We price S&P 500 index options under the assumption that the conditional risk-neutral density function of the index follows a Semi-Nonparametric (SNP) process with GARCH variance. The model is estimated combining a set of option contracts written on the index and the daily index return time series in the period 1996–2011. The in-sample and out-sample performance of the model is compared with several benchmark models, beating most of them.We conclude that a pricing model dealing simultaneously with non-normalities and time-varying volatility helps to mitigate the observed S&P 500 index option biases.

Pricing S&P 500 index options: a conditional semi-nonparametric approach

GUIDOLIN, MASSIMO;
2016

Abstract

We price S&P 500 index options under the assumption that the conditional risk-neutral density function of the index follows a Semi-Nonparametric (SNP) process with GARCH variance. The model is estimated combining a set of option contracts written on the index and the daily index return time series in the period 1996–2011. The in-sample and out-sample performance of the model is compared with several benchmark models, beating most of them.We conclude that a pricing model dealing simultaneously with non-normalities and time-varying volatility helps to mitigate the observed S&P 500 index option biases.
2016
2015
Guidolin, Massimo; Hansen, Erwin
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3993730
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