Nonparametric estimates of pricing functionals
Carlo Marinelli and
Authors registered in the RePEc Author Service: Stefano d'Addona ()
Journal of Empirical Finance, 2017, vol. 44, issue C, 19-35
We analyze the empirical performance of several non-parametric estimators of the pricing functional for European options, using historical put and call prices on the S&P500 during the year 2012. Two main families of estimators are considered, obtained by estimating the pricing functional directly, and by estimating the (Black–Scholes) implied volatility surface, respectively. In each case simple estimators based on linear interpolation are constructed, as well as more sophisticated ones based on smoothing kernels, à la Nadaraya–Watson. The results based on the analysis of the empirical pricing errors in an extensive out-of-sample study indicate that a simple approach based on the Black–Scholes formula coupled with linear interpolation of the volatility surface outperforms, both in accuracy and computational speed, all other methods.
Keywords: Nadaraya–Watson estimator; Option pricing; Implied volatility estimators; Smoothing (search for similar items in EconPapers)
JEL-codes: G13 C14 C52 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:44:y:2017:i:c:p:19-35
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