This study tests for the market efficiency of the Nairobi Securities Exchange (NSE) after the year 2000 to determine the effect of technological advancements on market efficiency. Data that is used is the NSE 20 share index over the period 2001 to 2015; and the NSE All Share Index (NSE ASI) from its initiation during 2008 to 2015. We cannot accept the Efficient Market Hypothesis (EMH) for the NSE using the serial correlation test, the unit root tests and the runs test. However, we can accept the EMH for the more robust variance ratio test. Overall, the results of the market efficiency are mixed. The most significant finding is that the efficiency of the NSE has increased since the year 2000 which suggests that advancements in technology have contributed to the increase in the market efficiency of the NSE. / Business Management / M. Com. (Business Management)

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