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Financial Time Series Analysis of SV Model by Hybrid Monte Carlo

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  • Tetsuya Takaishi

Abstract

We 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.

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  • Tetsuya Takaishi, 2008. "Financial Time Series Analysis of SV Model by Hybrid Monte Carlo," Papers 0807.4394, arXiv.org.
    • Handle: RePEc:arx:papers:0807.4394
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    References listed on IDEAS

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    Cited by:

    1. Tetsuya Takaishi, 2013. "Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm," Papers 1305.3184, arXiv.org.

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