Using and Evaluating Infinite Multivariate Scale Mixtures of Normals to Estimate the CCR Density
Thursday, Aug 8: 9:50 AM - 10:05 AM
3194
Contributed Papers
Oregon Convention Center
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.
Multivariate Scale Mixtures
Bayesian Method
UNMIX
CCR
Main Sponsor
Section on Bayesian Statistical Science
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