Modelling Stock Returns Volatility on Uganda Securities Exchange

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dc.creatorWeke, Patrick G. O.
dc.creatorNamugaya, Jalira
dc.creatorCharles, Wilson M.
dc.date2016-09-21T12:36:24Z
dc.date2016-09-21T12:36:24Z
dc.date2014
dc.date.accessioned2018-03-27T08:58:03Z
dc.date.available2018-03-27T08:58:03Z
dc.descriptionStock 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.
dc.identifierNamugaya, 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.
dc.identifierhttp://hdl.handle.net/20.500.11810/3834
dc.identifier10.12988/ams.2014.46394
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3834
dc.languageen
dc.subjectModelling
dc.subjectVolatility
dc.subjectUganda Securities Exchange
dc.titleModelling Stock Returns Volatility on Uganda Securities Exchange
dc.typeJournal Article, Peer Reviewed

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