This paper develops a new index of financial market stress for South Africa (SAFSI) over the period 1995-2017, that has the advantage of capturing the interconnectedness of financial markets as well as enabling each indicator to be assessed in terms of its systemic importance. The index represents a technical improvement over past measures as it is comprised of financial indicators that have been selected based on their ability to capture key periods of financial stress in the economy.
In this paper, we extend the literature on modelling exchange rate volatility in South Africa by estimating a range of models, including some that attempt to account for structural breaks and long memory. We examine the key nominal exchange rates of the South African rand and replicate common findings in the literature; particularly that volatility is ‘persistent’. We investigate whether this ‘persistence’ is due to structural breaks or long memory, and the extent of asymmetric responses of the rand to ‘good news’ and ‘bad news’.
This paper investigates the determinants of exchange rate volatility in South Africa for the period 1986-2013 using the New Open Economy Macroeconomics model by Obstfeld & Rogoff (1996) and Hau (2002). The main focus of the paper is to test the hypothesis that economic openness decreases Rand (ZAR) volatility. This follows South Africa's liberalisation of its capital account in the mid-1990s and the mixed results in the literature on the relationship between exchange rate volatility and economic openness. Employing monthly time series data, GARCH models are estimated.
The purpose of this paper is to foresee the likely developmental impact of the proposed institutionalisation of derivatives trading in sub-Saharan Africa(n) (SSA) countries. The case of South Africa is emphasised to illustrate how domestic derivatives trading could influence economic growth and economic growth volatility; measuring growth in real GDP. From an empirical standpoint, the influence of local derivatives activity on economic growth could not be proven, even though a long-run Granger causality is reported from economic growth to the expansion of local derivatives.
This paper examines whether accounting for structural changes in the conditional variance process, through the use of Markov-switching models, improves estimates and forecasts of stock return volatility over those of the more conventional single-state (G)ARCH models, within and across selected African markets for the period 2002-2012. In the univariate portion of the paper, the performances of various Markov-switching models are tested against a single-state benchmark model through the use of in-sample goodness-of-fit and predictive ability measures.
This paper analyses how systematic risk emanating from the macro-economy is transmitted into stock market volatility using augmented autoregressive GARCH (AR-GARCH) and Vector autoregression models. Also examined is whether the relationship between the two is bidirectional. By imposing dummies for the 1997-98 Asian and the 2007-2008 sub-prime financial crises, the study further analyses whether financial crises affect the relationship between macroeconomic uncertainty and stock market volatility.