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A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach

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  • Katarzyna Bień-Barkowska

    ()
    (Warsaw School of Economics)

Abstract

In this paper we present a copula-based model for a binary and a continuous variable in a time series setup. Within this modeling framework both marginals can be equipped with their own dynamics whereas the contemporaneous dependence between both processes can be flexibly captured via a copula function. We propose a method for testing the goodness-offit of such a time series model using probability integral transforms (PIT). This verification procedure allows not only a verification of the goodness-offit of the estimated marginal distribution for a continuous variable but also the conditional distribution of a continuous variable given the outcome of its binary counterpart (i.e. the adequacy of the copula choice). We test the model on an empirical example: investigating the relationship between trading volume and the indicators of arbitrarily ’large’ price movements on the interbank EUR/PLN spot market.

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Bibliographic Info

Article provided by CEJEME in its journal Central European Journal of Economic Modelling and Econometrics.

Volume (Year): 4 (2012)
Issue (Month): 2 (June)
Pages: 117-142

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Handle: RePEc:psc:journl:v:4:y:2012:i:2:p:117-142

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Related research

Keywords: copula function; mixed binary-continuous distribution; ACD models; market microstructure;

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