Bi-cubic B-spline fitting-based local volatility model with mean reversion process
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 119-132 |
Journal / Publication | Journal of Systems Science and Complexity |
Volume | 29 |
Issue number | 1 |
Publication status | Published - 1 Feb 2016 |
Link(s)
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.
In: Journal of Systems Science and Complexity, Vol. 29, No. 1, 01.02.2016, p. 119-132.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review