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Details of Grant 

EPSRC Reference: GR/M84282/01
Title: APPLICATION OF HPC TO RISK MANAGEMENT OF LARGE SCALE FINANCIAL PORTFOLIO OPTIMISATION PROBLEMS
Principal Investigator: Liddell, Professor H
Other Investigators:
Researcher Co-Investigators:
Project Partners:
A B N Amro Bank N V Numerical Algorithms Group Ltd
Department: Computer Science
Organisation: Queen Mary University of London
Scheme: Standard Research (Pre-FEC)
Starts: 01 July 1999 Ends: 30 June 2001 Value (£): 204,429
EPSRC Research Topic Classifications:
Parallel Computing
EPSRC Industrial Sector Classifications:
Financial Services
Related Grants:
Panel History:  
Summary on Grant Application Form
The proposed research concerns a specific example in the financial domain of a generic problem in non linear optimisation. A Portfolio Manager wants to choose portfolios with controlled risk. The choice of portfolio will depend on the Manger's assessment of the future performance of potential securities in changing European Market places. These assessments will vary, depending on certain major events such as the success or failure of the EURO. This project aims to develop a portfolio estimation tool which will allow the Manager to investigate portfolios with controlled risk across a set of different scenario.Non linear optimisation techniques with stochastic inputs in the value are used. These techniques lead to large scale Monte Carlo computations with a large number of independent iterations; this requires the use of HPC architectures and parallel processing techniques. Real market data will be used to study the scalability and stability of the solutions and thus help the understanding of the real issues that arise in obtaining convergence for such problems. We will also investigate the performance of the latest state-of-the-art non linear sparse solvers with automatic scaling when applied to these problems.
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