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Long Memory and Tail dependence in Trading Volume and Volatility

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Author Info
Eduardo Rossi () (Dipartimento di economia politica e metodi quantitativi, University of Pavia, Italy.)
Paolo Santucci de Magistris (Dipartimento di economia politica e metodi quantitativi, University of Pavia, Italy)

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Abstract

This paper investigates long-run dependencies of volatility and volume, supposing that are driven by the same informative process. Log-realized volatility and log-volume are characterized by upper and lower tail dependence, where the positive tail dependence is mainly due to the jump component. The possibility that volume and volatility are driven by a common fractionally integrated stochastic trend, as the Mixture Distribution Hypothesis prescribes, is rejected. We model the two series with a bivariate Fractionally Integrated VAR specification. The joint density is parameterized by means of with different copula functions, which provide flexibility in modeling the dependence in the extremes and are computationally convenient. Finally, we present a simulation exercise to validate the model.

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Publisher Info
Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2009-30.

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Length: 43
Date of creation: 13 Jul 2009
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Handle: RePEc:aah:create:2009-30

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Web page: http://www.econ.au.dk/afn/

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Related research
Keywords: Realized Volatility; Trading Volume; Fractional Cointegration; Tail dependence; Copula Modeling;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

This paper has been announced in the following NEP Reports:

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  4. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August. [Downloadable!] (restricted)
    Other versions:
  5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March. [Downloadable!] (restricted)
    Other versions:
  6. Robinson, Peter M. & Yajima, Yoshihiro, 2002. "Determination of cointegrating rank in fractional systems," Journal of Econometrics, Elsevier, vol. 106(2), pages 217-241, February. [Downloadable!] (restricted)
    Other versions:
  7. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  8. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37. [Downloadable!] (restricted)
    Other versions:
  9. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(01), pages 109-126, March. [Downloadable!]
  10. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March. [Downloadable!] (restricted)
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    Other versions:
  12. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 17(2), pages 581-610. [Downloadable!] (restricted)
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