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Return Interval, Dependence Structure and Multivariate Normality

Author

Listed:
  • Thierry Ané
  • Chiraz Labidi

Abstract

We focus on changes in the multivariate distribution of index returns stemming purely from varying the return interval, assuming daily to quarterly returns. Whereas longtailedness is present in daily returns, we find that, in agreement with a well-established idea, univariate return distributions converge to normality as the return interval is lengthened. Such convergence does not occur, however, for multivariate distributions. Using a new method to parametrically model the dependence structure implying negative asymptotic dependence in return series is the reason for the rejection of multivariate normality for low return frequencies.

Suggested Citation

  • Thierry Ané & Chiraz Labidi, 2001. "Return Interval, Dependence Structure and Multivariate Normality," Research Paper Series 64, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:64
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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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