A goodnessoffit test for regular vine copula models
Abstract
We introduce a new goodnessoffit test for regular vine (Rvine) copula models. Rvine copulas are a very flexible class of multivariate copulas based on a paircopula construction (PCC). The test arises from the information matrix equality and specification test proposed by White (1982) and extends the goodnessoffit test for copulas introduced by Huang and Prokhorov (2011). The corresponding critical value can be approximated by asymptotic theory or simulation. The simulation based test shows excellent performance with regard to observed size and power in an extensive simulation study, while the asymptotic theory based test is inaccurate for n<10000 for a 5dimensional model (in d=8 even 20000 are not enough). The simulation based test is applied to select among different Rvine specifications to model the dependency among exchange rates.
 Publication:

arXiv eprints
 Pub Date:
 June 2013
 arXiv:
 arXiv:1306.0818
 Bibcode:
 2013arXiv1306.0818S
 Keywords:

 Statistics  Computation;
 Mathematics  Statistics Theory