Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series
SFB 649 Discussion Paper No. 2012-054
16 Pages Posted: 25 Aug 2013
Date Written: 2012
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: Suggested Citation