Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/206822 
Authors: 
Year of Publication: 
2019
Citation: 
[Journal:] International Journal for Re-Views in Empirical Economics (IREE) [ISSN:] 2566-8269 [Volume:] 3 [Issue:] 2019-6 [Publisher:] ZBW – Leibniz Information Centre for Economics [Place:] Kiel, Hamburg [Year:] 2019 [Pages:] 1-20
Publisher: 
ZBW – Leibniz Information Centre for Economics, Kiel, Hamburg
Abstract: 
This paper aims to replicate the semiparametric Value-At-Risk model by Dias (2014) and to test its legitimacy. The study confirms the superiority of semiparametric estimation over classical methods such as mixture normal and Student-t approximations in estimating tail distribution of portfolios, which can be credited to the model's uniqueness in combining strengths of both extreme value theory (EVT) models and other multivariate models. The author however discovers, in one instance, the infeasibility of the Dias model, and suggests a modification.
Subjects: 
Multi-asset portfolios
Risk management
Tail probability
Tail risk
Multivariate extremevalue theory
Value-at-Risk
Replication study
JEL: 
C51
G01
G11
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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