Three major regression-based seasonal unit root tests: the DHF test introduced by Dickey et al (1984), the HEGY test proposed by Hylleberg et al. (1990) and the Kunst test introduced by Kunst (1997) are compared. The regression model for the DHF test is a reduced form of that for the Kunst test....

GMM provides a computationally convenient estimation method and the resulting estimator can be shown to be consistent and asymptotically normal under the fairly moderate regularity conditions. It is widely known that the information content in the population moment condition has impacts on the...

Value at Risk and the Expected Shortfall are two measurements of market risks for financial assets. Statistically, they are extreme quantiles of the distribution of financial log returns. Though financial log return data are usually both heteroscedastic and fatter-tailed, most of the existing...

Modeling portfolio credit risk involves the default dependencies between the individual securities in a portfolio. The copula is a common approach to construct it. It parameterizes the joint distribution of individual defaults independently of their marginal distributions. The current market...

This thesis builds a stochastic volatility model for the term structure of interest rates, which is also known as the dynamics of the yield curve. The main purpose of the model is to propose a parsimonious and plausible approach to capture some characteristics that conform to some empirical...

Aimed at providing the anticipatory ability for the proactive traffic control systems, a new adaptive online short-term univariate traffic condition forecasting method is presented in this dissertation by assimilating knowledge from previous research. Using 15-minute traffic flow series as a...

Measuring risk is a crucial aspect of the portfolio optimization problem in finance, and of capital adequacy assessment in risk management. Expected Shortfall (ES) has been proposed as a coherent risk measure, by contrast with Value-at-Risk (VaR) and the standard-deviation-type of measures....

Diffusion modeling of commodity price behavior is important for commodity risk management. This research seeks to improve upon the existing commodity diffusion models by incorporating stochastic volatility and seasonality through the affine diffusion framework. In particular, it evaluates affine...

Stochastic Volatility (SV) models play an integral role in modeling time varyingvolatility, with widespread application in finance. Due to the absence of a closed form likelihoodfunction, estimation is a challenging problem. In the presence of outliers, and the highkurtosis prevalent in...

In this work we develop a methodology to reduce the variance when applying Monte Carlo simulation to the pricing of a European, American or Barrier option in a stochastic volatility environment. We begin by presenting some applicable concepts in the theory of stochastic differential equations....