THREE ESSAYS ON ECONOMETRICS: ASYMMETRIC EXPONENTIAL POWER DISTRIBUTION, ECONOMETRIC COMPUTATION, AND MULTIFACTOR MODEL

Abstract

OF THE DISSERTATION Three Essays on Econometrics: Asymmetric Exponential Power Distribution, Econometric Computation, and Multifactor Model by Shiliang Li Dissertation Director: Hiroki Tsurumi The dissertation consists of three independent essays, and they are put in as three chapters. The goal of the first chapter is to develop an estimation procedure for financial time series models with the error terms following the Asymmetric Exponential Power Distribution (AEPD). The AEPD is the most general class of unimodal distributions. In addition to the usual location and scale parameters, it has skewness and kurtosis parameters. The kurtosis parameter is hard to estimate when the sample size is small and skewness is large. We show that when the skewness parameter is either close to zero or close to one the estimation of the kurtosis parameters are virtually unidentifiable unless the sample size is large. We analyze the nonlinear GARCH model (NGARCH) and an asset pricing model known as CKLS. We devise Bayesian Markov chain Monte Carlo (MCMC) algorithms. In chapter 2, we focus on econometric computation and develop a method to speed up intensive computation. The combination of MATLAB, C/C++ and Graphic Processing Unit (GPU) is a method to put convenience and speed together. MATLAB is a high level computing language for econometrics. C/C++ language, on the other hand,