Assessing some stylized facts about financial market indexes: a Markov copula approach. Issue 2 (2014)

• Record Type: Journal Article
• Authors: Osvaldo Candido Silva Filho; Flavio Augusto Ziegelmann
• Is Part Of: Journal of economic studies. Volume 41:Issue 2(2014)
• Page Start: 253
• Page End: 271
• Publication Date: 2014
• Subjects: Economics -- Periodicals; 330.05
• DOI: 10.1108/JES-06-2012-0080
• Languages: English
• ISSNs: 0144-3585

Abstract

<abstract> <title> <x xml:space="preserve"> Abstract </x> </title> <p> <bold>Purpose</bold> – 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. <bold>Design/methodology/approach</bold> – 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. <bold>Findings</bold> – 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. <bold>Originality/value</bold> – 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.</p> <ack> <title> <x xml:space="preserve"> Acknowledgements </x> </title> <p> <bold>JEL classification</bold> – C15, C46, G15 The first author gratefully acknowledges the financial support of CNPq (406568/2012‐0).</p> </ack> </abstract>