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A general multivariate threshold GARCH model with dynamic conditional correlations

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Fabio Trojani ()
Francesco Audrino

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Abstract

We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance matrices is naturally ensured by the pure model structure. Conditional thresholds in volatilities and correlations are estimated from the data, together with all other model parameters. We study the performance of our approach in some Monte Carlo simulations, where it is shown that the model is able to fit correctly a GARCH-type dynamics and a complex threshold structure in conditional volatilities and correlations of simulated data. In a real data application to international equity markets, we observe estimated conditional volatilities that are strongly influenced by GARCH-type and multivariate threshold effects. Conditional correlations, instead, are determined by simple threshold structures where no GARCH-type effect could be identified.

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Paper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2005 with number 2005-04.

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Length: 41 pages
Date of creation: Jan 2005
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Handle: RePEc:usg:dp2005:2005-04

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Olivier Ledoit & Pedro Santa-Clara & Michael Wolf, 2003. "Flexible Multivariate GARCH Modeling with an Application to International Stock Markets," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 735-747, 07. [Downloadable!] (restricted)
  2. Becker, Kent G. & Finnerty, Joseph E. & Friedman, Joseph, 1995. "Economic news and equity market linkages between the U.S. and U.K," Journal of Banking & Finance, Elsevier, vol. 19(7), pages 1191-1210, October. [Downloadable!] (restricted)
  3. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2003. "Choosing the Best Volatility Models: The Model Confidence Set Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 839-861, December. [Downloadable!] (restricted)
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  4. Fabio Trojani & Francesco Audrino, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369. [Downloadable!]
  5. Fulvio Corsi & Francesco Audrino, 2007. "Realized Correlation Tick-by-Tick," University of St. Gallen Department of Economics working paper series 2007 2007-02, Department of Economics, University of St. Gallen. [Downloadable!]
  6. Pagan, Adrian, 1986. "Two Stage and Related Estimators and Their Applications," Review of Economic Studies, Blackwell Publishing, vol. 53(4), pages 517-38, August. [Downloadable!] (restricted)
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  7. Ole E. Barndorff-Nielsen & Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280. [Downloadable!] (restricted)
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  8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March. [Downloadable!] (restricted)
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  9. Bae, Kee-Hong & Andrew Karolyi, G., 1994. "Good news, bad news and international spillovers of stock return volatility between Japan and the U.S," Pacific-Basin Finance Journal, Elsevier, vol. 2(4), pages 405-438, December. [Downloadable!] (restricted)
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  10. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier. [Downloadable!] (restricted)
  11. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August. [Downloadable!] (restricted)
  12. Sang W. Kim & John H. Rogers, 1995. "International stock price spillovers and market liberalization: evidence from Korea, Japan, and the United States," International Finance Discussion Papers 499, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
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  13. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  14. Hamao, Yasushi & Masulis, Ronald W & Ng, Victor, 1990. "Correlations in Price Changes and Volatility across International Stock Markets," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 3(2), pages 281-307. [Downloadable!] (restricted)
  15. Koutmos, Gregory & Booth, G Geoffrey, 1995. "Asymmetric volatility transmission in international stock markets," Journal of International Money and Finance, Elsevier, vol. 14(6), pages 747-762, December. [Downloadable!] (restricted)
  16. Audrino, Francesco, 2006. "Tree-Structured Multiple Regimes in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 338-353, July. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Fulvio Corsi & Francesco Audrino, 2008. "Modeling Tick-by-Tick Realized Correlations," University of St. Gallen Department of Economics working paper series 2008 2008-05, Department of Economics, University of St. Gallen. [Downloadable!]
  2. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Modelling Conditional Correlations for Risk Diversification in Crude Oil Markets," CIRJE F-Series CIRJE-F-640, CIRJE, Faculty of Economics, University of Tokyo. [Downloadable!]
    Other versions:
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