Characteristic Function-Based Estimation of Affine Option Pricing Models

12 Pages Posted: 14 Feb 2019

See all articles by Yannick Dillschneider

Yannick Dillschneider

Goethe University Frankfurt - Department of Finance

Date Written: February 4, 2019

Abstract

In this paper, we derive explicit expressions for certain joint moments of stock prices and option prices within a generic affine stochastic volatility model. Evaluation of each moment requires weighted inverse Fourier transformation of a function that is determined by the risk-neutral and real-world characteristic functions of the state vector. Explicit availability of such moment expressions allows to devise a novel GMM approach to jointly estimate real-world and risk-neutral parameters of affine stochastic volatility models using observed individual option prices. Moreover, the moment expressions may be used to include option price information into other existing moment-based estimation approaches.

Keywords: Stochastic Volatility, Option Pricing, Generalized Method of Moments, Characteristic Function

JEL Classification: C32, C51, C58, G12, G13

Suggested Citation

Dillschneider, Yannick, Characteristic Function-Based Estimation of Affine Option Pricing Models (February 4, 2019). Available at SSRN: https://ssrn.com/abstract=3328584 or http://dx.doi.org/10.2139/ssrn.3328584

Yannick Dillschneider (Contact Author)

Goethe University Frankfurt - Department of Finance ( email )

Theodor-W.-Adorno-Platz 3
Frankfurt, 60629
Germany

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