Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Lindner, Alexander M."'
Publikováno v:
Scandinavian Journal of Statistics, 2007 Jun 01. 34(2), 298-316.
Externí odkaz:
https://www.jstor.org/stable/41548553
Publikováno v:
In Linear Algebra and Its Applications 2002 355(1):147-159
Autor:
Christensen, Ole *, Lindner, Alexander M.
Publikováno v:
In Linear Algebra and Its Applications 2001 323(1):117-130
Herausragende Leistungen mit wertstromorientierten Prozessmanagement erreichen!- Prozesse optimieren und Kosten senken- Praxiserprobte Vorgehensweise- Viele Beispiele und konkrete TippsProzessmanagement und Wertstromdesign bieten viele Berührungspun
We characterize convergence of a sequence of d-dimensional random vectors by convergence of the one-dimensional margins and of the copula. The result is applied to the approximation of portofolio modelled by t-copulas with large degrees of freedom, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a09e2ebdc42cd1804e0b46dfd57f371
We use a discrete time analysis, giving necessary and sufficient conditions for the almost sure convergence of ARCH(1) and GARCH(1,1) discrete time models, tosuggest an extension of the (G)ARCH concept to continuous time processes. Our "COGARCH" (con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c3b7a29df1f217bd600f565ee7663c7
https://hdl.handle.net/10419/31047
https://hdl.handle.net/10419/31047
We compare the probabilistic properties of the non-Gaussian Ornstein-Uhlenbeck based stochastic volatility model of Barndorff-Nielsen and Shephard (2001) with those of the COGARCH process. The latter is a continuous time GARCH process introduced by t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c08094de265be437f6513434f5dc4295
https://hdl.handle.net/10419/31106
https://hdl.handle.net/10419/31106
A continuous time GARCH model of order (p,q) is introduced, which is driven by a single Lévy process. It extends many of the features of discrete time GARCH(p,q) processes to a continuous time setting. When p=q=1, the process thus defined reduces to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a17d8b064031453d25ebd48be3ec5153
https://hdl.handle.net/10419/31103
https://hdl.handle.net/10419/31103
Empirical volatility changes in time and exhibits tails, which are heavier than normal. Moreover, empirical volatility has - sometimes quite substantial - upwards jumps and clusters on high levels. We investigate classical and non-classical stochasti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5b5b1bfe9427292267c55204d306d2a