Publikation: An Inflated Multivariate Integer Count Hurdle Model : an Application to Bid and Ask Quote Dynamics
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2007
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Zusammenfassung
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 bivariate 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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330 Wirtschaft
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Multivariate Discrete Distributions, Conditional Inflation, Copula Functions, Truncations, Metropolized-Independence Sampler
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BIEN, Katarzyna, Ingmar NOLTE, Winfried POHLMEIER, 2007. An Inflated Multivariate Integer Count Hurdle Model : an Application to Bid and Ask Quote DynamicsBibTex
@techreport{Bien2007Infla-12020,
year={2007},
series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
title={An Inflated Multivariate Integer Count Hurdle Model : an Application to Bid and Ask Quote Dynamics},
number={2007/04},
author={Bien, Katarzyna and Nolte, Ingmar and Pohlmeier, Winfried}
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