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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.
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Journal of Algorithms and Computational Technology
ISSN: 1748-3018
Year: 2017
Issue: 3
Volume: 11
Page: 246-260
0 . 8 0 0
JCR@2023
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WoS CC Cited Count: 0
SCOPUS Cited Count: 3
ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 0
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