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  • 标题:Monte Carlo Simulation with Asymptotic Method
  • 本地全文:下载
  • 作者:Akihiko Takahashi ; Nakahiro Yoshida
  • 期刊名称:JOURNAL OF THE JAPAN STATISTICAL SOCIETY
  • 印刷版ISSN:1882-2754
  • 电子版ISSN:1348-6365
  • 出版年度:2005
  • 卷号:35
  • 期号:2
  • 页码:171-203
  • DOI:10.14490/jjss.35.171
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:We shall propose a new computational scheme with the asymptotic method to achieve variance reduction of Monte Carlo simulation for numerical analysis particularly for finance. We not only provide general scheme of our method, but also show its effectiveness through numerical examples such as computing optimal portfolio and pricing an average option. Finally, we show mathematical validity of our method.
  • 关键词:asymptotic method;average options;derivatives;finance;Malliavin calculus;Monte Carlo simulation;optimal portfolio
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