The purpose of this paper is to model the nonparametric realized volatility of the U.S. based futures contract for dollar exchange with the South African rand (ZAR). We find that the Kajiji-4 Bayesian regularization radial basis function neural network confirms the hypothesis that bilateral mineral alliances contribute to the observed volatility patterns of the ZAR contract. We also confirm the role of conditional volatility, trade-weighted state variables and news effects from the U.S. on the ZAR volatility prediction. Finally, the modelling results provide new evidence to support the heterogeneous trading hypothesis across the bilateral trade dimensions at the daily level.
This paper investigates the random walk behaviour of stock returns on four African stock markets taking into account the thin-trading effect. Worthy noting is the way returns are calculated using the trade-to-trade approach and adjusted to account for the thin-trading effect. The adjustment was done by dividing each trade-to-trade return with the number of days between trades. A test was performed to find if this adjustment method is justifiable. The findings were that there is a positive relationship between the absolute trade-to-trade returns and the number of days between trades. The adjusted stock returns were also tested for normality, which was rejected on all the four markets. In testing if stock returns follow a random walk, two simple traditional testing methods, that is, the serial correlation test and the runs test were used. The findings were that almost half of the stocks on each of the four markets showed significant serial correlation. There was therefore not enough evidence to accept the hypothesis of a random walk.
The focus of this paper is to examine the impact of economic and political uncertainty on foreign direct investment (FDI) flows to African economies. Flows of manufacturing and non-manufacturing U.S. FDI into a sample of host countries in Africa are analyzed in this study. A generalized autoregressive conditional heteroscedasticity (GARCH) model is used to generate economic uncertainty indicators of the inflation rate and the real exchange rate. The results of the study show that for aggregate U.S. FDI flow, economic and political uncertainties are not major concerns. However, for U.S. manufacturing and non-manufacturing FDI flows, economic uncertainties are the major impediments only when combined with political instability and external debt burden.
Extreme events in financial markets are central issues in finance and particularly in risk management and financial regulation. Value at Risk and Expected Shortfall emerged as standard tools for measuring market risk. However, no consensus has yet been reach as to the best method to implement these measures. All conventional methods have significant shortfalls. Extreme Value Theory (EVT) provides a natural approach to the calculation of extreme market risk. The aim of the paper is to illustrate the use of the peaks-over-threshold method of EVT to measure extreme market risk. The technique will be applied to the South African Rand/Dollar One Year Futures Contract.