Are Classical Option Pricing Models Consistent with Observed Option Second-Order Moments? Evidence from High-Frequency Data

Posted: 27 Apr 2013 Last revised: 16 Dec 2015

See all articles by Francesco Audrino

Francesco Audrino

University of St. Gallen; Swiss Finance Institute

Matthias R. Fengler

University of St. Gallen - SEPS: Economics and Political Sciences; Swiss Finance Institute

Date Written: April 26, 2013

Abstract

As a means of validating an option pricing model, we compare the ex-post intra-day realized variance of options with the realized variance of the associated underlying asset that would be implied using assumptions as in the Black and Scholes (BS) model, the Heston and the Bates model. Based on data for the S&P 500 index, we find that the BS model is strongly directionally biased due to the presence of stochastic volatility. The Heston model reduces the mismatch in realized variance between the two markets, but deviations are still significant. With the exception of short-dated options, we achieve best approximations after controlling for the presence of jumps in the underlying dynamics. Finally, we provide evidence that, although heavily biased, the realized variance based on the BS model contains relevant predictive information that can be exploited when option high-frequency data is not available.

Keywords: option pricing, high frequency data, realized variance, stochastic volatility

JEL Classification: C52, C58, G13, G17

Suggested Citation

Audrino, Francesco and Fengler, Matthias R., Are Classical Option Pricing Models Consistent with Observed Option Second-Order Moments? Evidence from High-Frequency Data (April 26, 2013). Journal of Banking and Finance, Vol. 64, 2015, pp. 46-63, Available at SSRN: https://ssrn.com/abstract=2256899 or http://dx.doi.org/10.2139/ssrn.2256899

Francesco Audrino

University of St. Gallen ( email )

Bodanstrasse 6
St. Gallen, CH-9000
Switzerland

Swiss Finance Institute ( email )

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

Matthias R. Fengler (Contact Author)

University of St. Gallen - SEPS: Economics and Political Sciences ( email )

Rosenbergstrasse 22
CH-9000 St. Gallen, 9000
Switzerland

HOME PAGE: http://www.mathstat.unisg.ch/fengler

Swiss Finance Institute ( email )

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

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