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Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution

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  • Pesaran, Bahram

    () (affiliation not available)

  • Pesaran, M. Hashem

    () (University of Cambridge)

Abstract

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC estimation procedure is applied to a portfolio of daily returns on currency futures, government bonds and equity index futures. The results strongly reject the normal-DCC model in favour of a t-DCC specification. The t-DCC model also passes a number of VaR diagnostic tests over an evaluation sample. The estimation results suggest a general trend towards a lower level of return volatility, accompanied by a rising trend in conditional cross correlations in most markets; possibly reflecting the advent of euro in 1999 and increased interdependence of financial markets.

Suggested Citation

  • Pesaran, Bahram & Pesaran, M. Hashem, 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," IZA Discussion Papers 2906, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp2906
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    1. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
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    6. Bauwens, Luc & Laurent, Sebastien, 2005. "A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
    7. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
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    11. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    12. Gabriele Fiorentini & Enrique Sentana & Giorgio Calzolari, 2000. "The Score Of Conditionally Heteroskedastic Dynamic Regression Models With Student T Innovations, An Lm Test For Multivariate Normality," Working Papers. Serie AD 2000-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    13. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
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    Citations

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    Cited by:

    1. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    2. Rizvi , Syed Aun R & Arshad , Shaista, 2014. "An Empirical Study of Islamic Equity as a Better Alternative during Crisis Using Multivariate GARCH DCC," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 22, pages 159-184.
    3. Masih, Mansur & Majid, Hamdan Abdul, 2013. "The Volatility and Correlations of Stock Returns of Some Crisis-Hit Countries: US, Greece, Thailand and Malaysia: Evidence from MGARCH-DCC applications," MPRA Paper 58946, University Library of Munich, Germany.
    4. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
    5. Samitas, Aristeidis & Tsakalos, Ioannis, 2013. "How can a small country affect the European economy? The Greek contagion phenomenon," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 18-32.
    6. Rahim, Adam Mohamed & Masih, Mansur, 2016. "Portfolio diversification benefits of Islamic investors with their major trading partners: Evidence from Malaysia based on MGARCH-DCC and wavelet approaches," Economic Modelling, Elsevier, vol. 54(C), pages 425-438.
    7. Pesaran, Bahram & Pesaran, M. Hashem, 2010. "Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash," Economic Modelling, Elsevier, vol. 27(6), pages 1398-1416, November.
    8. Rizvi, Syed Aun & Masih, Mansur, 2013. "Do Shariah (Islamic) Indices Provide a Safer Avenue in Crisis? Empirical Evidence from Dow Jones Indices using Multivariate GARCH-DCC," MPRA Paper 57701, University Library of Munich, Germany.
    9. repec:dau:papers:123456789/6913 is not listed on IDEAS

    More about this item

    Keywords

    volatilities and correlations; futures market; multivariate t; financial interdependence; VaR diagnostics;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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