Term of Award

Spring 2016

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (open access)

Department

Department of Mathematical Sciences

Committee Chair

Tharanga Wickramarachchi

Committee Member 1

Patricia Humphrey

Committee Member 2

Arpita Chatterjee

Committee Member 3

Stephen Carden

Abstract

Typical General Autoregressive Conditional Heteroskedastic (GARCH) processes involve normally-distributed errors, and they model strictly-positive error processes poorly. This thesis will present a method for estimating the parameters of a GARCH(1,1) process with shifted Gamma-distributed errors, conduct a simulation study to test the method, and apply the method to real time series data.

Share

COinS