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Comparing Regime-Switching Models In Time Series: Logistic Mixtures vs. Markov Switching

dc.contributor.advisorKedem, Benjaminen_US
dc.contributor.authorPaliouras, Dimitrios V.en_US
dc.description.abstractThe 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.en_US
dc.format.extent3623189 bytes
dc.titleComparing Regime-Switching Models In Time Series: Logistic Mixtures vs. Markov Switchingen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentApplied Mathematics and Scientific Computationen_US
dc.subject.pqcontrolledEconomics, Financeen_US
dc.subject.pquncontrolledlogistic mixturesen_US
dc.subject.pquncontrolledEM algorithmen_US
dc.subject.pquncontrolledcommodity futuresen_US

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