Fractional stochastic volatility correction to CEV implied volatility

Hyun Gyoon Kim; Se Jin Kwon; Jeong Hoon Kim

doi:10.1080/14697688.2020.1812703

Fractional stochastic volatility correction to CEV implied volatility

Hyun Gyoon Kim, Se Jin Kwon, Jeong Hoon Kim

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Recent ground-breaking work shows that stochastic volatility models driven by fractional Brownian motion with short memory provide better calibration of the volatility surface and more robust estimation of historical volatility. Based on the fractional nature of the volatility correlation, we choose two types of stochastic-local volatility built on the constant elasticity of variance model to calculate European option prices. Our analysis reveals how the associated implied volatility term structures are related to the elasticity factor and the Hurst exponent as well as the underlying value.

Original language	English
Pages (from-to)	565-574
Number of pages	10
Journal	Quantitative Finance
Volume	21
Issue number	4
DOIs	https://doi.org/10.1080/14697688.2020.1812703
Publication status	Published - 2021

Bibliographical note

Funding Information:
The research of J.-H. Kim was supported by the National Research Foundation of Korea [grant number NRF-2020R1H1A2006105]. The research of H.-G. Kim was partially supported by the Graduate School of Yonsei University Research Scholarship Grants in 2020. The authors are grateful for helpful comments and constructive suggestions from anonymous referees to enhance the contributions of this paper.

Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

All Science Journal Classification (ASJC) codes

Finance
Economics, Econometrics and Finance(all)

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10.1080/14697688.2020.1812703

Cite this

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title = "Fractional stochastic volatility correction to CEV implied volatility",

abstract = "Recent ground-breaking work shows that stochastic volatility models driven by fractional Brownian motion with short memory provide better calibration of the volatility surface and more robust estimation of historical volatility. Based on the fractional nature of the volatility correlation, we choose two types of stochastic-local volatility built on the constant elasticity of variance model to calculate European option prices. Our analysis reveals how the associated implied volatility term structures are related to the elasticity factor and the Hurst exponent as well as the underlying value.",

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N2 - Recent ground-breaking work shows that stochastic volatility models driven by fractional Brownian motion with short memory provide better calibration of the volatility surface and more robust estimation of historical volatility. Based on the fractional nature of the volatility correlation, we choose two types of stochastic-local volatility built on the constant elasticity of variance model to calculate European option prices. Our analysis reveals how the associated implied volatility term structures are related to the elasticity factor and the Hurst exponent as well as the underlying value.

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Fractional stochastic volatility correction to CEV implied volatility

Abstract

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