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Threshold linkages between volatility and trading volume: evidence from developed and emerging markets

Threshold linkages between volatility and trading volume: evidence from developed and emerging... Abstract This paper studies volatility dynamics and provides further insights into its relationship with trading volume. In particular, we examine whether trading volume is significantly informative for investors when attempting to apprehend potential changes in volatility dynamics, and hence, in the evolution of market risk. To this end, we apply recent nonlinear modeling tools, namely Switching Transition Regression (STR) models that are robust to asymmetry and nonlinearity as well as TARCH models to check for the nature of transition between volatility regimes. Our findings show that volatility dynamics exhibit nonlinearity and switching regimes for which the transition is smooth rather than abrupt. Furthermore, one regime is associated with low volatility and a weak relationship with trading volume while in the second regime, the causality relationship is stronger and volatility is high. The paper’s novelty is to show that not only does trading volume contribute to explaining market volatility, but also that the change in volatility dynamics is performed through the change in its relationship with trading volume. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Threshold linkages between volatility and trading volume: evidence from developed and emerging markets

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Publisher
de Gruyter
Copyright
Copyright © 2013 by the
ISSN
1081-1826
eISSN
1558-3708
DOI
10.1515/snde-2012-0040
Publisher site
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Abstract

Abstract This paper studies volatility dynamics and provides further insights into its relationship with trading volume. In particular, we examine whether trading volume is significantly informative for investors when attempting to apprehend potential changes in volatility dynamics, and hence, in the evolution of market risk. To this end, we apply recent nonlinear modeling tools, namely Switching Transition Regression (STR) models that are robust to asymmetry and nonlinearity as well as TARCH models to check for the nature of transition between volatility regimes. Our findings show that volatility dynamics exhibit nonlinearity and switching regimes for which the transition is smooth rather than abrupt. Furthermore, one regime is associated with low volatility and a weak relationship with trading volume while in the second regime, the causality relationship is stronger and volatility is high. The paper’s novelty is to show that not only does trading volume contribute to explaining market volatility, but also that the change in volatility dynamics is performed through the change in its relationship with trading volume.

Journal

Studies in Nonlinear Dynamics & Econometrics – de Gruyter

Published: May 1, 2013

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    Zakoian
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    Engle
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    Fleming
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    Harris
  • Testing for a Unit Root in Time Series Regressions
    Phillips
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    Gennotte
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    Harris
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    Van Dijk
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    Saatcioglu
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    Ureche
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    Subrahmanyan
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    Wagner
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    Glosten
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    Bollerslev
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    Poon
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    Bollerslev
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    Lee
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    Lamoureux
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    Glosten
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    Bollerslev
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    Harris
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    Lobato
  • Surprise Volume and Heteroskedasticity in Equity Market Returns
    Wagner
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    Harris
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    Cai
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    Teräsvirta
  • The of Bid - Ask Spreads Trading Volume and Return Volatility : Evidence from DAX of
    Hussain
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    Admati
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    Andersen
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    Poon
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    Wang
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    Ureche
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    Dumas
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    Liesenfeld
  • Model of Competitive Stock Trading Volume of
    Wang
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    Andersen
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    Granger
  • More on the Volatility - Trading Volume Relationship in Emerging Markets : The Chinese Stock Market of
    Ureche
  • Transaction Data Tests of the Mixture of Distributions Hypothesis of and
    Harris
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    Clark
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    Heimstra
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    Lee
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    Giot
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    Fleming
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    Jawadi
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    Li
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    Admati
  • Specification Estimation and Evaluation of Smooth Transition Autoregressive Models of the
    Teräsvirta
  • The Price Variability Volume Relationship on Speculative Markets
    Tauchen
  • Equity Trading Volume and Volatility Latent Information Arrivals and Common Long - Run Dependence of
    Bollerslev
  • The Dynamic Relation Between Stock Returns Trading Volume Volatility Financial
    Chen
  • Volume Volatility Leverage Dynamic of
    Tauchen
  • Fur International Market Correlation Volatility Financial September
    Solnik