Unconditional and conditional distributional models for the Nikkei index

Stefan Mittnik, Marc S. Paolella, Svetlozar T. Rachev

Research output: Contribution to journalArticle

28 Scopus citations

Abstract

We investigate alternative unconditional and conditional distributional models for the returns on Japan's Nikkei 225 stock market index. Among them is the recently introduced class of ARMA-GARCH models driven by α-stable (or stable Paretian) distributed innovations, designed to capture the observed serial dependence, conditional heteroskedasticity and fat-tailedness present in the return data. Of the eight entertained distributions, the partially asymmetric Weibull, Student's t and asymmetric α-stable present themselses as the most viable candidates in terms of overall fit. However, the tails of the sample distribution are approximated best by the asymmetric α-stable distribution. Good tail approximations are particularly important for risk assessments.

Original languageEnglish
Pages (from-to)99-128
Number of pages30
JournalAsia-Pacific Financial Markets
Volume5
Issue number2
DOIs
StatePublished - 1998

Keywords

  • GARCH
  • Persistence
  • Skewness
  • Stable Paretian distribution
  • Volatility

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