Theses and Dissertations
Different Estimations of Time Series Models and Application for Foreign Exchange in Emerging Markets
Issuing Body
Mississippi State University
Advisor
Wu, Tung-Lung
Committee Member
McBride, Matthew S.
Committee Member
Sepehrifar, Mohammad
Date of Degree
8-12-2016
Document Type
Graduate Thesis - Open Access
Major
Statistics
Degree Name
Master of Science (M.S.)
College
College of Arts and Sciences
Department
Department of Mathematics and Statistics
Abstract
Time series models have been widely used in simulating financial data sets. Finding a nice way to estimate the parameters is really important. One of the traditional ways is to use maximum likelihood estimation to make an approach. However, when the error terms don’t have normality, MLE would be less efficient. Quasi maximum likelihood estimation, also regarded as Gaussian MLE, would be more efficient. Considering the heavy-tailed financial data sets, we can use non-Gaussian quasi maximum likelihood, which needs less assumptions and conditions. We use real financial data sets to compare these estimators.
URI
https://hdl.handle.net/11668/19994
Recommended Citation
Wang, Jingjing, "Different Estimations of Time Series Models and Application for Foreign Exchange in Emerging Markets" (2016). Theses and Dissertations. 1498.
https://scholarsjunction.msstate.edu/td/1498