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EVENT: Quantitative Models: Taking Research Results into Real World Financial Applications 24 June 2004, London PRICE: GPB 195 industry and GBP 125 academic FURTHER INFORMATION: Please reply to this message or call Alec McCutcheon or Chris Veniopoulos on +44 (0) 1895 256 484. BENEFITS OF ATTENDING: This one-day briefing brings you the work of five outstanding researchers from industry and academia, who have wide experience of real world applications of quantitative models. While most of the research results have been created in an academic context, the models and software systems have been taken across and applied to the finance industry. You will gain first hand experience of the innovative thinking and best practices currently being developed at Stanford, University of Tennessee, CARISMA and other institutions, complemented by user experiences at UBS. PROGRAMME: Introduction and Scene Setting Gautam Mitra, CARISMA (The Centre for the Analysis of Risk and Optimisation Modelling Application), Brunel University, UK Combining Markowitz and Assymetric Risk Measures: New directions in Portfolio Planning Gautam Mitra, CARISMA, UK The use of higher moments, downside risk, Value at Risk (VaR) and Conditional Value at Risk (CvaR) are becoming increasingly important measures of Portfolio Planning. In this talk some research results will be summarized. This will be followed by a critique of rolling Markowitz and rebalancing approach. The role of a scenario-based approach in a temporal setting will be considered. Dynamic Asset Allocation for Individuals and Institutions - A Web Based Software Application for Asset Managers and Financial Advisors Gerd Infanger, Infanger Investment Technology, LLC and Stanford University, USA . Asset allocation and its dynamic aspects . Advantages and risks of implementing dynamic asset allocation strategies . WealthiOR(tm) software demonstration . How quantitative tools can help facilitate superior investment advice Portfolio Optimisation in Practice David Jessop, UBS Ltd, UK . A short outline of the problem . A comparison of different commercial optimisers . Optimisation isn't an exact science . Dealing with estimation errors . Problems still to solve Integrated Risk Management using Multistage Stochastic Portfolio Optimization: The case of MiSOFT Chanaka Edirisinghe, University of Tennessee, USA . Static and dynamic risk control with exogenous/endogenous wealth targets . Portfolio rebalancing with leverage, fix-mix and other policy constraints . Drawdown control and market neutrality integrated rebalancing . Multiperiod look-ahead trading with multistage stochastic optimization models, solution complexities . Rate of return scenario samples adapted to short-term market evolution Modelling Asset Price Changes Using Extreme Value Theory John James, Insightful, UK Asset prices changes consist of many small changes and a few very large ones. This leads to various problems when using asset price changes to create a useful Value at Risk (VaR) model. The issue is at which level to separate the largest price changes from the smaller ones since these lead to a disproportionate effect on the VaR number. This talk will illustrate how to separate and then model the changes using advanced statistics in the software package S-PLUS. CONTACT: Alec McCutcheon UNICOM UNICOM R&D House One Oxford Road Uxbridge UB9 4DA Direct: +44 (0) 1895 819 475 Swbd: +44 (0) 1895 256 484 Fax: +44 (0) 1895 813 095 www.unicom.co.uk