend has been gaining ground, namely, arbitrage in derivatives. The critical parameter in derivatives pricing is the volatility of the underlying asset. Exchanges often overestimate volatility in order to cover any sudden changes in market behavior, leading to systematic overpricing of derivatives. Accurate forecasting of volatility would expose systematic overpricing. Unfortunately, volatility is not an easy phenomenon to predict or forecast. One class of models that have proved successful in forecasting volatility in many situations is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family of models. The objective of the present study is to analyze systematic bias in the pricing of options derivatives. In order to perform the analysis, data were collected for a sample of stock options traded on the National Stock Exchange (NSE) of India and their underlying stocks. In the study, GARCH models are used to forecast underlying stock volatility, and the forecasted volatility is used in the Black-Scholes model in order to determine whether the corresponding options were fairly priced. Any systematic bias in options pricing would provide evidence for arbitrage opportunities.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116412316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market indices and neglected the potential long-term dynamics, our econometric evaluation is based on sector level data and caters for both the short-term and long-term dynamics of the assets as well as for the lack of leverage in the direct real estate indices. In addition to the real estate and stock market indices, the analysis includes a number of fundamental variables that are expected to influence real estate and stock returns significantly. We estimate vector error-correction models and investigate the forecast error variance decompositions and impulse responses of the assets. Both the variance decompositions and impulse responses suggest that the long-run REIT market performance is much more closely related to the direct real estate market than to the general stock market. Consequently, REITs and direct real estate should be relatively good substitutes in a long-horizon investment portfolio. The results are of relevance regarding the relationship between public and private markets in general, as the ‘duality’ of the real estate markets offers an opportunity to test whether and how closely securitized asset returns reflect the performance of underlying private assets. The study also includes implications concerning the recent financial crisis.
{"title":"Are REITs Real Estate? Evidence from International Sector Level Data","authors":"Martin Hoesli, Elias Oikarinen","doi":"10.2139/ssrn.2034377","DOIUrl":"https://doi.org/10.2139/ssrn.2034377","url":null,"abstract":"The aim of this study is to examine whether securitized real estate returns reflect direct real estate returns or general stock market returns using international data for the U.S., U.K., and Australia. In contrast to previous research, which has generally relied on overall real estate market indices and neglected the potential long-term dynamics, our econometric evaluation is based on sector level data and caters for both the short-term and long-term dynamics of the assets as well as for the lack of leverage in the direct real estate indices. In addition to the real estate and stock market indices, the analysis includes a number of fundamental variables that are expected to influence real estate and stock returns significantly. We estimate vector error-correction models and investigate the forecast error variance decompositions and impulse responses of the assets. Both the variance decompositions and impulse responses suggest that the long-run REIT market performance is much more closely related to the direct real estate market than to the general stock market. Consequently, REITs and direct real estate should be relatively good substitutes in a long-horizon investment portfolio. The results are of relevance regarding the relationship between public and private markets in general, as the ‘duality’ of the real estate markets offers an opportunity to test whether and how closely securitized asset returns reflect the performance of underlying private assets. The study also includes implications concerning the recent financial crisis.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132954534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps. One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to jumps. We improve the scope and efficiency of multipower variation by the use of a more sophisticated exploitation of high frequency data. This suggests very significant improvements in the power of jump tests. It also yields efficient estimates of the integrated variance of the continuous part of a semimartingale. The paper also shows how to extend the theory to the case where there is microstructure in the observations and derive the first nonparametric high frequency estimator of the volatility of volatility. A fundamental device in the paper is a new type of result showing path-by-path (strong) approximation between multipower and the (unobserved) RV based on the continuous part of the process.
{"title":"Efficient and Feasible Inference for the Components of Financial Variation Using Blocked Multipower Variation","authors":"P. Mykland, N. Shephard, Kevin Sheppard","doi":"10.2139/ssrn.2008690","DOIUrl":"https://doi.org/10.2139/ssrn.2008690","url":null,"abstract":"High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps. One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to jumps. We improve the scope and efficiency of multipower variation by the use of a more sophisticated exploitation of high frequency data. This suggests very significant improvements in the power of jump tests. It also yields efficient estimates of the integrated variance of the continuous part of a semimartingale. The paper also shows how to extend the theory to the case where there is microstructure in the observations and derive the first nonparametric high frequency estimator of the volatility of volatility. A fundamental device in the paper is a new type of result showing path-by-path (strong) approximation between multipower and the (unobserved) RV based on the continuous part of the process.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121757590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article describes the expectation and measure groups of the quadratic Gaussian algebra, and considers their application in the pricing of interest rate and cross asset derivatives. The discussion is motivated by the desire to construct consistent, arbitrage-free, term structure pricing models, that incorporate multi-factor decorrelation and credible smile dynamics in a robust and easy to implement framework. The article concludes with the application of symmetry techniques in the construction of the quadratic Gaussian Libor model.
{"title":"Symmetry Methods for the Quadratic Gaussian Libor Model","authors":"P. Mccloud","doi":"10.2139/ssrn.2007823","DOIUrl":"https://doi.org/10.2139/ssrn.2007823","url":null,"abstract":"This article describes the expectation and measure groups of the quadratic Gaussian algebra, and considers their application in the pricing of interest rate and cross asset derivatives. The discussion is motivated by the desire to construct consistent, arbitrage-free, term structure pricing models, that incorporate multi-factor decorrelation and credible smile dynamics in a robust and easy to implement framework. The article concludes with the application of symmetry techniques in the construction of the quadratic Gaussian Libor model.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127642170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is a widespread view that derivatives played a crucial role during the recent financial and economic crisis. This opinion manifested in headlines such as “Why Derivatives Caused Financial Crisis” and derivatives have been termed “Financial Weapons of Mass Destruction”. However, the analysis of the role of derivatives in the economy requires a much more differentiated discussion as the statements given above imply. In this paper we analyze the effect of institutionalization of derivatives trading on economic growth and economic growth volatility; measuring growth in GDP per capita. The relationship between the institutionalization of derivatives trading and economic growth is investigated by using a panel data set comprising of 45 countries observed over 39 years. Our results show a statistically and economically significant positive effect of the establishment and existence of a domestic derivatives exchange on economic growth. These results are robust to different model specifications and to controlling for financial reforms. The effect of institutionalized derivatives trading on growth volatility is analyzed by means of an EGARCH model and is found to be negative and significant.
{"title":"Does the Institutionalization of Derivatives Trading Spur Economic Growth?","authors":"Paulo Rodrigues, C. Schwarz, Norman J. Seeger","doi":"10.2139/ssrn.2014805","DOIUrl":"https://doi.org/10.2139/ssrn.2014805","url":null,"abstract":"It is a widespread view that derivatives played a crucial role during the recent financial and economic crisis. This opinion manifested in headlines such as “Why Derivatives Caused Financial Crisis” and derivatives have been termed “Financial Weapons of Mass Destruction”. However, the analysis of the role of derivatives in the economy requires a much more differentiated discussion as the statements given above imply. In this paper we analyze the effect of institutionalization of derivatives trading on economic growth and economic growth volatility; measuring growth in GDP per capita. The relationship between the institutionalization of derivatives trading and economic growth is investigated by using a panel data set comprising of 45 countries observed over 39 years. Our results show a statistically and economically significant positive effect of the establishment and existence of a domestic derivatives exchange on economic growth. These results are robust to different model specifications and to controlling for financial reforms. The effect of institutionalized derivatives trading on growth volatility is analyzed by means of an EGARCH model and is found to be negative and significant.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129797800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper gauges volatility transmission between stock markets by testing conditional independence of their volatility measures. In particular, we check whether the conditional density of the volatility changes if we further condition on the volatility of another market. We employ nonparametric methods to estimate the conditional densities and model-free realized measures of volatility, allowing for both microstructure noise and jumps. We establish the asymptotic normality of the test statistic as well as the first-order validity of the bootstrap analog. Finally, we uncover significant volatility spillovers between the stock markets in China, Japan, UK and US.
{"title":"International Market Links and Volatility Transmission","authors":"V. Corradi, W. Distaso, Marcelo Fernandes","doi":"10.2139/ssrn.2005006","DOIUrl":"https://doi.org/10.2139/ssrn.2005006","url":null,"abstract":"This paper gauges volatility transmission between stock markets by testing conditional independence of their volatility measures. In particular, we check whether the conditional density of the volatility changes if we further condition on the volatility of another market. We employ nonparametric methods to estimate the conditional densities and model-free realized measures of volatility, allowing for both microstructure noise and jumps. We establish the asymptotic normality of the test statistic as well as the first-order validity of the bootstrap analog. Finally, we uncover significant volatility spillovers between the stock markets in China, Japan, UK and US.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124088718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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