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Course Number: LODDOA 070306, Summer 2009

College/University: Maryville MO

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Bayesian Analysis of Multivariate Stochastic Volatility and Dynamic Models Antonello Loddo Dongchu Sun, Dissertation Supervisor ABSTRACT We consider a multivariate regression model with time varying volatilities in the error term. The time varying volatility for each component of the error is of unknown nature, may be deterministic or stochastic. We propose Bayesian stochastic search as a feasible variable...

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Bayesian Analysis of Multivariate Stochastic Volatility and Dynamic Models Antonello Loddo Dongchu Sun, Dissertation Supervisor ABSTRACT We consider a multivariate regression model with time varying volatilities in the error term. The time varying volatility for each component of the error is of unknown nature, may be deterministic or stochastic. We propose Bayesian stochastic search as a feasible variable selection technique for the regression and volatility equations. We develop <a href="/keyword/markov-chain-monte-carlo/" ><a href="/keyword/markov-chain-monte/" >markov chain monte</a> carlo</a> (MCMC) algorithms that generate a posteriori restrictions on the elements of both the regression coefficients and the covariance matrix of the error term. Efficient parametrization of the time varying <a href="/keyword/covariance-matrices/" >covariance matrices</a> is studied using different modified Cholesky decompositions. We propose a hierarchal approach for selection of the volatility equation's variance components. We extend the results of the first in order to apply the stochasti...

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