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An Inflated Multivariate Integer Count Hurdle Model: An Application to Bid and Ask Quote Dynamics

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  • Katarzyna Bien

    ()
    (University of Konstanz)

  • Ingmar Nolte

    ()
    (University of Konstanz)

  • Winfried Pohlmeier

    ()
    (University of Konstanz)

Abstract

In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain Zn. Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete domain, (ii) the tendency to cluster at certain outcome values and (iii) contemporaneous dependence. These kind of properties can be found for high or ultra-high frequent data describing the trading process on financial markets. We present a straightforward method of sampling from such an inflated multivariate density through the application of an Independence Metropolis-Hastings sampling algorithm. We demonstrate the power of our approach by modelling the conditional bivari- ate density of bid and ask quote changes in a high frequency setup. We show how to derive the implied conditional discrete density of the bid-ask spread, taking quote clusterings (at multiples of 5 ticks) into account.

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Bibliographic Info

Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 07-04.

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Length: 26 pages
Date of creation: 28 Mar 2007
Date of revision:
Handle: RePEc:knz:cofedp:0704

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Related research

Keywords: Multivariate Discrete Distributions; Conditional Inflation; Copula Functions; Truncations; Metropolized-Independence Sampler;

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References

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Citations

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Cited by:
  1. Deb P & Trivedi PK & Zimmer DM, 2009. "Dynamic Cost-offsets of Prescription Drug Expenditures: Panel Data Analysis Using a Copula-based Hurdle Model," Health, Econometrics and Data Group (HEDG) Working Papers 09/15, HEDG, c/o Department of Economics, University of York.
  2. Katarzyna BieĊ„-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(2), pages 117-142, June.

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