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Inverse Gaussian Ornstein-Uhlenbeck Applied To Modeling High Frequency Data, Emmanuel Kofi Kusi
Inverse Gaussian Ornstein-Uhlenbeck Applied To Modeling High Frequency Data, Emmanuel Kofi Kusi
Open Access Theses & Dissertations
With about 226050 estimated deaths worldwide in 2010, an earthquake is considered as one of the disasters that records 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 IG(a,b) process. IG(a,b) Ornstein-Uhlenbeck processes offers 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 markets by fitting the superposed IG(a,b) Ornstein-Uhlenbeck model to earthquake and financial time series.