dc.contributor.advisor Nualart, David dc.contributor.author Wu, Fengmei dc.date.accessioned 2013-09-29T15:18:53Z dc.date.available 2013-09-29T15:18:53Z dc.date.issued 2013-08-31 dc.date.submitted 2013 dc.identifier.other http://dissertations.umi.com/ku:13016 dc.identifier.uri http://hdl.handle.net/1808/12221 dc.description.abstract This paper studies continuous-time stock pricing models with stochastic volatility driven by fractional Brownian motion. We compare two ways for simulating the paths of stochastic volatility and stock price when the Hurst parameter of fractional Brown motion is between 0.5 and 1. The first approach, is to use truncated fractional Brownian motion to approximate the fractional Brownian motion and estimate the volatility by Monte Carlo integral and symbolic integral. In the second one, Euler method is employed in simulation, without truncating the fractional Brownian process. Simulating the fractional Brownian motion in the second approach, we use spectral representation. Simulation results show that the latter is more efficient than using the symbolic integral and Monte Carlo integral is the worst. The application of the stochastic model is illustrated through real financial data. dc.format.extent 58 pages dc.language.iso en dc.publisher University of Kansas dc.rights This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author. dc.subject Applied mathematics dc.title Simulation Methods Comparison and Parameter Estimation for a Fractional Stochastic Volatility Model with Application in Stock Price Analysis dc.type Thesis dc.contributor.cmtemember Hu, Yaozhong dc.contributor.cmtemember Pasik-Duncan, Bozenna dc.thesis.degreeDiscipline Mathematics dc.thesis.degreeLevel M.A. kusw.oastatus na kusw.oapolicy This item does not meet KU Open Access policy criteria. kusw.bibid 8086353 dc.rights.accessrights openAccess
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