Analysis of Malaysia Stock Return Using Mixture of Normal Distributions - Kamaruzzaman, Zetty Ain; Isa, Zaidi (International Journal of Sciences: Basic and Applied Research (IJSBAR), 2015)
In this paper, two component univariate mixtures of Normal distributions is proposed to accommodate the non-normality and asymmetry characteristics of financial time series data as found in the distribution of monthly rates of returns for Bursa Malaysia Index Series namely the FTSE Bursa Malaysia Composite Index (FBMKLCI) from July 1990 until July 2010. Firstly, we give some basic definitions and concepts of mixtures of Normal distributions. Next, we explore some of its distribution properties. In support of determining the number of components, we use the information criterion for model selection. The measures provide supporting evidence in favour of the two-component mixtures of Normal distributions. For parameter estimation, we apply the most commonly used Maximum Likelihood Estimation (MLE) via the EM algorithm to fit the two-component mixtures of Normal distributions using data set on logarithmic stock return of Bursa Malaysia index.