EFFICIENT MONTE CARLO SIMULATION OF SECURITY PRICES
成果类型：
Article
署名作者：
Duffie, Darrell; Glynn, Peter
署名单位：
Stanford University; Stanford University
刊物名称：
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN：
1050-5164
DOI：
10.1214/aoap/1177004598
发表日期：
1995
页码：
897-905
关键词：
摘要：
This paper provides an asymptotically efficient algorithm for the allocation of computing resources to the problem of Monte Carlo integration of continuous-time security prices. The tradeoff between increasing the number of time intervals per unit of time and increasing the number of simulations, given a limited budget of computer time, is resolved for first-order discretization schemes (such as Euler) as well as second- and higher-order schemes (such as those of Milshtein or Talay).
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