PT - JOURNAL ARTICLE AU - Desheng Wu AU - Tianxiang Liu TI - Curve-Fitting Method for Implied Volatility AID - 10.3905/jod.2018.26.2.019 DP - 2018 Nov 30 TA - The Journal of Derivatives PG - 19--37 VI - 26 IP - 2 4099 - https://pm-research.com/content/26/2/19.short 4100 - https://pm-research.com/content/26/2/19.full AB - 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.TOPICS: Options, statistical methods, emerging, exchange-traded funds and applications