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.
This paper highlights the shortfalls of Modern Portfolio Theory (MPT). Amongst other flaws, MPT assumes that returns are normally distributed; that correlations are linear; and that risks are symmetrical. We propose a dynamic and flexible scenario-based approach to portfolio selection that incorporates an investor’s economic forecast.
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.