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.
Marinelli, C., & D'Addona, S. (2017). Nonparametric estimates of pricing functionals. JOURNAL OF EMPIRICAL FINANCE, 44, 19-35 [10.1016/j.jempfin.2017.07.005].
|Titolo:||Nonparametric estimates of pricing functionals|
|Data di pubblicazione:||2017|
|Citazione:||Marinelli, C., & D'Addona, S. (2017). Nonparametric estimates of pricing functionals. JOURNAL OF EMPIRICAL FINANCE, 44, 19-35 [10.1016/j.jempfin.2017.07.005].|
|Appare nelle tipologie:||1.1 Articolo in rivista|