A parallel Particle swarm optimization algorithm for option pricing

Abstract

Financial derivatives play significant role in an investor's success. Financial option is one form of derivatives. Option pricing is one of the challenging and fundamental problems of computational finance. Due to highly volatile and dynamic market con- ii Abstract iii In this research, we have designed a sequential PSO based option pricing algorithm using basic principles of PSO. The algorithm is applicable for both European and American options, and handles both constant and variable volatility. We show that our results for European options compare well with Black-Scholes-Merton formula.Since it is very important and critical to lock-in profit making opportunities in the real market, we have also designed and developed parallel algorithm to expedite the computing process.We evaluate the performance of our algorithm on a cluster of multicore machines that supports three different architectures: shared memory, distributed memory, and a hybrid architectures. We conclude that for a shared memory architecture or a hybrid architecture, one-to-one mapping of particles to processors is recommended for performance speedup. We get a speedup of 20 on a cluster of four nodes with 8 dual-core processors per node.

Studies on migration strategies of multiple population parallel particle swarm optimization

“…On function 12 , One-To-Migrate-20 and One-To-Migrate-40 can find the minimum value, as well as migration strategies BW, 1.0651e+04 -1.0512e+04 -1.0120e+04 -9.6549e+03 -1.0826e+04 -1.0534e+04 -1.0799e+04 -1.0008e+04 -1.0817e+04 -1.0157e+04 -1.0922e+04 -9.3233e+03 5 7.0694e-34 7.8369e-21 1.1260e-05 1.6914e-01 8.5002e-40 6.0438e-34 1.3171-23 2.2254e-19 1.6692e-32 5.0309e-10 7.5524e-25 1.3539e-05 6 7.9208e-55 4.6283e-31 9.8792e-12 3.9488e-06 1.5237e-79 1.9355e-61 1.6513e-30 9.0957e-28 8.3741e-63 8.8394e-24 3.7827e-41 9.1314e-15 7 10 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0. 1.5704e-32 1.5704e-32 4.5439e-21 1.0901e-13 1.5704e-32 2.8854e-23 1.5704e-32 1.5259e-17 1.5704e-32 2.7009e-23 1.5704e-32 RW, BWM and RRM. On function 11 , the result of migration strategy BR is the best one.…”

“…Prasain et al used PPSO to solve optimal pricing problem [7]. Jeong et al used PPSO for searching the optimal solution to the state estimation problem in power system [8].…”

Implementasi Paralel PSO dalam Melatih JST untuk Memprediksi Ketinggian Gelombang Laut

“…Salah satu cara mempercepat pemrosesan data yang banyak adalah dengan membagi data tersebut menjadi sub-sub bagian dan memprosesnya secara paralel. Beberapa penelitian melakukan paralelisasi algoritma PSO seperti pada penelitian [8] dan [9]. Pada penelitian-penelitian tersebut belum ada yang mengimplementasikan paralelisasi PSO dalam melatih JST untuk melakukan prediksi ketinggian gelombang.…”

Parallel Binomial American Option Pricing under Proportional Transaction Costs

“…The algorithms were implemented on an NVIDIA GeGorce 9800 GX2 video card with only one of the two GPUs being used. Prasain et al [2010] proposed a parallel synchronous option pricing algorithm to price simple European options using particle swarm optimisation: a nature-inspired global search algorithm based on swarm intelligence. Sak et al [2007] discussed the application of parallel computing in pricing backward-starting fixed strike Asian options that are continuously averaged.…”