Data Research, Vol. 3, Issue 4, Dec  2019, Pages 51-59; DOI: 10.31058/j.data.2019.34001 10.31058/j.data.2019.34001

On the Performance of the Method of Principal Component and Maximum Likelihood for Factor Analysis of the Nigerian Stock Exchange

, Vol. 3, Issue 4, Dec  2019, Pages 51-59.

DOI: 10.31058/j.data.2019.34001

Bilesanmi A. O. 1 , Aronu, C. O. 2*

1 Department of General Studies, Petroleum Training Institute, Effurun-Delta State, Nigeria

2 Department of Statistics, ChukwuemekaOdumegwuOjukwu University, Uli, Nigeria

Received: 1 November 2019; Accepted: 20 November 2019; Published: 12 December 2019

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Abstract

This study assessed the performance of the principal component analysis and the maximum likelihood analysis for factor analysis of the various sectors of the Nigerian Stock Exchange from 2015-2017. The data used in this study was secondary data from daily official list of the Nigeria Stock Exchange (NSE). This study covers monthly stock rates of returns of the Nigerian Stock Exchange daily official list for the period of January, 2015 - December 2017.  The findings of the study showed that the principal component analysis (PCA) and the maximum likelihood analysis (MLA) evenly identified that two factors were able to explain about 80% of total variation in the models. Further findings showed that using the principal component analysis that the sectors  that explain over 50% of the variability attributed to the model includes;  Healthcare, Financial Services, Natural Resources, Construction Real Estate, Agriculture, Oil Gas, ICT, Conglomerates, Consumer Goods, Services, and Industrial Goods. Also, findings using the maximum likelihood method  revealed that the sectors  that explain over 50% of the variability attributed to the model comprises of Agriculture, Oil & Gas, Financial Services, Healthcare, Natural Resources, Conglomerates, Construction Real Estate, ICT, Consumer Goods, and Industrial Goods. In conclusion, the two methods of factor extraction were able to evenly identify the same number of factors to be adequate in explaining the total variation for the Nigerian Stock Exchange Market within the period under study. Also, the methods identified industrial goods as the least sector that contributes to the variability of the Nigerian Stock Market within the period under study. In addition, an insignificant difference was found between the performance of the PCA and MLA in determining the variability in the Nigerian Stock market.

Keywords

Factors Analysis, Industrial Goods, Maximum likelihood Analysis, Principal Component Analysis, Stock Market

Copyright

© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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