Gibbs sampler to stochastic volatility models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F01%3A00064622" target="_blank" >RIV/49777513:23520/01:00064622 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Gibbs sampler to stochastic volatility models
Original language description
A new technique for nonlinear state and parameter estimation of the discrete time stochastic volatility models in which the logarithm of the asset return conditional variance follows an autoregressive model is developed. The Gibbs sampling algorithm is used to construct a Markov-chain simulation tool that reflects both inherent model variability and parameter uncertainty. The proposed chain converges to an equilibrium making it possible to summarize the distributions of the unobserved volatilities and the unknown model parameters. The non-Gaussian density of the log of squared inovations is advantageously modelled as a mixture of Gaussians.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BC - Theory and management systems
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F01%2F0021" target="_blank" >GA102/01/0021: Nonlinear estimation and change detection for stochastic systems</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Gibbs sampler to stochastic volatility models
ISBN
9727520472
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
EUCA
Place of publication
Porto
Event location
Porto
Event date
Jan 1, 2001
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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