EconPapers    
Economics at your fingertips  
 

Computationally efficient inference procedures for vast dimensional realized covariance models

Luc Bauwens () and Giuseppe Storti ()

No 2012028, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: This paper illustrates some computationally efficient estimation procedures for the estimation of vast dimensional realized covariance models. In particular, we derive a Composite Maximum Likelihood (CML) estimator for the parameters of a Conditionally Autoregressive Wishart (CAW) model incorporating scalar system matrices and covariance targeting. The finite sample statistical properties of this estimator are investigated by means of a Monte Carlo simulation study in which the data generating process is assumed to be given by a scalar CAW model. The performance of the CML estimator is satisfactory in all the settings considered although a relevant finding of our study is that the efficiency of the CML estimator is critically dependent on the implementation settings chosen by modeller and, more specifically, on the dimension of the marginal log-likelihoods used to build the composite likelihood functions.

Keywords: realized covariance; CAW model; BEKK model; composite likelihood; covariance targeting; Wishart distribution (search for similar items in EconPapers)
JEL-codes: C32 C58 (search for similar items in EconPapers)
Date: 2012-07-25
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
http://uclouvain.be/cps/ucl/doc/core/documents/coredp2012_28web.pdf (application/pdf)

Related works:
Working Paper: Computationally efficient inference procedures for vast dimensional realized covariance models (2013) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2012028

Access Statistics for this paper

More papers in CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Alain GILLIS ().

 
Page updated 2019-09-12
Handle: RePEc:cor:louvco:2012028