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

Osvaldo Candido and Flavio Augusto Ziegelmann

Journal of Economic Studies, 2014, vol. 41, issue 2, 253-271

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.

Keywords: Copulas; Markov switching; Tail dependence; Time-varying parameters (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:jespps:v:41:y:2014:i:2:p:253-271

DOI: 10.1108/JES-06-2012-0080

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