Two Way Parallel Calibration of the Garch (1,1) Model in CUDA

This article demonstrates the use of two approaches to parallelizing a Garch(1,1) calibration algorithm. The base serial implementation is a genetic algorithm that uses maximum likelihood in the fitness function. This is written in generic C. The first type of parallelization involves calculating all the fitness functions of the population in parallel. The second type of parallelization involves parallelizing the fitness function itself. The parallel algorithms are developed in nVIDIA CUDA and run on a GPU architecture

Year of publication:	2011
Authors:	Pearce, Barry
Publisher:	[S.l.] : SSRN
Subject:	Schätztheorie \| Estimation theory \| ARCH-Modell \| ARCH model

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