Team Tosca

Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Contracts and Grants with Industry

ANR GCPMF: Grille de Calcul pour les Mathématiques Financières

Participants : Mireille Bossy, Denis Talay.

We collaborate with the OASIS team within the ANR project entitled “GCPMF” funded by the ANR Research Program “Calcul Intensif et Grilles de Calcul 2005”.

The aim of this ANR program is to highlight the potential of parallel techniques applied to mathematical finance computing on Grid infrastructures. The consortium that conducts this project includes ten participants from academic laboratories in computer science and mathematics, banks, and IT companies.

Financial applications require to solve large size computations, that are so huge that they cannot be tackled by conventional PCs. A typical example addresses time-critical computations required during trading hours, in particular Monte Carlo simulations for option pricing and other derivative products.

A software system called PicsouGrid has been designed and implemented by the OASIS team, which utilizes the ProActive library to parallelize and distribute various option pricing algorithms. Currently, PicsouGrid has been deployed on various grid systems to evaluate its scalability and performance in European option pricing. We also developed several European option pricing algorithms such as standard, barrier, basket options to experiment in PicsouGrid. A part of this work was presented in [45] and [Oops!] .

In the second half of 2007, parallel versions of several American option pricing algorithms have been implemented (Longstaff and Schwartz, Ibanez and Zapatero, and Picazo), including those which price options on several assets simultaneously (called basket options). Our work has focused on finding efficient parallelization strategies which can be used for a range of pricing algorithms. The objective is to allow algorithm designers to focus on an efficient serial implementation without concern for the parallelization, and for the model to be used to automatically or semi-automatically provide a load-balanced (for heterogeneous compute resources) parallel implementation. The extended abstract of this work can be found in [Oops!] .


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