Parameterization based on randomized quasi-Monte Carlo methods

被引：10
|
作者：
Okten, Giray [1 ]
Willyard, Matthew [1 ]
机构：
[1] Florida State Univ, Dept Math, Tallahassee, FL 32306 USA
来源：
PARALLEL COMPUTING | 2010年 / 36卷 / 07期
关键词：
Parameterization; Randomized quasi-Monte Carlo; Option pricing; LOW-DISCREPANCY SEQUENCES; MULTIPLE INTEGRATION; DERIVATIVES; GENERATION; QUADRATURE; ALGORITHM; VARIANCE;
D O I：
10.1016/j.parco.2010.03.003
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We present a theoretical framework where any randomized quasi-Monte Carlo method can be viewed and analyzed as a parameterization method for parallel quasi-Monte Carlo. We present deterministic and stochastic error bounds when different processors of the computing environment run at different speeds. We implement two parameterization methods, both based on randomized quasi-Monte Carlo, and apply them to pricing digital options and collateralized mortgage obligations. Numerical results are used to compare the parameterization methods by their parallel performance as well as their Monte Carlo efficiency. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：415 / 422
页数：8
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