Modeling Volatility in Selected Nigerian Stock Market

Ekum Matthew Iwada; Owolabi Toyin Omoyeni.; Alakija Temitope

Modeling Volatility in Selected Nigerian Stock Market

Ekum Matthew Iwada & Owolabi Toyin Omoyeni. and Alakija Temitope

Abstract

Modeling the volatility in daily stock prices requires to study the particular error distribution that best fits the data, since it is evident that the stock market is now relied upon by investment analysts, economists and policy makers to measure changes in the general economic activities of a nation and globally. This study, therefore aimed at fitting symmetric and asymmetric GARCH models to daily stock prices of selected securities in Nigeria using Access and Fidelity Banks daily closing share prices from April 1, 2010 to December 16, 2016. This study estimates first order symmetric and asymmetric volatility models each in Normal, Student’s-t and generalized error distributions (GED) with the view to selecting the best forecasting volatility model with the most appropriate error distribution. The results of the analysis shows that PARCH (1, 1), EGARCH (1, 1) and TGARCH in that order with GED were selected to be the best fitted models based on the Akaike Information Criterion (AIC). The out-of-sample forecasting evaluation result adjudged PGARCH (1, 1) with GED as the best predictive model based on Mean Absolute Error and Theil Inequality Coefficient and EGARCH(1,1) based on root mean square error (RMSE). It is therefore recommended that empirical workers should consider alternative error distributions while specifying predictive volatility model as less contributing error distributions implies incorrect specification, which could lead to loss of efficiency in the model, especially to model the volatility in stock prices.

Keywords

Asymmetric GARCH; Student’s t distribution; Normal distribution; generalized error distribution; Stock prices

References

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Modeling Volatility in Selected Nigerian Stock Market

Abstract

Keywords

References

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