INVESTIGATING STOCK RETURNS VOLATILITY IN NIGERIA USING GARCH MODELS - Bello, Abubakar; A. U. Kinafa; Diri, Gambo Isah (BIMA JOURNAL OF SCIENCE AND TECHNOLOGY GOMBE, 2018)
Stock market volatility affects business investment and economic growth showing market inefficiency. However, the degree of volatility presence in the stock market would lead investors to demand a higher risk premium, creating higher cost of capital which impedes investment and slows economic development. Therefore this work investigates the nature and behavior of Stock Returns Volatility of the Nigerian Stock Exchange (NSE) using the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) model- GARCH (1,1) Model- and the Glosten, Jagannathan and Runkle- Generalized Autoregressive Conditional Heteroskedastic GARCH Model - GJR-GARCH(1,1) model. Monthly All Share Indices of the Nigerian Stock Exchange (NSE) for the periods of 1stJanuary 1985 to 31stDecember 2011 provided the 324 time series sample data for investigating volatility persistence and asymmetric properties of the series. The results of GARCH (1,1) model indicate evidence of volatility clustering in the NSE returns series. Also, the results of the GJR-GARCH (1,1) model shows the existence of leverage effects in the series. Finally, the Generalized Error Distribution (GED) shape test reveals leptokurtic returns distribution. Overall results from this study provide evidence to show volatility persistence, fat- Tail distribution, and leverage effects for the Nigeria stock returns data. Base on the findings in this work, investors are at greater risk if the market is not modernized to improve efficiency.