Modelling Stock Returns Volatility on Uganda Securities Exchange

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dc.contributor.authorWeke, Patrick G. O.
dc.contributor.authorNamugaya, Jalira
dc.contributor.authorCharles, Wilson M.
dc.date.accessioned2016-09-21T12:36:24Z
dc.date.available2016-09-21T12:36:24Z
dc.date.issued2014
dc.description.abstractStock returns volatility of daily closing prices of the Uganda Securities Exchange(USE) all share index over a period of 04/01/2005 to 18/12/2013 is Modelled. We employ different univariate Generalised Autoregressive Conditional Heteroscedastic(GARCH) models; both symmetric and asymmetric. The models include; GARCH(1,1), GARCH-M, EGARCH(1,1) and TGARCH(1,1). Quasi Maximum Likelihood(QML) method was used to estimate the models and then the best performing model obtained using two model selection criteria; Akaike Information criterion(AIC) and Bayesian Information criterion(BIC). Overall, the GARCH(1; 1) model outperformed the other competing models. This result is analogous with other studies, that GARCH(1; 1) is best.en_US
dc.identifier.citationNamugaya, J., Weke, P.G. and Charles, W.M., 2014. Modelling Stock Returns Volatility on Uganda Securities Exchange. Applied Mathematical Sciences, 8(104), pp.5173-5184.en_US
dc.identifier.doi10.12988/ams.2014.46394
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3834
dc.language.isoenen_US
dc.subjectModellingen_US
dc.subjectVolatilityen_US
dc.subjectUganda Securities Exchangeen_US
dc.titleModelling Stock Returns Volatility on Uganda Securities Exchangeen_US
dc.typeJournal Article, Peer Revieweden_US
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