Parallel Approach to Monte Carlo Simulation for Option Price Sensitivities Using the Adjoint and Interval Analysis

被引：1

作者：

Kozikowski, Grzegorz ^{[1
]}

Kubica, Bartlomiej Jacek ^{[1
]}

机构：

[1] Univ Manchester, Sch Comp Sci, Manchester, Lancs, England

来源：

PARALLEL PROCESSING AND APPLIED MATHEMATICS (PPAM 2013), PT II | 2014年 / 8385卷

关键词：

Option pricing; The greeks; Automatic Differentiation; The Adjoint; Calibration; Interval analysis; CUDA;

D O I：

10.1007/978-3-642-55195-6_57

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper concerns a new approach to evaluation of Option Price sensitivities using the Monte Carlo simulation, based on the parallel GPU architecture and Automatic Differentiation methods. In order to study rounding errors, the interval arithmetic is used. Considerations are based on two implementations of the algorithm - the sequential and parallel ones. For efficient differentiation, the Adjoint method is employed. Computational experiments include analysis of performance, uncertainty error and rounding error and consider Black-Scholes and Heston models.

引用

页码：600 / 612

页数：13

共 11 条

[1] [Anonymous], 2011, Options, Futures, and Other Derivatives
[2] Beck PD, 2013, LECT NOTES COMPUT SC, V7782, P454, DOI 10.1007/978-3-642-36803-5_34
[3] Bucker M., 1981, AUTOMATIC DIFFERENTI
[4] Kozikowski G., 2013, THESIS WUT
[5] Kozikowski G., 2011, THESIS WUT
[6] Kozikowski G, 2013, LECT NOTES COMPUT SC, V7782, P489, DOI 10.1007/978-3-642-36803-5_37
[7] A class of problems that can be solved using interval algorithms
Kubica, Bartlomiej Jacek
[J]. COMPUTING, 2012, 94 (2-4) : 271 - 280
[8] Nvidia, CUDA SDK DOC
[9] Rouah F. D., EULER MILSTEIN DISCR
[10] An Option Pricing Model Calibration Using Algorithmic Differentiation
Tadjouddine, Emmanuel M.
Cao, Yi
[J]. COMPUTER AND INFORMATION SCIENCES II, 2012, : 577 - 581

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