| dc.creator |
Weke, Patrick G. O. |
|
| dc.creator |
Namugaya, Jalira |
|
| dc.creator |
Charles, Wilson M. |
|
| dc.date |
2016-09-21T12:36:24Z |
|
| dc.date |
2016-09-21T12:36:24Z |
|
| dc.date |
2014 |
|
| dc.date.accessioned |
2018-03-27T08:58:03Z |
|
| dc.date.available |
2018-03-27T08:58:03Z |
|
| dc.identifier |
Namugaya, 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.identifier |
http://hdl.handle.net/20.500.11810/3834 |
|
| dc.identifier |
10.12988/ams.2014.46394 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.11810/3834 |
|
| dc.description |
Stock 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.language |
en |
|
| dc.subject |
Modelling |
|
| dc.subject |
Volatility |
|
| dc.subject |
Uganda Securities Exchange |
|
| dc.title |
Modelling Stock Returns Volatility on Uganda Securities Exchange |
|
| dc.type |
Journal Article, Peer Reviewed |
|