Monte Carlo Simulation with Asymptotic Method

• Takahashi Akihiko

  Graduate Scool of Economics, The University of Tokyo

• Yoshida Nakahiro

  Graduate Scool of Mathematical Sciences, The University of Tokyo

Abstract

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.

Journal

• JOURNAL OF THE JAPAN STATISTICAL SOCIETY

  JOURNAL OF THE JAPAN STATISTICAL SOCIETY 35 (2), 171-203, 2005

  THE JAPAN STATISTICAL SOCIETY

Keywords

• asymptotic method
• average options
• derivatives
• finance
• Malliavin calculus
• Monte Carlo simulation
• optimal portfolio

Details

• CRID: 1390282680264501376
• NII Article ID: 110003495322
• NII Book ID: AA1105098X
• DOI: 10.14490/jjss.35.171
• ISSN: 13486365
• ISSN: 18822754
• NDL BIB ID: 7966697
• Web Site: http://id.ndl.go.jp/bib/7966697
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7966697
• Web Site: https://www.jstage.jst.go.jp/article/jjss/35/2/35_2_171/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed