Bi-cubic B-spline fitting-based local volatility model with mean reversion process

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Scopus Citations
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Author(s)

  • Shifei Zhou
  • Hao Wang
  • Jerome Yen
  • Kin Keung Lai

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)119-132
Journal / PublicationJournal of Systems Science and Complexity
Volume29
Issue number1
Publication statusPublished - 1 Feb 2016

Abstract

This paper studies the traditional local volatility model and proposes: A novel local volatility model with mean-reversion process. The larger is the gap between local volatility and its mean level, the higher will be the rate at which local volatility will revert to the mean. Then, a B-spline method with proper knot control is applied to interpolate the local volatility matrix. The bi-cubic B-spline is used to recover the local volatility surface from this local volatility matrix. Finally, empirical tests show that the proposed mean-reversion local volatility model offers better prediction performance than the traditional local volatility model.

Research Area(s)

  • Bi-cubic B-spline, local volatility, mean reversion, surface fitting

Citation Format(s)

Bi-cubic B-spline fitting-based local volatility model with mean reversion process. / Zhou, Shifei; Wang, Hao; Yen, Jerome et al.
In: Journal of Systems Science and Complexity, Vol. 29, No. 1, 01.02.2016, p. 119-132.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review