Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method

Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method

© 2016 by the Mathematical Association of Thailand. All rights reserved. A Bayesian method is proposed for the parameter identification of a stock market dynamics which is modeled by a Stochastic Differential Equation (SDE) driven by fractional Brownian motion (fBm). The formulation for the identifi...

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Main Authors: Harnpornchai N., Autchariyapanitkul K.
Format: Journal
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008312164&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42446
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-424462017-09-28T04:27:06Z Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method Harnpornchai N. Autchariyapanitkul K. © 2016 by the Mathematical Association of Thailand. All rights reserved. A Bayesian method is proposed for the parameter identification of a stock market dynamics which is modeled by a Stochastic Differential Equation (SDE) driven by fractional Brownian motion (fBm). The formulation for the identification is based on the Wick-product solution of the SDE driven by an fBm. The determination of the solution is carried out using an independence Metropolis Hastings algorithm. The historical record of SET index is employed for the purpose of method demonstration. For the SET index example, the estimate of the Hurst exponent is approximately 0.5. Consequently, the market is considered efficient. 2017-09-28T04:27:06Z 2017-09-28T04:27:06Z 2016-01-01 Journal 16860209 2-s2.0-85008312164 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008312164&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42446
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © 2016 by the Mathematical Association of Thailand. All rights reserved. A Bayesian method is proposed for the parameter identification of a stock market dynamics which is modeled by a Stochastic Differential Equation (SDE) driven by fractional Brownian motion (fBm). The formulation for the identification is based on the Wick-product solution of the SDE driven by an fBm. The determination of the solution is carried out using an independence Metropolis Hastings algorithm. The historical record of SET index is employed for the purpose of method demonstration. For the SET index example, the estimate of the Hurst exponent is approximately 0.5. Consequently, the market is considered efficient.
format Journal
author Harnpornchai N.
Autchariyapanitkul K.
spellingShingle Harnpornchai N.
Autchariyapanitkul K.
Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
author_facet Harnpornchai N.
Autchariyapanitkul K.
author_sort Harnpornchai N.
title Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
title_short Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
title_full Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
title_fullStr Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
title_full_unstemmed Modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: A Bayesian method
title_sort modeling stock market dynamics with stochastic differential equation driven by fractional brownian motion: a bayesian method
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008312164&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42446
_version_ 1681422190823604224

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