Data Analysis Using a Coupled System of Ornstein–Uhlenbeck Equations Driven by Lévy Processes
Axioms
; 11(4):160, 2022.
Article
Dans Anglais
| ProQuest Central | ID: covidwho-1809680
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 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.
Mathematics; Ornstein–Uhlenbeck equation; background driving Lévy process; gamma process; inverse Gaussian process; coupled system; sample paths; Stock exchanges; Data analysis; Behavior; Datasets; Random variables; Performance prediction; Trends; Volcanoes; Prediction models; Securities markets; Pandemics; Geophysics; Medical research; Earthquakes; Mathematical models; Stochastic models; Disease prevention; Empirical analysis; Coronaviruses; Stochastic systems; Data sets; COVID-19
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
ProQuest Central
langue:
Anglais
Revue:
Axioms
Année:
2022
Type de document:
Article
Documents relatifs à ce sujet
MEDLINE
...
LILACS
LIS