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Multivariate skewed t-distribution with degrees of freedom vector and its application to financial modeling

Author

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  • Balaev , Alexey

    (Higher School of Economics, Moscow)

Abstract

A modification of multivariate t-distribution with vector of degrees of freedom is suggested: multivariate t-distribution with vector of skewness parameters and vector of degrees of freedom is introduced. A special case of this distribution is already known multivariate skew t-distribution with scalar parameter of degrees of freedom. Application of the constructed distribution in BEKK models is considered.

Suggested Citation

  • Balaev , Alexey, 2011. "Multivariate skewed t-distribution with degrees of freedom vector and its application to financial modeling," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 23(3), pages 79-97.
    • Handle: RePEc:ris:apltrx:0093
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    References listed on IDEAS

    as
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    4. Vlaar, Peter J G & Palm, Franz C, 1993. "The Message in Weekly Exchange Rates in the European Monetary System: Mean Reversion, Conditional Heteroscedasticity, and Jumps," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 351-360, July.
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    6. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
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    More about this item

    Keywords

    multivariate t-distribution; skewness; heavy tails; conditional density function;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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