Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = background driving Lévy process

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
17 pages, 1720 KiB  
Article
Data Analysis Using a Coupled System of Ornstein–Uhlenbeck Equations Driven by Lévy Processes
by Maria C. Mariani, Peter K. Asante, William Kubin and Osei K. Tweneboah
Axioms 2022, 11(4), 160; https://doi.org/10.3390/axioms11040160 - 1 Apr 2022
Cited by 4 | Viewed by 3146
Abstract
In this work, we have analyzed data sets from various fields using a coupled Ornstein–Uhlenbeck (OU) system of equations driven by Lévy processes. The Ornstein–Uhlenbeck model is well known for its ability to capture stochastic behaviors when used as a predictive model. There’s [...] Read more.
In this work, we have analyzed data sets from various fields using a coupled Ornstein–Uhlenbeck (OU) system of equations driven by Lévy processes. The Ornstein–Uhlenbeck model is well known for its ability to capture stochastic behaviors when used as a predictive model. There’s empirical evidence showing that there exist dependencies or correlations between events; thus, we may be able to model them together. Here we show such correlation between data from finance, geophysics and health as well as show the predictive performance when they are modeled with a coupled Ornstein–Uhlenbeck system of equations. The results show that the solution to the stochastic system provides a good fit to the data sets analyzed. In addition by comparing the results obtained when the BDLP is a Γ(a,b) process or an IG(a,b) process, we are able to deduce the best choice out of the two to model our data sets. Full article
(This article belongs to the Special Issue Financial Mathematics and Econophysics)
Show Figures

Figure 1

Back to TopTop