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Stochastic Models and Inferences for Commodity Futures Pricing

Title: Stochastic Models and Inferences for Commodity Futures Pricing.
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Name(s): Ncube, Moeti M., 1985-, author
Srivastava, Anuj, professor co-directing dissertation
Doran, James, professor co-directing dissertation
Mason, Patrick, outside committee member
Niu, Xufeng, committee member
Huffer, Fred, committee member
Wu, Wei, committee member
Department of Statistics, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2009
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: The stochastic modeling of financial assets is essential to the valuation of financial products and investment decisions. These models are governed by certain parameters that are estimated through a process known as calibration. Current procedures typically perform a grid-search optimization of a given objective function over a specified parameter space. These methods can be computationally intensive and require restrictions on the parameter space to achieve timely convergence. In this thesis, we propose an alternative Kalman Smoother Expectation Maximization procedure (KSEM) that can jointly estimate all the parameters and produces better model t that compared to alternative estimation procedures. Further, we consider the additional complexity of the modeling of jumps or spikes that may occur in a time series. For this calibration we develop a Particle Smoother Expectation Maximization procedure (PSEM) for the optimization of nonlinear systems. This is an entirely new estimation approach, and we provide several examples of it's application.
Identifier: FSU_migr_etd-2707 (IID)
Submitted Note: A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Degree Awarded: Fall Semester, 2009.
Date of Defense: July 17, 2009.
Keywords: Particle Smoothing, EM Algorithm, Particle Filter Kalman Filter, Kalman Smoothing, Parameter Learning, Gaussian Mixture
Bibliography Note: Includes bibliographical references.
Advisory Committee: Anuj Srivastava, Professor Co-Directing Dissertation; James Doran, Professor Co-Directing Dissertation; Patrick Mason, Outside Committee Member; Xufeng Niu, Committee Member; Fred Huffer, Committee Member; Wei Wu, Committee Member.
Subject(s): Statistics
Probabilities
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_migr_etd-2707
Owner Institution: FSU

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Ncube, M. M. (2009). Stochastic Models and Inferences for Commodity Futures Pricing. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-2707