A Computational Approach to Financial Option Pricing Using Quasi Monte Carlo Methods via Variance Reduction Techniques

DOI: 10.4236/jmf.2012.22021   PDF   HTML     4,374 Downloads   8,882 Views   Citations

Abstract

In this paper, we consider two types of pricing option in financial markets using quasi Monte Carlo algorithm with variance reduction procedures. We evaluate Asian-style and European-style options pricing based on Black-Scholes model. Finally, some numerical results presented.

Share and Cite:

F. Mehrdoust and K. Vajargah, "A Computational Approach to Financial Option Pricing Using Quasi Monte Carlo Methods via Variance Reduction Techniques," Journal of Mathematical Finance, Vol. 2 No. 2, 2012, pp. 195-198. doi: 10.4236/jmf.2012.22021.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] P. Glasserman, “Monte Carlo Methods in Financial Mathematics,” Springer-Verlag, New York, 2004.
[2] J. S. Dagpunar, “Simulation and Monte Carlo with Applications in Finance and MCMC,” John Wiley & Sons, New York, 2007.
[3] V. N. Alexandrov, C. G. Martel and J. Strabburg, “Monte Carlo Scalable Algorithms for Computational Finance,” Procedia Computer Science, Vol. 4, 2011, pp. 1798-1715. doi:10.1016/j.procs.2011.04.185
[4] L. Cao and Z. F. Gue, “A Comparison of Gradient Estimation Techniques for European Call Options,” Accounting & Taxation, Forthcoming, 2011.
[5] L. Cao and Z. F. Gue, “A Comparison of Delta Hedging under Two Price Distribution Assumptions by Likelihood Ratio,” International Journal of Business and Finance Research, Forthcoming, 2011.
[6] L. Cao and Z. F. Gue, “Delata Hedging with Deltas from a Geometric Brownian Mo-tion Process,” Proceeding Conference on Applied Financial Economic, Samos Island, March 2011.
[7] L. Cao and Z. F. Gue, “Applying Gradient Estimation Technique to Estimate Gradients of European Call Following Variance-Gamma,” Global Conference on Business and Finance Proceeding, Vol. 6, No. 2, 2011, pp. 12-18.
[8] M. Davis, “Mathematics of Financial Markets,” Supported by FWF, 2009.
[9] C. Lemieux, “Monte Carlo and Quasi Monte Carlo Sampling,” Springer Science, New York, 2009.
[10] B. Fathi Vajargah and F. Mehrdoust, A. Pourdarvish and F. Norouz, “Some New Advantages on Monte Carlo Integration Using Variance Reduction Procedures,” In-ternational Journal of Advanced Research in Computer Science, Vol. 1, No. 4, 2011.

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.