Share Price Movement and the White-noise Hypothesis: the Algebraic Approach

Abstract

Over time market players have developed much interest in factors that bring about movement or change in share price in the stock market either upward movement or downward movement several issues have been adduced for this over the years, some of which are rational and some are said to be irrational factors for the purpose of this study this is called market noise or white noise

The problem is that all the mentioned  factors can be measured or have been measured one way or the other except the white noise  that seems no one  have provided any serious measurement for,  thus,  in this study an attempt is made to test this factor

The secondary source of data was used for the purpose of the analysis and a multiple regression analysis was adopted 

The model derived by the researcher shows that the white noise is equal to the error factor of the fist order of the regression. The regression model derived in the second order was tested and the result shows that the white noise will improve the coefficient of the impact variables when used and that the predictive power of the model becomes more realistic with the inclusion of the white noise variables than when excluded

It was therefore recommended that white noise coefficient be included when measuring the impact of the independent variable on the market values of share for effective prediction purpose