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Document type:
Zeitschriftenaufsatz 
Author(s):
Nagler, T., Bumann, C. and Czado, C. 
Title:
Model selection in sparse high-dimensional vine copula models with an application to portfolio risk 
Abstract:
Vine copulas allow the construction of flexible dependence models for an arbitrary number of variables using only bivariate building blocks. The number of parameters in a vine copula model increases quadratically with the dimension, which poses challenges in high-dimensional applications. To alleviate the computational burden and risk of overfitting, we propose a modified Bayesian information criterion (BIC) tailored to sparse vine copula models. We argue that this criterion can consistently dis...    »
 
Keywords:
BIC, Model selection, Sparsity, Value-at-Risk, Vine copula 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Journal of Multivariate Analysis 
Year:
2019 
Journal volume:
172 
Year / month:
2019-07 
Quarter:
3. Quartal 
Month:
Jul 
Pages contribution:
180-192 
Language:
en 
Publisher:
Elsevier BV 
E-ISSN:
0047-259X 
Date of publication:
01.07.2019 
Semester:
SS 19 
TUM Institution:
Professur für Angewandte Mathematische Statistik 
Format:
Text