Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Application of quasi-Monte Carlo methods in multi-asset option pricing

준난수 몬테칼로 방법을 이용한 다중자산 옵션 가격의 추정

  • Mo, Eun Bi (Department of Statistics, Sungkyunkwan University) ;
  • Park, Chongsun (Department of Statistics, Sungkyunkwan University)
  • Received : 2013.05.03
  • Accepted : 2013.05.29
  • Published : 2013.07.31
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Abstract

Quasi-Monte Carlo method is known to have lower convergence rate than the standard Monte Carlo method. Quasi-Monte Carlo methods are using low discrepancy sequences as quasi-random numbers. They include Halton sequence, Faure sequence, and Sobol sequence. In this article, we compared standard Monte Carlo method, quasi-Monte Carlo methods and three scrambling methods of Owen, Faure-Tezuka, Owen-Faure-Tezuka in valuation of multi-asset European call option through simulations. Moro inversion method is used in generating random numbers from normal distribution. It has been shown that three scrambling methods are superior in estimating option prices regardless of the number of assets, volatility, and correlations between assets. However, there are no big differences between them.

본 연구에서는 다중자산 옵션 가격의 추정에 있어 자산의 수, 상관계수, 자산의 값들과 표준편차의 여러 조합에 대한 시뮬레이션을 통하여 저불일치 수열에 따르는 준난수 몬테칼로 방법들을 비교하였다. 결과적으로 준난수와 모로 역변환을 이용하는 것이 기본적인 몬테칼로 방법보다 정확하였으며 자산의 수와 관계없이 준난수 방법들 중 혼합법들이 더욱 효과적임을 알 수 있었다.

Keywords

References

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