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Dokumenttyp:
Zeitschriftenaufsatz 
Autor(en):
Nagler, T., Bumann, C. and Czado, C. 
Titel:
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...    »
 
Stichworte:
BIC, Model selection, Sparsity, Value-at-Risk, Vine copula 
Dewey Dezimalklassifikation:
510 Mathematik 
Zeitschriftentitel:
Journal of Multivariate Analysis 
Jahr:
2019 
Band / Volume:
172 
Jahr / Monat:
2019-07 
Quartal:
3. Quartal 
Monat:
Jul 
Seitenangaben Beitrag:
180-192 
Sprache:
en 
Verlag / Institution:
Elsevier BV 
E-ISSN:
0047-259X 
Publikationsdatum:
01.07.2019 
Semester:
SS 19 
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik 
Format:
Text