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Assessing some stylized facts about financial market indexes: a Markov copula approach

Author

Listed:
  • Osvaldo Candido Silva Filho
  • Flavio Augusto Ziegelmann

Abstract

Purpose - – The aim of this paper is to measure and evaluate the relationship between returns-volatility and trading volume and returns and volatility of financial market indexes using time-varying copulas. Design/methodology/approach - – The time dynamic dependence parameter is allowed to evolve according to a restricted ARMA-type equation which includes a constant term that is driven by a hidden two-state first-order Markov chain. Findings - – In using this time dynamics in conjunction with non-elliptical distribution functions and tail dependence measure, the authors are allowing for (and focusing on) non-linearities in the returns-volume-volatility relationship. The results support the assumption that current trading volume provides information about future volatility as well as that there is a negative relationship between returns and their volatilities in financial market indexes. Originality/value - – The authors provide an interesting empirical interpretation for the regimes the authors have identified: in the high dependence regime the sequential information arrival hypothesis and/or noise trading hypothesis are valid, consequently future volatility prediction is possible and persistent but does not last indefinitely; in the low dependence regime, the future volatility prediction is more unlikely to occur, since both trading volume and return negatives have a low (near zero) relation with future volatility.

Suggested Citation

  • Osvaldo Candido Silva Filho & Flavio Augusto Ziegelmann, 2014. "Assessing some stylized facts about financial market indexes: a Markov copula approach," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 253-271, March.
    • Handle: RePEc:eme:jespps:v:41:y:2014:i:2:p:253-271
    DOI: 10.1108/JES-06-2012-0080
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    Citations

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    Cited by:

    1. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    2. Julio Cesar Araujo da Silva Junior, 2017. "An S-Shaped Crude Oil Price Return-Implied Volatility Relation: Parametric and Nonparametric Estimations," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(12), pages 54-70, December.
    3. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.

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