This paper is concerned with the Bayesian estimation and comparison of flexible, high dimensional multivariate time series models with time varying correlations. The model proposed and considered here combines features of the classical factor model with that of the heavy tailed univariate...

In this dissertation we propose a new model which captures observed features of asset prices. The model reproduces the skewness and fat tails of asset returns by introducing a discretized variance gamma process as the driving innovation process, in addition to a double gamma process to reflect...

This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed Student-t distributions (with unknown degrees of freedom) and exogenous variables in the observation and volatility equations and a jump component in the observation...

This paper is concerned with the Bayesian analysis of stochastic volatility (SV) models with leverage. Specifically, the paper shows how the often used Kim et al. [1998. Stochastic volatility: likelihood inference and comparison with ARCH models. Review of Economic Studies 65, 361–393] method...

In this thesis two contributions are made to the area of mathematical finance. First, in order to explain the non-trivial skewness and kurtosis that is observed in the time series data of constant maturity swap (CMS) rates, we employ the pure jump Levy processes, i.e. in particular Variance...

Item Response Theory (IRT) models are the basis of modern educational measurement. In order to increase testing efficiency, modern tests make ample use of groups of questions associated with a single stimulus (testlets). This violates the IRT assumption of local independence. However, a set of...

The point source is the most common type of source to be modeled for its effect on air pollution. Point sources provide auxiliary information that may impact both the mean and covariance structure of measured responses, but these possible impacts are often overlooked by spatial modelers. In this...

In this paper, I develop and estimate a dynamic model of strategicnetwork formation with heterogeneous agents. The main theoretical resultis the existence of a unique stationary equilibrium, which characterizesthe probability of observing a specific network in the data. As aconsequence, the...

Univariate hierarchical Bayes models are being vigorously researched for use in disease mapping, engineering, geology, and ecology. This dissertation shows how the models can also be used to build modelbased risk maps for areabased roadway traffic crashes. Countylevel vehicle crash records and...

A large body of literature studies the issues of the option price and other ex-antewelfare measures under the microeconomic theory to valuate reductions of risks inherentin environment and human health. However, it does not offer a careful discussion of howto estimate risk reduction values using...