Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics
AU - Bien, Katarzyna
AU - Nolte, Ingmar
AU - Pohlmeier, Winfried
PY - 2011/6
Y1 - 2011/6
N2 - In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain ℤn, n ∈ ℕ. 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 kinds of properties can be found for high- or ultra-high-frequency data describing the trading process on financial markets. We present a straightforward sampling method for 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. Copyright © 2009 John Wiley & Sons, Ltd.
AB - In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain ℤn, n ∈ ℕ. 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 kinds of properties can be found for high- or ultra-high-frequency data describing the trading process on financial markets. We present a straightforward sampling method for 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. Copyright © 2009 John Wiley & Sons, Ltd.
U2 - 10.1002/jae.1122
DO - 10.1002/jae.1122
M3 - Journal article
VL - 26
SP - 669
EP - 707
JO - Journal of Applied Econometrics
JF - Journal of Applied Econometrics
SN - 0883-7252
IS - 4
ER -