Estimating Volatility of Daily Price Returns of Nigerian Stock Market

Abstract

S.C Emenyonu, B. O. Osu, C. Olunkwa

The financial markets are opened to market risk. Modelling the volatility in daily stock prices entails studying the partic- ular error distribution that is most appropriate for the model. Considering a particular Nigeria stock market from April 1, 2016 to December 16, this study estimates both the symmetric and asymmetric volatilitymodels.The ARMA-GARCH, ARMA-EGARCH models were employed with the error distributions such as normal distribution, student t-distribution and skewed student t- distribution. The ARMA (2,1)-EGARCH (1,1) with student t-distribution was seen to be the most appropriate model. A volatility forecasting accuracy was determined by using the mean absolute scaled error (MASE) to predict the values of the stock market prices for the next 20 years and the result showed that the model was appropriate for predicting volatility.Hence volatility prediction would help inachieving a sound policy decision.

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