Ammar Kherraz is a Visiting Lecturer, specialising in quantitative and computational finance and risk management.
Ammar has extensively worked in the quantitative and risk management field in the industry internationally – in investment banking and asset management.
The technical/quantitative end of his research interests has spanned multi-dimensional boundary crossing problems; efficient methods for capturing complex dependency/correlation structures; and investigating the performance of fully implicit vs. semi-implicit finite-difference schemes, depending on the profile of the instrument being priced / risk-managed. He has also worked on the development and testing of tools for counterparty risk solutions; different volatility modelling regimes to suit different derivatives types; and the theoretical and empirical analysis of various pricing and risk management models/methods for correlation dependent products.
Ammar's lecturing to MSc, MBA, PhD and executive education programmes - at several institutions - has spanned computational finance (with particular focus on the theory and application of various Monte Carlo and grid techniques), C++/VBA/MATLAB for finance, algorithmic trading, quantitative actuarial practice, stochastic calculus etc. He has also given talks on e.g. credit default swaps (CDS) and their use as hedging and speculative instruments; the currency options in relation to Scottish independence; a comparative analysis of the regulatory capital frameworks for banks and insurance companies; and the major anomalies and shortcomings of the mathematical models in finance, as highlighted by the financial crisis.
Outside of work, his interests include handball, the English countryside, and molecular genetics.