Beschreibung
We consider some popular stochastic differential equation models used in finance, such as the Vasicek Interest Rate model, the Heston model and a new fractional Heston model. We discuss how to perform inference about unknown quantities associated with these models in the Bayesian framework. We apply our methodology to simulated and real financial data with success. We then discuss how to make forecasts using both the Heston and the fractional Heston model. We make comparisons between the models and show that using our new fractional Heston model can lead to improve forecasts for real financial data.
Autorenporträt
Dr. Muhannad Al-Saadony has obtained his PhD in Statistics/ Measure Theory from Plymouth University/ United Kingdom in 2013. The main area of his work is Stochastic (Partial) Differential Equation with application in Finance and Medical Data using R and Matlab, Now, He is working in Al-Qadisiyha University/ Iraq as Lecturer in Statistics department
