Thesis submitted in fulfilment of the requirements for the degree of Master of Management in Finance and Investment (MMFI) in the Faculty of Commerce, Law and Management Wits Business school at the University of Witwatersrand, 2016 / This thesis studied the effects of terrorist attacks on Kenya‟s financial markets between January 2004 and December 2014. The study uses an augmented asset-pricing model similar to that in Eldor and Menelik (2004). The model includes terrorist attack dummies representing location of the attack, the type of attack, the intended target, number of people injured and number of people killed. Data on the terrorist attacks and share index values and foreign exchange rates variables are used to estimate the model. The results show that attacks carried out using explosives had a positive impact on share prices on the NSE. On the flipside, attacks that were carried out on facilities/infrastructure or on religious figures/institutions as well as those carried out using incendiaries had a negative impact on the NSE. An increase in the number of people injured also led to a greater negative impact on the NSE. As regards the forex market, attacks carried out using firearms and incendiaries led to a depreciation of the local currency. Transport attacks on the other hand led to an appreciation. Similarly, the greater the number of people injured led to a greater appreciation of the KES / GR2018

Department of Statistics / MSc (Statistics) / The ripple e ect of a stock market crash due to extremal dependence is a global issue with key attention and it is at the core of all modelling e orts in risk management. Two methods of extreme value theory (EVT) were used in this study to model equity risk and extremal dependence in the tails of stock market indices from four African emerging markets: South Africa, Nigeria, Kenya and Egypt. The rst is the \bivariate-threshold-excess model" and the second is the \point process approach". With regards to the univariate analysis, the rst nding in the study shows in descending hierarchy that volatility with persistence is highest in the South African market, followed by Egyptian market, then Nigerian market and lastly, the Kenyan equity market. In terms of risk hierarchy, the Egyptian EGX 30 market is the most risk-prone, followed by the South African JSE-ALSI market, then the Nigerian NIGALSH market and the least risky is the Kenyan NSE 20 market. It is therefore concluded that risk is not a brainchild of volatility in these markets. For the bivariate modelling, the extremal dependence ndings indicate that the African continent regional equity markets present a huge investment platform for investors and traders, and o er tremendous opportunity for portfolio diversi cation and investment synergies between markets. These synergistic opportunities are due to the markets being asymptotic (extremal) independent or (very) weak asymptotic dependent and negatively dependent. This outcome is consistent with the ndings of Alagidede (2008) who analysed these same markets using co-integration analysis. The bivariate-threshold-excess and point process models are appropriate for modelling the markets' risks. For modelling the extremal dependence however, given the same marginal threshold quantile, the point process has more access to the extreme observations due to its wider sphere of coverage than the bivariate-threshold-excess model. / NRF