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Details of Grant 

EPSRC Reference: GR/R01484/01
Title: Domain Specific Parallel Programming For Real Time Contingent Claim Modelling
Principal Investigator: Guo, Professor Y
Other Investigators:
Rustem, Professor B Darlington, Professor J
Researcher Co-Investigators:
Project Partners:
Department: Computing
Organisation: Imperial College London
Scheme: Standard Research (Pre-FEC)
Starts: 01 September 2000 Ends: 30 April 2003 Value (£): 235,704
EPSRC Research Topic Classifications:
Parallel Computing
EPSRC Industrial Sector Classifications:
Financial Services Pharmaceuticals and Biotechnology
Energy
Related Grants:
Panel History:  
Summary on Grant Application Form
This project aims to develop a domain specific parallel programming system for Contingent Claims Modelling (CCM). CCM is the use of methods from stochastic mathematics to value investment projects whose value is contingent on the uncertain future state of the world. It is one of the most general and sophisticated valuation methods applicable to investment projects.There are, however, significant technical and practical challenges to the computer implementation of this methodology. The algorithms required to analyse the models are very computationally intensive. Moreover implementations must change dynamically as the underlying scenario evolves. Auditing and validation of models and software are essential, but notoriously difficult when programs are hand coded and dynamically updated.We aim to facilitate rapid development of transparent CCM programs using advanced hardware, algorithms and software techniques. This will be achieved by allowing users to specify models naturally at the mathematical level, and by using symbolic rewrite rules and algorithm template technology to automatically construct solution code. The project applies the successful research on generic co-ordination forms for parallel application construction to this specific application domain, and in doing so will develop new software methods and algorithms.
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Organisation Website: http://www.imperial.ac.uk