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Description
  • A new technique for nonlinear state and parameter estimation of the discrete time stochastic volatility models is developed. Algorithm of Gibbs sampler and simulation filters are used to construct a simulation tool that reflects both inherent model variability and parameter uncertainty. The proposed chain converges to equilibrium enabling to estimate the unobserved volatilities and unknown model parameters distributions. The estimation algorithm is demonstrated in a numerical example.
  • A new technique for nonlinear state and parameter estimation of the discrete time stochastic volatility models is developed. Algorithm of Gibbs sampler and simulation filters are used to construct a simulation tool that reflects both inherent model variability and parameter uncertainty. The proposed chain converges to equilibrium enabling to estimate the unobserved volatilities and unknown model parameters distributions. The estimation algorithm is demonstrated in a numerical example. (en)
  • Je vyvinuta nová metoda odhadu stavu a parametrů pro diskrétní stochasticky nestálé modely. Je využito algoritmů Gibbsova vzorkovače a simulačních filtrů ke konstrukci simulačního nástroje, který zohledňuje jak variabilitu modelu, tak i neurčitost parametrů. Navrhovaná řada konverguje k rovnovážnému stavu, což umožňuje odhad nepozorovaných nestálostí a rozdělení pararametrů neznámého modelu. Algoritmus odhadu je demostrován na příkladu. (cs)
Title
  • Simulační metody Monte Carlo pro rozšířené strocahsticky nestálé modely (cs)
  • Simulation Monte Carlo methods in extended stochastic volatility models
  • Simulation Monte Carlo methods in extended stochastic volatility models (en)
skos:prefLabel
  • Simulační metody Monte Carlo pro rozšířené strocahsticky nestálé modely (cs)
  • Simulation Monte Carlo methods in extended stochastic volatility models
  • Simulation Monte Carlo methods in extended stochastic volatility models (en)
skos:notation
  • RIV/49777513:23520/02:00000066!RIV07-GA0-23520___
http://linked.open.../vavai/riv/strany
  • 109
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  • P(GA102/01/0021)
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  • 0
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  • 663605
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  • RIV/49777513:23520/02:00000066
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  • Stochastic volatility model; Nonlinear estimation; Monte Carlo methods (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [ED9E18860690]
http://linked.open...i/riv/nazevZdroje
  • International Journal of Intelligent Systems in Accounting, Finance & Management
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http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Soukup, Tomáš
  • Šimandl, Miroslav
issn
  • 1055-615X
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  • 23520
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