Option Pricing with Model-Guided Nonparametric Methods

55 Pages Posted: 20 Feb 2007 Last revised: 13 Feb 2009

See all articles by Jianqing Fan

Jianqing Fan

Princeton University - Bendheim Center for Finance

Loriano Mancini

USI Lugano - Institute of Finance; Swiss Finance Institute

Date Written: February 9, 2009

Abstract

Parametric option pricing models are largely used in Finance. These models capture several features of asset price dynamics. However, their pricing performance can be significantly enhanced when they are combined with nonparametric learning approaches that learn and correct empirically the pricing errors. In this paper, we propose a new nonparametric method for pricing derivatives assets. Our method relies on the state price distribution instead of the state price density because the former is easier to estimate nonparametrically than the latter. A parametric model is used as an initial estimate of the state price distribution. Then the pricing errors induced by the parametric model are fitted nonparametrically. This model-guided method estimates the state price distribution nonparametrically and is called Automatic Correction of Errors (ACE). The method is easy to implement and can be combined with any model-based pricing formula to correct the systematic biases of pricing errors. We also develop a nonparametric test based on the generalized likelihood ratio to document the efficacy of the ACE method. Empirical studies based on S&P 500 index options show that our method outperforms several competing pricing models in terms of predictive and hedging abilities.

Keywords: Nonparametric regression, state price distribution, model misspecification, out-of-sample analysis, generalized likelihood ratio test

JEL Classification: C14, G13

Suggested Citation

Fan, Jianqing and Mancini, Loriano, Option Pricing with Model-Guided Nonparametric Methods (February 9, 2009). Available at SSRN: https://ssrn.com/abstract=955740 or http://dx.doi.org/10.2139/ssrn.955740

Jianqing Fan

Princeton University - Bendheim Center for Finance ( email )

26 Prospect Avenue
Princeton, NJ 08540
United States
609-258-7924 (Phone)
609-258-8551 (Fax)

HOME PAGE: http://orfe.princeton.edu/~jqfan/

Loriano Mancini (Contact Author)

USI Lugano - Institute of Finance ( email )

Via Giuseppe Buffi 6
6904 Lugano, CH-6904
Switzerland
+41 (0)91 912 46 47 (Fax)

HOME PAGE: http://www.people.usi.ch/mancil/

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

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