Journal of Mathematical Finance

Volume 3, Issue 4 (November 2013)

ISSN Print: 2162-2434   ISSN Online: 2162-2442

Google-based Impact Factor: 1.39  Citations  

Variance Reduction Techniques of Importance Sampling Monte Carlo Methods for Pricing Options

HTML  Download Download as PDF (Size: 230KB)  PP. 431-436  
DOI: 10.4236/jmf.2013.34045    7,756 Downloads   12,760 Views  Citations

ABSTRACT

In this paper we discuss the importance sampling Monte Carlo methods for pricing options. The classical importance sampling method is used to eliminate the variance caused by the linear part of the logarithmic function of payoff. The variance caused by the quadratic part is reduced by stratified sampling. We eliminate both kinds of variances just by importance sampling. The corresponding space for the eigenvalues of the Hessian matrix of the logarithmic function of payoff is enlarged. Computational Simulation shows the high efficiency of the new method.

Share and Cite:

Q. Zhao, G. Liu and G. Gu, "Variance Reduction Techniques of Importance Sampling Monte Carlo Methods for Pricing Options," Journal of Mathematical Finance, Vol. 3 No. 4, 2013, pp. 431-436. doi: 10.4236/jmf.2013.34045.

Cited by

[1] Denoised Monte Carlo for option pricing and Greeks estimation
arXiv preprint arXiv:2402.12528, 2024
[2] ÖNEM ÖRNEKLEMESİNİN BLACK SCHOLES OPSİYON FİYATLANDIRMA MODELİNE ETKİSİNİN İNCELENMESİ
Kapanaltı Dergisi, 2024
[3] EXCERPT
2022
[4] Evolution of risk assessment methods and the possibility of their use in determining the investment and construction projects' effectiveness
E3S Web of Conferences, 2021
[5] Assessment of socio-economic efficiency of investments in transport construction by Monte Carlo method including uncertainty/Оценка социально-экономической …
2019
[6] Оценка социально-экономической эффективности инвестиций в транспортное строительство с учетом неопределенности методом Монте-Карло
2019
[7] FireFly: A Bayesian Approach to Source Finding in Astronomical Data
2019
[8] Kolmogorov Backward Equations with Singular Diffusion Matrices
2019
[9] Тенденции развития теории оценки эффективности перспективных инвестиционно-строительных проектов в цифровой экономике
2019
[10] Assessment of socio-economic efficiency of investments in transport construction by Monte Carlo method including uncertainty
2019
[11] Bayesian Framework for Multi-Stage Transmission Expansion Planning Under Uncertainty via Emulation
2018
[12] Transfer learning for actor-critic methods in Lipschitz Markov decision processes
2017
[13] Variance reduced Monte-Carlo Simulations of Stochastic Differential Equations
Dissertation, 2017
[14] Solution of Multidimensional Integration using Adaptive Monte Carlo Method with General Division Approach and its Validation
2017
[15] Monte Carlo Methods in Finance
2016
[16] A joint application of the put-call-parity and importance sampling to variance reduced option pricing
2016
[17] Pricing 50ETF in the Way of American Options Based on Least Squares Monte Carlo Simulation
2016
[18] Improved Variance Reduced Monte-Carlo Simulation of in-the-Money Options
2016
[19] An application of the put-call-parity to variance reduced Monte-Carlo option pricing
2016
[20] Approximations of option price elasticities for importance sampling
2016
[21] Assessing the credit risk of money market funds during the eurozone crisis
Journal of Financial Stability, 2015

Copyright © 2025 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.