Enforcing an Admissible Parameter Space for Vector Multiplicative Error Models: The Fundamental Role of Matrix Inequality Constraints.
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...
| Publicado en: | Journal of Financial Econometrics Vol. 24; no. 3; pp. 1 - 29 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Oxford University Press / USA
2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=194637002&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 194637002 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 14798409 T2Y jtl: Journal of Financial Econometrics issn: 14798409 maglogo: N pubinfo: dt: 2026 vid: 24 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 194637002 10.1093/jjfinec/nbag008 ppf: 1 ppct: 28 formats: tig: atl: Enforcing an Admissible Parameter Space for Vector Multiplicative Error Models: The Fundamental Role of Matrix Inequality Constraints. aug: au: Karanasos, Menelaos Xu, Yongdeng Yfanti, Stavroula Zopounidis, Constantin affil: Economics and Finance, Brunel University of London, Uxbridge, UK Cardiff Business School, Cardiff University, Cardiff, UK School of Business and Management, Queen Mary University of London, London, UK School of Production, Engineering and Management, Technical University of Crete, Chania, Greece su: Matrix inequalities Maximum likelihood statistics Statistical models sug: subj: Matrix inequalities Maximum likelihood statistics Statistical models keyword: admissible parameter space C32 C53 C58 constrained maximum likelihood estimation copyrightHolder:Oxford University Press copyrightYear:2026 G15 inLanguage:en matrix inequalities MEM multivariate volatility modeling publisher:Oxford University Press sameAs:https://dx.doi.org/10.1093/jjfinec/nbag008 second moment structure admissible parameter space C32 C53 C58 constrained maximum likelihood estimation copyrightHolder:Oxford University Press copyrightYear:2026 G15 inLanguage:en matrix inequalities MEM multivariate volatility modeling publisher:Oxford University Press sameAs:https://dx.doi.org/10.1093/jjfinec/nbag008 second moment structure ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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