Portfolio Optimisation: Basics and Advances in Continuous-Time Model and Discrete-Time Models May 30, 2012

Financial Planning problems are eminently suited for analysis using the efficient risk & return frontiers. There are in general two schools of modellers who practice Portfolio analytics.(i) continuous time finance specialists and (ii) those specialising in the application of discrete optimisation techniques to portfolio models. In this workshop both these modelling approaches are covered in depth. The continuous time specialists use stochastic differential equations and martingale theory; the applications focus mainly on optimal investment with derivatives, and take into consideration stochastic interest rates, as well as suitable benchmarks. The class of discrete models emanating from Markowitz’s classical Mean-Variance approach are successfully processed as quadratic optimisation problems. Rather belatedly quadratic programs in the form of mean-variance analysis have become the tool of choice when it comes to financial planning, be it portfolio selection, asset liability management models, or index tracking. Further, integer quadratic optimisation is one of the most valuable extensions that make the portfolio selection realistic and applicable by introducing threshold values, numbers to be chosen, and transaction costs. This special two-day course is designed to successfully demonstrate and transfer the skills needed for developing these two classes of portfolio problems.