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Valorisation d’options américaines et Value At Risk de portefeuille sur cluster de GPUs/CPUs hétérogène

Michaël Benguigui 1
1 SCALE - Safe Composition of Autonomous applications with Large-SCALE Execution environment
Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
Abstract : The research work described in this thesis aims at speeding up the pricing of complex financial instruments, like an American option on a realistic size basket of assets (e.g. 40) by leveraging the parallel processing power of Graphics Processing Units. To this aim, we start from a previous research work that distributed the pricing algorithm based on Monte Carlo simulation and machine learning proposed by J. Picazo. We propose an adaptation of this distributed algorithm to take advantage of a single GPU. This allows us to get performances using one single GPU comparable to those measured using a 64 cores cluster for pricing a 40-assets basket American option. Still, on this realistic-size option, the pricing requires a handful of hours. Then we extend this first contribution in order to tackle a cluster of heterogeneous devices, both GPUs and CPUs programmed in OpenCL, at once. Doing this, we are able to drastically accelerate the option pricing time, even if the various classification methods we experiment with (AdaBoost, SVM) constitute a performance bottleneck. So, we consider instead an alternate, distributable approach, based upon Random Forests which allow our approach to become more scalable. The last part reuses these two contributions to tackle the Value at Risk evaluation of a complete portfolio of financial instruments, on a heterogeneous cluster of GPUs and CPUs.
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Submitted on : Thursday, September 24, 2015 - 11:10:57 AM
Last modification on : Tuesday, January 12, 2021 - 8:44:01 AM
Long-term archiving on: : Tuesday, December 29, 2015 - 9:44:40 AM


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  • HAL Id : tel-01204580, version 1



Michaël Benguigui. Valorisation d’options américaines et Value At Risk de portefeuille sur cluster de GPUs/CPUs hétérogène. Autre [cs.OH]. Université Nice Sophia Antipolis, 2015. Français. ⟨NNT : 2015NICE4053⟩. ⟨tel-01204580⟩



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