Financial Time Series Analysis of SV Model by Hybrid Monte Carlo

dc.creatorTakaishi, Tetsuya
dc.date2008-07-28
dc.date.accessioned2026-07-07T12:05:56Z
dc.date.available2026-07-07T12:05:56Z
dc.descriptionWe apply the hybrid Monte Carlo (HMC) algorithm to the financial time sires analysis of the stochastic volatility (SV) model for the first time. The HMC algorithm is used for the Markov chain Monte Carlo (MCMC) update of volatility variables of the SV model in the Bayesian inference. We compute parameters of the SV model from the artificial financial data and compare the results from the HMC algorithm with those from the Metropolis algorithm. We find that the HMC decorrelates the volatility variables faster than the Metropolis algorithm. We also make an empirical analysis based on the Yen/Dollar exchange rates.
dc.description8 pages, 3 figures, to be published in LNCS
dc.identifierhttps://arxiv.org/abs/0807.4394
dc.identifierhttp://arxiv.org/abs/0807.4394
dc.identifierLecture Notes in Computer Science Volume 5226 (2008) 929-936
dc.identifierdoi:10.1007/978-3-540-87442-3_114
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/208514
dc.subjectStatistical Finance
dc.subjectData Analysis, Statistics and Probability
dc.subjectPhysics and Society
dc.titleFinancial Time Series Analysis of SV Model by Hybrid Monte Carlo
dc.typetext

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