Pricing and hedging options with GARCH-stable proxy volatilities

Mozumder, S, Kabir, H and Dempsey, M 2018, 'Pricing and hedging options with GARCH-stable proxy volatilities', Applied Economics, vol. 50, no. 56, pp. 6034-6046.


Document type: Journal Article
Collection: Journal Articles

Title Pricing and hedging options with GARCH-stable proxy volatilities
Author(s) Mozumder, S
Kabir, H
Dempsey, M
Year 2018
Journal name Applied Economics
Volume number 50
Issue number 56
Start page 6034
End page 6046
Total pages 13
Publisher Routledge
Abstract This article considers modelling nonnormality in return with stable Paretian (SP) innovations in generalized autoregressive conditional heteroskedasticity (GARCH), exponential generalized autoregressive conditional heteroskedasticity (EGARCH)  and Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH) volatility dynamics. The forecasted volatilities from these dynamics have been used as a proxy to the volatility parameter of the BlackScholes (BS) model. The performance of these proxy-BS models has been compared with the performance of the BS model of constant volatility. Using a cross section of S&P500 options data, we find that EGARCH volatility forecast with SP innovations is an excellent proxy to BS constant volatility in terms of pricing. We find improved performance of hedging for an illustrative option portfolio. We also find better performance of spectral risk measure (SRM) than value-at-risk (VaR) and expected shortfall (ES) in estimating option portfolio risk in case of the proxy-BS models under SP innovations. Abbreviation: generalized autoregressive conditional heteroskedasticity (GARCH), exponential generalized autoregressive conditional heteroskedasticity (EGARCH) and Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH).
Subject Applied Economics not elsewhere classified
Keyword(s) Black and Scholes model
EGARCH
expected shortfall
GARCH
GJR-GARCH
spectral risk measure
stable Paretian distribution
VaR
DOI - identifier 10.1080/00036846.2018.1488057
Copyright notice © 2018 Informa UK Limited, trading as Taylor & Francis Group
ISSN 0003-6846
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