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author:

Wu, Xiaoyan (Wu, Xiaoyan.) [1] | Zhuang, Ying (Zhuang, Ying.) [2] | Chen, Fei (Chen, Fei.) [3] (Scholars:陈飞) | Wang, Meiqing (Wang, Meiqing.) [4] (Scholars:王美清)

Indexed by:

EI Scopus

Abstract:

Modeling the implied volatility has received extensive attention, as the implied volatility is an important parameter in option pricing. Usually the implied volatility can be approximated by fitting a polynomial about the strike and the maturity or by stochastic methods. In this article, a Gaussian semi-parametric model is proposed based on the quadratic polynomial semi-parametric model suggested by Borovkova. In the new model, the Gaussian function is used to construct a smooth term substituting the quadratic term in the polynomial model, and the arbitrage-free constraints are used to calibrate the model. The empirical tests show that the Gaussian semi-parametric model has a better performance in fitting and forecasting. © The Author(s) 2017.

Keyword:

Economics Gaussian distribution Polynomials Stochastic systems

Community:

  • [ 1 ] [Wu, Xiaoyan]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 2 ] [Zhuang, Ying]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 3 ] [Chen, Fei]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 4 ] [Wang, Meiqing]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • 王美清

    [wang, meiqing]college of mathematics and computer science, fuzhou university, fuzhou, china

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Source :

Journal of Algorithms and Computational Technology

ISSN: 1748-3018

Year: 2017

Issue: 3

Volume: 11

Page: 246-260

0 . 8 0 0

JCR@2023

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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