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Implied value-at-risk and model-free simulation

We propose a novel model-free approach for extracting the risk-neutral quantile function of an asset using options written on this asset. We develop two applications. First, we show how for a given stochastic asset model our approach makes it possible to simulate the underlying terminal asset value...

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Detalles Bibliográficos
Autores principales: Bernard, Carole, Perchiazzo, Andrea, Vanduffel, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638439/
https://www.ncbi.nlm.nih.gov/pubmed/36373135
http://dx.doi.org/10.1007/s10479-022-05048-w
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author Bernard, Carole
Perchiazzo, Andrea
Vanduffel, Steven
author_facet Bernard, Carole
Perchiazzo, Andrea
Vanduffel, Steven
author_sort Bernard, Carole
collection PubMed
description We propose a novel model-free approach for extracting the risk-neutral quantile function of an asset using options written on this asset. We develop two applications. First, we show how for a given stochastic asset model our approach makes it possible to simulate the underlying terminal asset value under the risk-neutral probability measure directly from option prices. Specifically, our approach outperforms existing approaches for simulating asset values for stochastic volatility models such as the Heston, the SVI, and the SABR models. Second, we estimate the option implied value-at-risk (VaR) and the option implied tail value-at-risk (TVaR) of a financial asset in a direct manner. We also provide an empirical illustration in which we use S &P 500 Index options to construct an implied VaR Index and we compare it with the VIX Index.
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spelling pubmed-96384392022-11-07 Implied value-at-risk and model-free simulation Bernard, Carole Perchiazzo, Andrea Vanduffel, Steven Ann Oper Res Original Research We propose a novel model-free approach for extracting the risk-neutral quantile function of an asset using options written on this asset. We develop two applications. First, we show how for a given stochastic asset model our approach makes it possible to simulate the underlying terminal asset value under the risk-neutral probability measure directly from option prices. Specifically, our approach outperforms existing approaches for simulating asset values for stochastic volatility models such as the Heston, the SVI, and the SABR models. Second, we estimate the option implied value-at-risk (VaR) and the option implied tail value-at-risk (TVaR) of a financial asset in a direct manner. We also provide an empirical illustration in which we use S &P 500 Index options to construct an implied VaR Index and we compare it with the VIX Index. Springer US 2022-11-05 /pmc/articles/PMC9638439/ /pubmed/36373135 http://dx.doi.org/10.1007/s10479-022-05048-w Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Bernard, Carole
Perchiazzo, Andrea
Vanduffel, Steven
Implied value-at-risk and model-free simulation
title Implied value-at-risk and model-free simulation
title_full Implied value-at-risk and model-free simulation
title_fullStr Implied value-at-risk and model-free simulation
title_full_unstemmed Implied value-at-risk and model-free simulation
title_short Implied value-at-risk and model-free simulation
title_sort implied value-at-risk and model-free simulation
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638439/
https://www.ncbi.nlm.nih.gov/pubmed/36373135
http://dx.doi.org/10.1007/s10479-022-05048-w
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