Enforcing an admissible parameter space for vector MEM: the fundamental role of matrix inequality constraints

Karanasos, Menelaos, Xu, Yongdeng ORCID: https://orcid.org/0000-0001-8275-1585, Yfanti, S. and Zopounidis, C. 2026. Enforcing an admissible parameter space for vector MEM: the fundamental role of matrix inequality constraints. Journal of Financial Econometrics 24 (3) , nbag008. 10.1093/jjfinec/nbag008

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Abstract

We derive an admissible parameter space for vector multiplicative error models (vMEMs), explicitly formulating it in terms of the model’s matrix parameters through a set of matrix inequalities. Another key contribution is the adoption of constrained maximum likelihood estimation for the multivariate process, which ensures compliance with these matrix inequalities and addresses the limitations of unconstrained approaches used in previous studies. To demonstrate the effectiveness of the proposed method, we apply it to four empirical cases in financial volatility modeling, emphasizing its practical relevance.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Schools > Business (Including Economics)
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HG Finance
Publisher:	Oxford University Press
ISSN:	1479-8409
Date of First Compliant Deposit:	31 March 2026
Date of Acceptance:	12 March 2026
Last Modified:	02 Jul 2026 15:58
URI:	https://orca.cardiff.ac.uk/id/eprint/186100

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