STA5086Z - Advanced Portfolio Theory
15 credits at NQF level 9
Entry Requirements:
Acceptance into Master’s programs in Advanced Analytics or Data Science, and/or statistical background deemed sufficient by the Head of Department.
Course Outline:
The course Advanced Portfolio Theory is intended to expose students to the more advanced topics in portfolio theory, portfolio management and risk management. Statistical techniques such as optimisation, simulation, spectral decomposition of the covariance matrix and robust optimisation are some of the techniques that will be utilised in the models. Notwithstanding the emphasis in this course is on the practical application of the models and theories. There will thus be an emphasis on the qualification of these measures and parameterisation of models in a South African (and African) setting. Furthermore there will be a focus on the interpretation and linkages between the concepts. Topics covered include: Interest rates;Equity evaluation; Portfolio risk components; risk in thinly-traded environments- the SA and African case; Advanced risk measures; systematic risk; eigenvectors; tail risk measures. Active management and the Generalised Fundamental Law. Absolute and Active Portfolio optimisation; the Black-Litterman Model; the Qualitative Model, Non-parametric Models, Robust Portfolio optimisation models including Bayesian shrinkage. Rebalancing of portfolios. Advanced performance measures. Asset pricing models. The course may not be offered every year.