Abstract
Computational requirements for solving models of financial derivatives, for example, the option pricing problems, are huge and demand efficient algorithms and high performance computing capabilities. This demand has been rekindled by the recent developments in the mobile technology making wireless trading a possibility. In this paper, we focus on the development of a Monte-Carlo algorithm on a modern multi-core chip architecture, Cyclops-64 (C64) under development at IBM as the experimental platform for our study in pricing options. The timing results on C64 show that various sets of simulations could be done in a real-time fashion while yielding high performance/price improvement over traditional microprocessors for finance applications.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kontoghiorghes, E.J., Nagurnec, A., Rustem, B.: Parallel Computing in Economics, Finance and Decision-making. Parallel Computing 26, 207–509 (2000)
Rahmayil, S., Shiller, I., Thulasiram, R.K.: Different Estimators of the Underlying Asset’s Volatility and Option Pricing Errors: Parallel Monte Carlo Simulation. In: Proc. Intl. Conf. on Computational Finance and its Applications, Bologna, Italy, April 2004, pp. 121–131 (2004)
Chen, G., Thulasiram, R.K., Thulasiraman, P.: Distributed Adaptive Quasi-Monte Carlo Algorithm for Option Pricing on HNOWs Using mpC. In: Proc. 9th Annual Simulation Sympoisum, Huntsville, AL, April 2006, pp. 90–97 (2006)
Kola, K.: WAMAN:Web-mining-Assisted Mobile-computing-enAbled on-line optioN pricing- a software architecture towards autonomic computing. Master’s thesis, Department of Computer Science, The University of Manitoba, Winnipeg, MB, Canada (May 2006)
Kargupta, H., Park, B., Pittie, S., Liu, L., Kushraj, D., Sarkar, K.: Mobimine: Monitoring the stock market from a pda. SIGKDD EXplorer 3, 37–46 (2002)
Varshney, U., Vetter, R.J.: Mobile commerce:framework, applications and networking support. MONET 7, 3–4 (2002)
Hull, J.C.: Options, Futures and Other Derivatives, 5th edn. Prentice-Hall, Upper Saddle River (2002)
Black, F., Scholes, M.: The pricing of options and corporate liabilities. J.Political Economy 81, 637–654 (1973)
Clark, I.J.: Option Pricing Algorithms for the Cray T3D Supercomputer. In: Proceedings of the first National Conference on Computational and Quantitative Finance (September 1998)
Thulasiram, R.K., Litov, L., Nojumi, H., Downing, C.T., Gao, G.R.: Multithreaded Algorithms for Pricing a Class of Complex Options. In: Proc. Intl. Parallel and Distributed Processing Symp (IPDPS 2001), San Francisco, CA (April 2001)
Cox, J.C., Ross, S.A., Rubinstein, M.: Option pricing: A simplified approach. J. Financial Economics 7, 229–263 (1979)
Carr, P., Madan, D.B.: Option Valuation using the Fast Fourier Transform. The Journal of Computational Finance 2(4), 61–73 (1999)
Barua, S., Thulasiram, R.K., Thulasiraman, P.: High Performance Computing for a Financial Application Using Fast Fourier Transform. In: Cunha, J.C., Medeiros, P.D. (eds.) Euro-Par 2005. LNCS, vol. 3648, pp. 1246–1253. Springer, Heidelberg (2005)
Mayo, A.: Fourth Order Accurate Implicit Finite Difference Method for Evaluating American Options. In: Proc. Intl. Conf. on Computational Finance 2000, London, England (June 2000)
Thulasiram, R.K., Zhen, C., Chhabra, A., Thulasiraman, P., Gumel, A.: A second order l0 stable algorithm for evaluating european options. In: Intl. Journal of High Performance Computing and Networking (in press, 2006)
Srinivasan, A.: Parallel an Distributed Computing Issues in Pricing Financial Derivatives through Quasi Monte Carlo. In: Proc. Intl. Parallel and Distributed Processing Symp (IPDPS 2002), Fort Lauderdale, FL (April 2002)
Chesney, M., Scott, L.: Pricing European Currency Options: A Comparision of the Modified Black-Scholes and a Random Variance Model. Journal of Financial and Quantitative Analysis 24, 267–284 (1989)
del Cuvillo, J., Zhu, W., Hu, Z., Gao, G.R.: FAST: A functionally accurate simulation toolset for the Cyclops64 cellular architecture. In: Workshop on Modeling, Benchmarking, and Simulation (MoBS 2005), Madison, WI (June 2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhu, W., Thulasiraman, P., Thulasiram, R.K., Gao, G.R. (2006). Exploring Financial Applications on Many-Core-on-a-Chip Architecture: A First Experiment. In: Min, G., Di Martino, B., Yang, L.T., Guo, M., Rünger, G. (eds) Frontiers of High Performance Computing and Networking – ISPA 2006 Workshops. ISPA 2006. Lecture Notes in Computer Science, vol 4331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11942634_24
Download citation
DOI: https://doi.org/10.1007/11942634_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49860-5
Online ISBN: 978-3-540-49862-9
eBook Packages: Computer ScienceComputer Science (R0)