Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Stöber, Jakob"'
For nearly every major stock market there exist equity and implied volatility indices. These play important roles within finance: be it as a benchmark, a measure of general uncertainty or a way of investing or hedging. It is well known in the academi
Externí odkaz:
http://arxiv.org/abs/1604.05598
Autor:
Stöber, Jakob, Schepsmeier, Ulf
We demonstrate how the uncertainty of parameter point estimates can be assessed in a maximum likelihood framework in order to prevent overfitting and erroneous detection of time-inhomogeneity. The class of models we consider are regular vine (R-vine)
Externí odkaz:
http://arxiv.org/abs/1205.4841
So called pair copula constructions (PCCs), specifying multivariate distributions only in terms of bivariate building blocks (pair copulas), constitute a flexible class of dependence models. To keep them tractable for inference and model selection, t
Externí odkaz:
http://arxiv.org/abs/1205.4844
Autor:
Stoeber, Jakob, Czado, Claudia
Misperceptions about extreme dependencies between different financial assets have been an im- portant element of the recent financial crisis. This paper studies inhomogeneity in dependence structures using Markov switching regular vine copulas. These
Externí odkaz:
http://arxiv.org/abs/1202.2009
Publikováno v:
In Computational Statistics and Data Analysis February 2017 106:138-152
Publikováno v:
In Computational Statistics and Data Analysis August 2015 88:28-39
Autor:
Stöber, Jakob, Czado, Claudia
Publikováno v:
In Computational Statistics and Data Analysis August 2014 76:672-686
Publikováno v:
In Journal of Multivariate Analysis August 2013 119:101-118
Autor:
Schepsmeier, Ulf1 schepsmeier@ma.tum.de, Stöber, Jakob1 stoeber@ma.tum.de
Publikováno v:
Statistical Papers. May2014, Vol. 55 Issue 2, p525-542. 18p.
Autor:
Stöber, Jakob
This thesis extends the theory of pair-copula constructions (PCCs) based on regular vines (R-vines) in several aspects. We develop PCCs for models with both discrete and continuous one dimensional marginal distributions and present algorithms for an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______518::5777359d41f5458578cdae5c4b442f1a
https://mediatum.ub.tum.de/1137287
https://mediatum.ub.tum.de/1137287