Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257954 
Year of Publication: 
2019
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 7 [Issue:] 4 [Article No.:] 116 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-14
Publisher: 
MDPI, Basel
Abstract: 
This article is concerned with the study of the tail correlation among equity indices by means of dynamic copula functions. The main idea is to consider the impact of the use of copula functions in the accuracy of the model's parameters and in the computation of Value-at-Risk (VaR). Results show that copulas provide more sophisticated results in terms of the accuracy of the forecasted VaR, in particular, if they are compared with the results obtained from Dynamic Conditional Correlation (DCC) model.
Subjects: 
copula functions
Monte Carlo simulation techniques
risk measures
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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