Munich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2010 · 48 citations · 9 references
Open access
BusinessEconomicsFinanceEconometricsFinancial EconomicsTime Series AnalysisAsset Pricing EmpiricsAsset Return ModelingCointegration AnalysisRisk-return AnalysisVolatility AnalysisVolatility ModelingEquity Return VolatilityFinancial Market VolatilityGeneralized Autoregressive Conditional Heteroskedasticity ModelsLeverage Effects On ReturnsStock Market ReturnsTime Series Volatility ModelingVolatilityVolatility Modelling
There is quite an extensive literature documenting the behaviour of stock returns volatility in both developed and emerging stock markets, but such studies are scanty for the Nigerian Stock Exchange (NSE). Modelling volatility is an important element in pricing equity, risk management and portfolio management. For these reasons, this paper investigates the behaviour of stock return volatility of the Nigerian Stock Exchange returns using GARCH (1,1) and the GJR-GARCH(1,1) models assuming the Generalized Error Distribution (GED). Monthly All Share Indices of the NSE from January 1999, to December 2008, provided the empirical sample 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 return series. Also, the results of the GJR-GARCH (1,1) model show 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.
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Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev · Journal of Econometrics · 1986 · 22.3K citations · Full text
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Studies of stock market volatility changes
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