Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/191692
Authors: 
Yaya, OlaOluwa S.
Akinlana, Damola M.
Shittu, Olanrewaju I.
Year of Publication: 
2016
Citation: 
[Journal:] CBN Journal of Applied Statistics [ISSN:] 2476-8472 [Volume:] 7 [Year:] 2016 [Issue:] 2 [Pages:] 137-158
Abstract: 
This paper examined the application of nonlinear Smooth Transition-Generalized Autoregressive Conditional Heteroscedasticity (ST-GARCH) model of Hagerud on prices of banks' shares in Nigeria. The methodology is informed by the failure of the conventional GARCH model to capture the asymmetric properties of the banks' daily share prices. The asymmetry and non-linearity in the model dynamics make it useful for generating nonlinear conditional variance series. From the empirical analysis, we obtained the conditional volatility of each bank's share price return. The highest volatility persistence was observed in Bank 6, while Bank 12 had the least volatility. Evidently, about 25% of the investigated banks exhibited linear volatility behaviour, while the remaining banks showed nonlinear volatility specifications. Given the level of risk associated with investment in stocks, investors and financial analysts could consider volatility modelling of bank share prices with variants of the ST-GARCH models. The impact of news is an important feature that relevant agencies could study so as to be guided while addressing underlying issues in the banking system.
Subjects: 
Specification
Smooth Transition-GARCH
Banks Stocks
Nigeria stock exchange
JEL: 
C22
Document Type: 
Article
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