Dissertation (MBus) -- AUT University, 2009. / Includes bibliographical references. Also held in print (vii., 43 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 332.632220994 CHE)

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.

Thesis (M.Sc.(Finance))--University of Pretoria, 2003. / Abstract in English. Includes bibliographical references.

Thesis (Ph. D.)--University of Chicago, Graduate School of Business, June 2003. / Includes bibliographical references. Also available on the Internet.

Thesis (B.A.)--Haverford College, Dept. of Economics, 2006. / Includes bibliographical references.

Thesis (M. Com.)--University of Canterbury, 2006. / Typescript (photocopy). "Senior supervisor: Prof. Edwin Maberly, Co-supervisor: Dr. Raylene Pierce." Includes bibliographical references (leaves 78-81). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed October 25, 2007) Includes bibliographical references.

The accurate estimation and forecasting of volatility is of utmost importance for anyone who participates in the financial market as it affects the whole financial system and, consequently, the whole economy. It has been a popular subject of research with no general conclusion as to which model provides the most accurate forecasts. This thesis enters the ongoing debate by assessing and comparing the forecasting performance of popular volatility models. Moreover, the role of key parameters of volatility is evaluated in improving the forecast accuracy of the models. For these purposes a number of US and European stock indices is used. The main contributions are four. First, I find that implied volatility can be per se forecasted and combining the information of implied volatility and GARCH models predict better the future volatility. Second, the GARCH class of models are superior to the stochastic volatility models in forecasting the one-, five- and twenty two-days ahead volatility. Third, when the realised volatility is modelled and forecast directly using time series, I find that the HAR model performs better than the ARFIMA. Finally, I find that the leverage effect and implied volatility significantly improve the fit and forecasting performance of all the models.

Rights issues continue to be a well-researched topic within the field of corporate finance. The focus of this study was to consider the long-run impact of rights issue on company performance both in terms of share price performance and operating performance. The long-run perspective taken in this study adds to the literature, which usually looks at the immediate share price reaction to a rights issue announcement. The study also looked at whether the intended use of capital stated in the SENS announcement had any post-issue effect on the share price. The study found significantly negative cumulative average abnormal returns within the first year after the rights issue. This study confirms the expected negative share price reaction to a rights issue announcement. The study also found evidence that companies that use the proceeds to repay debt, invest or for general purposes had a negative share price reaction to a rights issue announcement. Companies that were vague about the intended purpose of the rights issue had the largest post-issue underperformance. The study did not find any statistically significant evidence that the rights issue announcement had any effect on the operating performance. These findings suggest that rights issues have more impact on a company’s share price, and no clear impact on the operating performance of the issuing company. / Dissertation (MBA)--University of Pretoria, 2013. / lmgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted