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2012 | OriginalPaper | Chapter

7. Vector Multiplicative Error Models

Author : Professor Dr. Nikolaus Hautsch

Published in: Econometrics of Financial High-Frequency Data

Publisher: Springer Berlin Heidelberg

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Abstract

This chapter focusses on multivariate extensions of multiplicative error models. The basic multivariate (or vector) multiplicative error model is introduced in Sect. 7.1.1. We discuss specification, statistical inference and provide empirical illustrations. Section 7.2 is devoted to stochastic vector MEMs corresponding to multivariate versions of univariate stochastic MEMs as presented in Chap. 5. Here, the idea is to augment a VMEM process by a common latent component which jointly affects all individual processes. We illustrate how to estimate this class of models using simulated maximum likelihood and illustrate applications to the modelling of trading processes.

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previous chapter Generalized Multiplicative Error Models

next chapter Modelling High-Frequency Volatility

Recall the discussion of Log-ACD models in Chap. 5.

For a more sophisticated approach to model positive-valued (continuous) random variables which reveal a non-trivial part of zero outcomes, see Hautsch et al. (2010).

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Title: Vector Multiplicative Error Models
Author: Professor Dr. Nikolaus Hautsch
Publisher: Springer Berlin Heidelberg
Book: Econometrics of Financial High-Frequency Data
Print ISBN: 978-3-642-21924-5

Electronic ISBN: 978-3-642-21925-2

Copyright Year: 2012
DOI: https://doi.org/10.1007/978-3-642-21925-2_7