Stochastic model of stock market price Movement in the assessment of two selected companies in time-varying investments

Abstract

This paper examined the stochastic analysis of stock market prices of Dangote Cement and Bua Cement PLCs respectively, using Markov chain formation in finite states. The stock price data of the two companies were subjected to a 3-step transition probability matrix, while the mean data of Oct-Dec of each year (i.e. 2017-2021) were calculated and used as column vectors. This gave us a precise condition for obtaining variations of future price changes for both companies. From the stochastic analysis, it was discovered that Dangote Cement PLC has the highest rate of return: 137.4371 and also has the best probability of price reduction in the near future: 34% and a 32% chance of no change in price. This permeates an investor about stock price movement for the decision making. Recommendations includes stochastic control in modeling of stock price assessment in the further study.