On the Application of Geometric Brownian Motion Model to Stock Price Process on the Nigerian Stock Market

Abstract

This Study presents the application of Geometric Brownian Motion (GBM) model for the prediction of stock prices in the Nigeria Stock Market. We analyzed and examined the appropriateness of the GBM model in predicting stock prices on the Nigeria Stock market. Fluctuations of stock prices on daily basis make them more volatile and difficult for financial managers and investors to predict future stock prices. This paper, therefore, aims to give the importance of the application of GBM to stock prices and help financial managers and investors in forecasting future stock prices for a short-term investment. The sample for this study was based on listed stock
quoted on the Nigerian stock exchange (NSE). Daily stock prices data of Nestle Foods, First Bank, Associated Bus Company, MRS Oil, Dangote Cement and Transnational Corporation were obtained from updates of the official website of the NSE over a period of one month. It was observed that within a short period of time, the GBM is effective in precisely predicting the daily stock prices of stocks analyzed and examined.