Date of Award
2019-01-01
Degree Name
Master of Science
Department
Mathematical Sciences
Advisor(s)
Maria C. Mariani
Abstract
With about 226050 estimated deaths worldwide in 2010, earthquake is considered as one of the disasters that record a great number of deaths. This Thesis develops a model for the estimation of magnitude of future seismic events.
We propose a stochastic differential equation arising on the Ornstein-Uhlenbeck processes driven by Inverse Gaussian (a,b) process. Inverse Gaussian (a,b) Ornstein-Uhlenbeck processes offer analytic flexibility and provides a class of continuous time processes capable of exhibiting long memory behavior. The stochastic differential equation is applied to geophysics and financial stock market by fitting the superposed Inverse Gaussian (a,b) Ornstein-Uhlenbeck model to earthquake and financial time series.
Language
en
Provenance
Received from ProQuest
Copyright Date
2019-06
File Size
69 pages
File Format
application/pdf
Rights Holder
Emmanuel Kofi Kusi
Recommended Citation
Kusi, Emmanuel Kofi, "Inverse Gaussian Ornstein-Uhlenbeck Applied To Modeling High Frequency Data" (2019). Open Access Theses & Dissertations. 3102.
https://scholarworks.utep.edu/open_etd/3102