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Please use this identifier to cite or link to this item: http://hdl.handle.net/1903/6978

Title: Comparing Regime-Switching Models In Time Series: Logistic Mixtures vs. Markov Switching
Authors: Paliouras, Dimitrios V.
Advisors: Kedem, Benjamin
Department/Program: Applied Mathematics and Scientific Computation
Type: Thesis
Sponsors: Digital Repository at the University of Maryland
University of Maryland (College Park, Md.)
Subjects: Statistics
Economics, Finance
Statistics
Keywords: Regime-switching
Markov
logistic mixtures
EM algorithm
commodity futures
Issue Date: 16-May-2007
Abstract: The purpose of this thesis is to review several related regime-switching time series models. Specifically, we use simulated data to compare models where the unobserved state vector follows a Markov process against an independent logistic mixture process. We apply these techniques to crude oil and heating oil futures prices using several explanatory variables to estimate the unobserved regimes. We find that crude oil is characterized by regime switching, where prices alternate between a high volatility state with low returns and significant mean reversion and a low volatility state with positive returns and some trending. The spread between one-month and three-month futures prices is an important determinant in the dynamics of crude oil prices.
URI: http://hdl.handle.net/1903/6978
Appears in Collections:UMD Theses and Dissertations
Computer Science Theses and Dissertations
Mathematics Theses and Dissertations

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