Forecasting equity prices for selected companies at the Nairobi Securities Exchange

Abstract

Information asymmetry is the main cause of uncertainty in security exchanges all over the world. There are “informed investors” and “uninformed investors” with the latter having imperfect information. Due to this uncertainty, investors have been trying to come up with ways of predicting stock prices and to find the right stocks and perfect timing for when to buy or sell. The primary target of this research is to construct a model that will forecast the short term stock prices for five selected companies listed in the Nairobi Securities Exchange divided into those that are highly traded, highly capitalized and highly volatile. Secondary datasets of returns on Kenyan stock market prices were retrieved from online sources such as the Nairobi Securities Exchange website and the Valuraha platform. The model employed in this paper took the form of an autoregressive integrated moving average (ARIMA). Results obtained revealed an impressive performance of the ARIMA model in stock price prediction especially when it came to the highly traded and highly capitalized stocks.