Estimating Option Implied Risk Neutral Densities: A Novel Parametric Approach (Preprint)

Posted: 20 May 2019

See all articles by Greg Orosi

Greg Orosi

American University of Sharjah

Date Written: July 26, 2013

Abstract

In this paper, we propose a novel parametric approach to extract the implied risk-neutral density function from a cross-section of call option prices. The method is based on the framework proposed by Orosi (2011), who presents a multi-parameter extension of the models of Figlewski (2002) and Henderson, Hobson, and Kluge (2007). By choosing a proper functional form, we show that well-behaved risk neutral densities can be generated by imposing restrictions on the parameters of the model. The results of our numerical experiments demonstrate that the method is capable of extracting risk neutral densities with complex characteristics. Moreover, we demonstrate the pricing performance of our method by generating arbitrage-free call option prices that can be used to produce well-behaved densities from S&P 500 Index options. Additionally, the model is extremely easy to implement and calibrate, and further extensions are straightforward. NOTE: This is a preprint. The published version contains, in addition to extensive empirical tests, a generalization of the main model applicable to defaultable stocks, and an intuitive explanation of the choice of the model parameters.

Keywords: option pricing, arbitrage-free, risk neutral density, empirical performance

JEL Classification: C58, G13

Suggested Citation

Orosi, Greg, Estimating Option Implied Risk Neutral Densities: A Novel Parametric Approach (Preprint) (July 26, 2013). Journal of Derivatives, Vol. 23, No. 1, 2015. Available at SSRN: https://ssrn.com/abstract=2260360 or http://dx.doi.org/10.2139/ssrn.2260360

Greg Orosi (Contact Author)

American University of Sharjah ( email )

Sharjah
United Arab Emirates

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
1,272
PlumX Metrics