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pro vyhledávání: '"GRUBLYTĖ, IEVA"'
Autor:
Grublyte, Ieva
Le but principal de cette thèse est de développer de nouveaux modèles non linéaires à longue mémoire pour modéliser des rendements financiers et leur estimation statistique. En plus de la longue mémoire, ces modèles sont capables de mettre
Externí odkaz:
http://www.theses.fr/2017CERG0923
We discuss parametric quasi-maximum likelihood estimation for quadratic ARCH process with long memory introduced in Doukhan et al. (2015) and Grublyt\.e and \v{S}karnulis (2015) with conditional variance given by a strictly positive quadratic form of
Externí odkaz:
http://arxiv.org/abs/1509.06422
Autor:
Grublytė, Ieva, Škarnulis, Andrius
We study the existence and properties of stationary solution of ARCH-type equation $r_t= \zeta_t \sigma_t$, where $\zeta_t$ are standardized i.i.d. r.v.'s and the conditional variance satisfies an AR(1) equation $\sigma^2_t = Q^2\big(a + \sum_{j=1}^\
Externí odkaz:
http://arxiv.org/abs/1509.01708
We discuss a class of conditionally heteroscedastic time series models satisfying the equation $r_t= \zeta_t \sigma_t$, where $\zeta_t$ are standardized i.i.d. r.v.'s and the conditional standard deviation $\sigma_t$ is a nonlinear function $Q$ of in
Externí odkaz:
http://arxiv.org/abs/1502.00095
Autor:
Grublytė, Ieva, Surgailis, Donatas
A projective moving average $\{X_t, t \in \mathbb{Z}\}$ is a Bernoulli shift written as a backward martingale transform of the innovation sequence. We introduce a new class of nonlinear stochastic equations for projective moving averages, termed proj
Externí odkaz:
http://arxiv.org/abs/1312.1938
Autor:
Doukhan, Paul1 (AUTHOR), Grublytė, Ieva2 (AUTHOR), Pommeret, Denys3 (AUTHOR) denys.pommeret@univ-amu.fr, Reboul, Laurence4 (AUTHOR)
Publikováno v:
Annals of the Institute of Statistical Mathematics. Dec2020, Vol. 72 Issue 6, p1419-1447. 29p.
Autor:
GRUBLYTĖ, IEVA, SURGAILIS, DONATAS
Publikováno v:
Advances in Applied Probability, 2014 Dec 01. 46(4), 1084-1105.
Externí odkaz:
https://www.jstor.org/stable/43563449
Publikováno v:
Journal of Time Series Analysis. Jul2017, Vol. 38 Issue 4, p535-551. 17p.
Autor:
Grublytė, Ieva1,2 (AUTHOR) ieva.grublyte@mii.vu.lt, Škarnulis, Andrius2 (AUTHOR)
Publikováno v:
Statistics. Feb2017, Vol. 51 Issue 1, p123-140. 18p.
Autor:
Grublytė, Ieva
The thesis introduces new nonlinear models with long memory which can be used for modelling of financial returns and statistical inference. Apart from long memory, these models are capable to exhibit other stylized facts such as asymmetry and levera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5ff924b2601f8d32ad4f81bb301c107e
https://repository.vu.lt/VU:ELABAETD24527757&prefLang=en_US
https://repository.vu.lt/VU:ELABAETD24527757&prefLang=en_US