QUANTITATIVE FINANCE

The main goals of this Programme are to disseminate research studies that challenge classical assumptions in finance and provide practice guidance on quantitative finance and various long-term quantitative investment strategies within South Africa and beyond. Its target members range from academic researchers to industry practitioners with a keen interest in applying quantitative methods in finance.

The Programme’s scientific orientation is towards financial risk management, with high priority given to industry-relevant research. The Programme aims to contribute to a better general understanding of the mathematical approach to quantitative finance and risk management, a topic with a significant social importance. One of the main focuses is to engage in more interdisciplinary research. One such area is a quantitative study of Sustainable Investment Policies, for example, investment policies that consider Environmental Societal Governance (ESG) criteria, and price ESG-linked financial derivatives.

Moreover, the Programme seeks to have a broad spectrum of research streams, such as modelling of new risks phenomena and new markets (electricity markets, emissions trading, liquidity risk modelling, and quantifying model risk). It is supported by cutting edge tools of mathematical finance, statistical and computational finance (e.g., optimisation methods, financial econometrics, machine learning and parallel computing).

From 2023:

• Dr Mesias Alfeus (PI) (Stellenbosch University)
• Prof Daniel Polakow (Stellenbosch University)
• Prof Conrad Beyers (University of Pretoria)
• Prof Riaan de Jongh (North-West University)
• Prof Michael Graham (Stellenbosch University)
• Dr Chioma Okoro (University of Johannesburg)
• Prof Helgard Raubenheimer (North-West University)
• Prof Ronald Richman (Old Mutual Insure)
• Prof Willem Schutte (North-West University)
• Prof David Taylor (University of Cape Town)
• Prof Tanja Verster (North-West University)

PI – Principal investigator (programme manager) 

‘The Changing Landscape of Financial Credit Risk Models’ by Tanja Verster and Erika Fourie in International Journal of Financial Studies.

‘A Forward-Looking IFRS 9 Methodology, Focussing on the Incorporation of Macroeconomic and Macroprudential Information into Expected Credit Loss Calculation’ by Douw Gerbrand Breed, Jacques Hurter, Mercy Marimo, Matheba Raletjene, Helgard Raubenheimer, Vibhu Tomar and Tanja Verster in Risks.

‘Enhancing classification performance in imbalanced datasets: A comparative analysis of machine learning models’ by Lindani Dube and Tanja Verster in Data Science in Finance and Economics.

‘Stochastic Default Risk Estimation Evidence from the South African Financial Market’ by Mesias Alfeus, Kirsty Fitzhenry and Alessia Lederer in Computational Economics.

‘Implied Roughness in the Term Structure of Oil Markets Volatility’ by Mesias Alfeus, Christina S. Nikitopoulos, Ludger Overbeck in Quantitative Finance.

‘Roll-Over Risk: New Evidence from an Emerging Market‘ by Alfeus, M.

‘Pricing and Hedging of Futures Contracts on Renewables’ by Alfeus, M., Nikitopoulos, C. and Overbeck, L.

‘Pricing of Asian Options via Variance Reduction Methods’ by Alfeus, M. and Harvey, J.

‘Wind Energy Derivatives: Modelling for Risk Management and Investment’ by Dr Mesias Alfeus, Assoc. Prof Christina Nikitopoulos, Prof Ludger Overbeck, Dr Muthe Mwampashi and Theo Fischer.

‘Modelling the rand-dollar exchange rate in the case of sovereign default’ by Alexis Levendis and Mesias Alfeus.

‘Completing and stressing implied Volatility Surfaces using Variational Autoencoder(VAE)’ by Dr Hermann Azemtsa Donfack, Prof Celestin Wafo Soh and Mr B. F. Nteumagne.

‘Cheers to Enhanced Portfolio Performance: Wine as a Unique Asset Class’ by Mesias Alfeus, Anton Blignaut, Jean-Pierre Viljoen, and Roland Peens.