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Financial Time Series Analysis of SV Model by Hybrid Monte Carlo
Financial Time Series Analysis of SV Model by
Hybrid Monte Carlo
8 Tetsuya Takaishi
0
0 Hiroshima University of Economics,
2 Hiroshima 731-0192 JAPAN
l E-mail: takaishi@hiroshima-u.ac.jp
u
J
8 Abstract. We apply the hybrid Monte Carlo (HMC) algorithm to the
2
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
h (MCMC) update of volatility variables of the SV model in the Bayesian
p inference. We compute parameters of the SV model from the artificial
c- financial data and compare the results from the HMC algorithm with
o those from the Metropolis algorithm. We find that the HMC decorrelates
s the volatility variables faster than the Metropolis algorithm. We also
s. make an empirical analysis based on the Yen/Dollar exchange rates.
c
i Key words: Hybrid Monte Carlo Algorithm, Stochastic Volatility Model,
s
y Markov Chain Monte Carlo, Bayesian Inference, Financial Data Analysis
h
p
[ 1 Introduction
1
v It is well known that financial time series of asset returns shows various inter-
4 esting properties which can not be explained from the assumption of that the
9 time series o
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