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

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

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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 Dynamics

@techreport{Bien2007Infla-12020, series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie}, title={An Inflated Multivariate Integer Count Hurdle Model : an Application to Bid and Ask Quote Dynamics}, year={2007}, number={2007/04}, author={Bien, Katarzyna and Nolte, Ingmar and Pohlmeier, Winfried} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/12020"> <dc:contributor>Pohlmeier, Winfried</dc:contributor> <dcterms:title>An Inflated Multivariate Integer Count Hurdle Model : an Application to Bid and Ask Quote Dynamics</dcterms:title> <dc:contributor>Nolte, Ingmar</dc:contributor> <dcterms:issued>2007</dcterms:issued> <dc:rights>deposit-license</dc:rights> <dc:creator>Bien, Katarzyna</dc:creator> <dc:creator>Pohlmeier, Winfried</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:42:11Z</dcterms:available> <dc:format>application/pdf</dc:format> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:42:11Z</dc:date> <dcterms:rights rdf:resource="https://creativecommons.org/licenses/by-nc-nd/2.0/legalcode"/> <dc:contributor>Bien, Katarzyna</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/12020"/> <dc:creator>Nolte, Ingmar</dc:creator> <dcterms:abstract xml:lang="eng">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.</dcterms:abstract> <dc:language>eng</dc:language> </rdf:Description> </rdf:RDF>

Dateiabrufe seit 01.10.2014 (Informationen über die Zugriffsstatistik)

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