Estimating Liquidity Using Information on the Multivariate Trading Process

73 Pages Posted: 17 Jul 2006

See all articles by Katarzyna Bien

Katarzyna Bien

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE)

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Winfried Pohlmeier

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE)

Date Written: March 31, 2006

Abstract

In this paper we model the dynamic multivariate density of discrete bid and ask quote changes and their associated depths. We account for the contemporaneous relationship between these trading marks by exploiting the concept of copula functions. Thereby we show how to model truncations of the multivariate density in an easy way. A Metropolized-Independence Sampler is applied to draw from the dynamic multivariate density. The samples drawn serve to construct the dynamic density function of the quote slope liquidity measure, which enables us to quantify time varying liquidity risk. We analyze the influence of the decimalization at the NYSE on liquidity.

Keywords: Liquidity, Copula Functions, Trading Process, Decimalization, Metropolized-Independence Sampler

JEL Classification: G10, F30, C30

Suggested Citation

Bien, Katarzyna and Nolte, Ingmar and Pohlmeier, Winfried, Estimating Liquidity Using Information on the Multivariate Trading Process (March 31, 2006). Available at SSRN: https://ssrn.com/abstract=915348 or http://dx.doi.org/10.2139/ssrn.915348

Katarzyna Bien

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE) ( email )

Universitätsstr. 10
Box: D 124
78457 Konstanz
Germany

Ingmar Nolte (Contact Author)

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Winfried Pohlmeier

University of Konstanz - Department of Economics & Center of Finance & Econometrics (CoFE) ( email )

Konstanz, D-78457
Germany

HOME PAGE: http://econometrics.wiwi.uni-konstanz.de

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