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2012 | OriginalPaper | Chapter

6. Generalized 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

In this chapter, we present generalizations of the basic multiplicative error model as introduced in Chap. 5. Section 6.1 discusses a class of ACD models which can be presented in terms of a generalized polynomial random coefficient model according to Carrasco and Chen (2002). We illustrate various special cases, discuss the theoretical properties and show empirical illustrations. In Sect. 6.2, we consider regime-switching ACD models allowing for parameters which might change in dependence of observable or unobservable characteristics. We concentrate on threshold ACD models, smooth transition ACD models as well as Markov Switching ACD specifications. Section 6.3 focuses on ACD models accommodating long range dependence in the data. In this context, we discuss different possibilities to capture long memory.

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previous chapter Univariate Multiplicative Error Models

next chapter Vector Multiplicative Error Models

They use this notation to prevent confusion with the Exponential ACD model (EACD) based on an exponential distribution.

See also Carrasco and Chen (2005) and Meitz and Saikkonen (2008) for a correction of some of the results provided by Carrasco and Chen (2002). These corrections, however, do not affect the proposition presented above.

Note that in a nonlinear ACD specification, an upward kinked concave news impact function actually implies a negative value for α; see also Sect. 6.1.1.4.

For more details concerning threshold autoregressive (TAR) models, see, for example, Tong (1990).

For an overview, see Beran (1994) or Baillie (1996).

See also Meddahi et al. (1998) who introduce a similar specification.

Alternatively, Strickland et al. (2006) propose estimating the SCD model based on Monte Carlo Markov Chain (MCMC) techniques. Bauwens and Galli (2009) employ efficient importance sampling techniques as discussed in Sect. 7.2.

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Title: Generalized 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_6