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Citation

Šimandl, M. and Soukup, T. : Simulation Monte Carlo methods in extended stochastic volatility models . International Journal of Intelligent Systems in Accounting, Finance & Management, 11, vol. 2, p. 109-117, 2002.

Abstract

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.

Detail of publication

Title: Simulation Monte Carlo methods in extended stochastic volatility models
Author: Šimandl, M. ; Soukup, T.
Language: English
Date of publication: 1 Jan 2002
Year: 2002
Type of publication: Papers in journals
Title of journal or book: International Journal of Intelligent Systems in Accounting, Finance & Management
Series: 11
Číslo vydání: 2
Page: 109 - 117
ISBN: 1055-615X
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Keywords

Stochastic volatility model, Nonlinear estimation, Monte Carlo methods

BibTeX

@ARTICLE{SimandlM_2002_SimulationMonte,
 author = {\v{S}imandl, M. and Soukup, T.},
 title = {Simulation Monte Carlo methods in extended stochastic volatility models},
 year = {2002},
 journal = {International Journal of Intelligent Systems in Accounting, Finance & Management},
 volume = {2},
 pages = {109-117},
 series = {11},
 ISBN = {1055-615X},
 url = {http://www.kky.zcu.cz/en/publications/SimandlM_2002_SimulationMonte},
}