About: Optimal stochastic volatility models

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	A new technique for nonlinear state and parameter estimation of the discrete time stochastic volatility models in the state space form is developed. The Gibbs sampler is used to construct a Markov-chain simulation tool that reflects both inherent model variability and parameter uncertainty. The Gibbs sampling algorithm is derived from the generalized data-augmentation method and the iterative Monte Carlo simulation procedures to calculating marginal state and parameters probability density functions. The design algorithm is based on a loop where samples from the correspondent data augmented probability density function are drawn. The proposed chain converges to equilibrium enabling to summarize the unobserved variance states and unknown model parameters distributions. The non-Gaussian density of the log of squared inovations is advantageously modelled as a mixture of Gaussians. A new technique for nonlinear state and parameter estimation of the discrete time stochastic volatility models in the state space form is developed. The Gibbs sampler is used to construct a Markov-chain simulation tool that reflects both inherent model variability and parameter uncertainty. The Gibbs sampling algorithm is derived from the generalized data-augmentation method and the iterative Monte Carlo simulation procedures to calculating marginal state and parameters probability density functions. The design algorithm is based on a loop where samples from the correspondent data augmented probability density function are drawn. The proposed chain converges to equilibrium enabling to summarize the unobserved variance states and unknown model parameters distributions. The non-Gaussian density of the log of squared inovations is advantageously modelled as a mixture of Gaussians. (en)
Title	Optimal stochastic volatility models Optimal stochastic volatility models (en)
skos:prefLabel	Optimal stochastic volatility models Optimal stochastic volatility models (en)
skos:notation	RIV/49777513:23520/01:00064868!RIV/2002/GA0/235202/N
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(GA102/01/0021), Z(MSM 235200004)
http://linked.open...vai/riv/dodaniDat	2002
http://linked.open...aciTvurceVysledku	Soukup, Tomáš Šimandl, Miroslav
http://linked.open.../riv/druhVysledku	V - Výzkumná zpráva
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Západočeská univerzita v Plzni / Fakulta aplikovaných věd
http://linked.open...dnocenehoVysledku	690228
http://linked.open...ai/riv/idVysledku	RIV/49777513:23520/01:00064868
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	stochastic volatility models; nonlinear estimation; Monte Carlo methods (en)
http://linked.open.../riv/klicoveSlovo	Monte Carlo methods nonlinear estimation stochastic volatility models
http://linked.open...ontrolniKodProRIV	[14793235D0C7]
http://linked.open...i/riv/mistoVydani	Plzeň
http://linked.open...telVyzkumneZpravy	Západočeská univerzita
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...ocetUcastnikuAkce	0 (xsd:int)
http://linked.open...nichUcastnikuAkce	0 (xsd:int)
http://linked.open...vavai/riv/projekt	Nonlinear estimation and change detection for stochastic systems
http://linked.open...UplatneniVysledku	2001
http://linked.open...iv/tvurceVysledku	Soukup, Tomáš Šimandl, Miroslav
http://linked.open...rzeVyzkumneZpravy	Neuveden
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20235200004
number of pages	1 (xsd:int)
http://localhost/t...ganizacniJednotka	23520

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