Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series

SFB 649 Discussion Paper No. 2012-054

16 Pages Posted: 25 Aug 2013

See all articles by Nikolaus Hautsch

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics

Alexander Ristig

University of Vienna - Department of Statistics and Operations Research

Date Written: 2012

Abstract

Multiplicative error models (MEM) became a standard tool for modeling conditional durations of intra-day transactions, realized volatilities and trading volumes. The parametric estimation of the corresponding multivariate model, the so-called vector MEM (VMEM), requires a specification of the joint error term distribution, which is due to the lack of multivariate distribution functions on Rd defined via a copula. Maximum likelihood estimation is based on the assumption of constant copula parameters and therefore, leads to invalid inference, if the dependence exhibits time variations or structural breaks. Hence, we suggest to test for time-varying dependence by calibrating a time-varying copula model and to re-estimate the VMEM based on identified intervals of homogenous dependence. This paper summarizes the important aspects of (V)MEM, its estimation and a sequential test for changes in the dependence structure. The techniques are applied in an empirical example.

Keywords: vector multiplicative error model, copula, time-varying copula, high-frequency data

JEL Classification: C32, C51

Suggested Citation

Hautsch, Nikolaus and Okhrin, Ostap and Ristig, Alexander, Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series (2012). SFB 649 Discussion Paper No. 2012-054, Available at SSRN: https://ssrn.com/abstract=2315828 or http://dx.doi.org/10.2139/ssrn.2315828

Nikolaus Hautsch (Contact Author)

University of Vienna - Department of Statistics and Operations Research ( email )

Kolingasse 14
Vienna, A-1090
Austria

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Alexander Ristig

University of Vienna - Department of Statistics and Operations Research ( email )

Oskar-Morgenstern-Platz 1
Vienna, 1090
Austria

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