Abstract Number:
3194
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Hasan Hamdan (1), Mozhdeh Forghaniarani (2)
Institutions:
(1) James Madison University, N/A, (2) N/A, N/A
Co-Author:
First Author:
Presenting Author:
Abstract Text:
In this study, we will use infinite multivariate scale mixtures of Normal distributions to model the density of the continuously compounded return, CCR, of five major American stocks. The approach is based on using a finite discretized version of the density, then estimating the parameters of the corresponding multivariate density based on that of the univariate components using UNMIX, which is a newly developed program for estimating and fitting univariate infinite scale mixtures of Normals. The fitted density is compared with the empirical and the Bayesian method of estimation to the same data. The CCR of the weekly closing stock prices of Google, Amazon, Exxon Mobile, Apple and Fannie Mae and maybe few others. We also check the effect of correlation on the fits.
Keywords:
Multivariate Scale Mixtures| Bayesian Method|UNMIX|CCR| |
Sponsors:
Section on Bayesian Statistical Science
Tracks:
Applications in Applied Sciences
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