A Matrix Approach in Predicting Stock Market Prices with Regularly Varying Perturbations

Abstract

The behavior of a stock exchange market can be analysed through the temporal changes in volatile market variables in time so as to predict stock price fluctuations. However, a matrix application to Dangote stock market prices is considered where an illustrative case is provided in different forms. The systems of linear Equations were perturbed and there were no significant changes in the original systems which makes our model robust and stable. The statistical variables such as mean, kurtosis and skewness gave clear insight to investors about investment plans. Nevertheless, we developed, proved propositions and theorems. Finally, the results of propositions were simulated and graphical solutions obtained according to the value of each investment of different periods. This is informative to Dangote and other corporate investors develop strategies to achieve their investment goals and their daily decision making.