%0 Journal Article
%T SV Mixture, Classification Using EM Algorithm
%A Ahmed Hachicha
%A Fatma Hachicha
%A Afif Masmoudi
%J Asian Economic and Financial Review
%D 2013
%I Asian Economic and Social Society
%X The present paper presents a theoretical extension of our earlier work entitled¡°A comparative study of two models SV with MCMC algorithm¡± cited, Rev Quant Finan Acc (2012) 38:479-493 DOI 10.1007/s11156-011-0236-1 where we propose initially a mixture stochastic volatility model providing a tractable method for capturing certain market characteristics. To estimate the parameter of a mixture stochastic volatility model, we first use the Expectation-Maximisation (EM) algorithm. The second step is to adopt the clustering approach to classify the database into subsets (clusters).
%K Mixture stochastic volatitlity model
%K Expectation-Maximization algorithm
%K clustering approach
%U http://www.aessweb.com/abstract.php?m=April2013&id=5002&aid=1849