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Curve Fitting Method for Implied Volatility
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
Number of Authors: 22018 (English)In: Journal of Derivatives, ISSN 1074-1240, E-ISSN 2168-8524, Vol. 26, no 2, p. 19-37Article in journal (Refereed) Published
Abstract [en]

Curve-fitting methods are widely used in derivatives markets for construction of the implied volatility surface (IVS). Here we discuss the goodness of fit, smoothness, and economic implications of 12 distinctive curve-fitting methods. The choice of method relies on specific requirements. When fitting the Chicago Board Options Exchange data, three interpolation methods were found to provide the best goodness, whereas quadratic regression, the Nadaraya–Watson kernel regression, and the theoretical Carr–Wu model generate the smoothest surfaces. Because of the irregular nature of the emerging options market data, we propose a transformation method to improve three statistical methods to satisfy the Lee’s condition. Empirically, quadratic regression provides the best goodness when fitting the China 50ETF options data. In addition, the Carr–Wu model is a very good alternative because it natively satisfies the Lee’s condition and has economic implications.

Place, publisher, year, edition, pages
2018. Vol. 26, no 2, p. 19-37
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:su:diva-163598DOI: 10.3905/jod.2018.26.2.019ISI: 000451834800003OAI: oai:DiVA.org:su-163598DiVA, id: diva2:1277874
Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2019-01-11Bibliographically approved

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