STOCK PRICES PREDICTION USING GEOMETRIC BROWNIAN MOTION: ANALYSIS OF THE NIGERIAN STOCK EXCHANGE

Agbam, Azubuike Samuel 

Department of Banking and Finance,

Rivers State University, Nkpolu-Oroworukwo, Port Harcourt

Email: azubuikesamuelagbam@yahoo.com

ABSTRACT

In this study, the stochastic price movements of stocks are modeled by a geometric Brownian motion (GBM). The model assumptions of the GBM with drift: continuity, normality and Markov tendency, were investigated using four years (2015 – 2018) of historical closing prices of ten stocks listed on The Nigerian Stock Exchange. The sample for the study is based on the eight sectors of The Nigerian Stock Exchange and most continuously traded stocks. The predicted stocks prices have been compared to actual prices in order to evaluate the validity of the prediction model. On stocks prices prediction using geometric Brownian motion model, the algorithm starts from calculating the value of returns, followed by estimating values of volatility and drift, obtaining the stock prices forecast, calculating the forecast Mean Absolute Percentage Error, calculating the stock expected prices and calculating the confidence level at 95%. The results show that the value of the MAPE is 50% and below for the one to two year holding periods, and above 50% for the three year holding period. The MAPE and directional prediction accuracy method provided support that over short periods the GBM model is accurate. Meaning that the GBM is a reasonable predictive model for one or two years, but for three years, therefore, it is an inaccurate predictor.

Keyword: Stochastic forecasting, Geometric Brownian motion, Stochastic Differential Equation, Stock return, The Nigerian stock Exchange.