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Surprising information, the MDH, and the relationship between volatility and trading volume

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  • Park, Beum-Jo

Abstract

This paper explains the concept of surprising information with a sign effect. Employing the mixture of distribution hypothesis (MDH), this paper also theoretically demonstrates that the effect of surprising information on the relationship between volatility and trading volume contrasts with that of general information, and proposes a method to detect the unobservable surprising information. Furthermore, incorporating surprising information with a sign effect, this paper suggests an information-type switching GARCH-V model. Strong evidence in favor of the model specification over the standard GARCH models is based on empirical application with high frequency data, supporting the dependence of the relationship between volatility and trading volume on the type of information.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Financial Markets.

Volume (Year): 13 (2010)
Issue (Month): 3 (August)
Pages: 344-366

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Handle: RePEc:eee:finmar:v:13:y:2010:i:3:p:344-366

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Web page: http://www.elsevier.com/locate/finmar

Related research

Keywords: Surprising information with a sign effect Modified MDH Information-type switching GARCH-V model Trading volume Realized volatility Quantile regression;

References

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Citations

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Cited by:
  1. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, School of Economics and Management, University of Aarhus.
  2. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
  3. Park, Beum-Jo, 2011. "Asymmetric herding as a source of asymmetric return volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2657-2665, October.
  4. Olivier Damette & Stéphane Goutte, 2014. "Tobin tax and trading volume tightening: a reassessment," Working Papers halshs-00926805, HAL.
  5. Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.

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