SV MIXTURE, CLASSIFICATION USING EM ALGORITHM
Journal Title: Asian Economic and Financial Review - Year 2013, Vol 3, Issue 4
Abstract
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).
Authors and Affiliations
Ahmed Hachicha| University of Sfax, Department of Economic Development, Faculty of Economics and Management of Sfax, Airport road Km 4.5- B.P. 3018, Sfax, Tunisia, Fatma Hachicha| Department of Finance. Faculty of Economics and Management of Sfax Airport road Km 4.5- B.P. 3018, Sfax, Tunisia, Afif Masmoudi| Department of Mathematics. Faculty of Sciences of Sfax Soukra Road Km.3.5- B.P.1171 Sfax, Tunisia
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