The performance of maximum likelihood factor analysis on South African stock price performance
Moroke, Ntebogang Dinah
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Abstract: The purpose of this paper is to explore the effectiveness and applicability of Maximum Likelihood Factor Analysis (MLFA) method on stock price performance. This method identifies the variables according to their co-movement and variability and builds a model that can be useful for prediction and ranking or classification. The results of factor analysis in this study provide a guide as far as investment decision is concerned. Stock price performance of the seven well-known and biggest companies listed in the Johannesburg stock exchange (JSE) was used as an experimental unit. Monthly data was available for the period 2010 to 2014.Details of a trivariate factor model is: Factor 1 comprises of Absa and Standard Bank (Financial sectors), Factor 2 has Shoprite and Pick 'n Pay (Retail sectors) while Factor 3 collected Vodacom MTN and Sasol (Industrial sectors). The companies contribute 46.9%, 12.7% and 10.8% respectively to the three sectors and these findings are confirmed by a Chi-square and the Akaike information criterion to be valid. The three factors are also diverse and reliable according to Tucker and Lewis and Cronbach's coefficients. The findings of this study give economic significance and the study is relevant as it gives investors and portfolio manager's sensible investment reference.