A new approach to modeling co-movement of international equity markets: Evidence of unconditional copula-based simulation of tail dependence

Wei Sun, Svetlozar Rachev, Frank J. Fabozzi, Setko S. Kalev

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33 Scopus citations

Abstract

Analyzing equity market co-movements is important for risk diversification of an international portfolio. Copulas have several advantages compared to the linear correlation measure in modeling co-movement. This paper introduces a copula ARMA-GARCH model for analyzing the co-movement of international equity markets. The model is implemented with an ARMA-GARCH model for the marginal distributions and a copula for the joint distribution. After goodness of fit testing, we find that the Student's t copula ARMA(1,1)-GARCH(1,1) model with fractional Gaussian noise is superior to alternative models investigated in our study where we model the simultaneous co-movement of nine international equity market indexes. This model is also suitable for capturing the long-range dependence and tail dependence observed in international equity markets.

Original languageEnglish
Pages (from-to)201-229
Number of pages29
JournalEmpirical Economics
Volume36
Issue number1
DOIs
StatePublished - 2009

Keywords

  • Copula
  • Fractional Gaussian noise
  • High-frequency data
  • Self-similarity
  • Tail dependence

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