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A general equilibrium approach to pricing volatility risk

This paper provides a general equilibrium approach to pricing volatility. Existing models (e.g., ARCH/GARCH, stochastic volatility) take a statistical approach to estimating volatility, volatility indices (e.g., CBOE VIX) use a weighted combination of options, and utility based models assume a speci...

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Detalles Bibliográficos
Autores principales: Han, Jianlei, Linnenluecke, Martina, Liu, Zhangxin, Pan, Zheyao, Smith, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461293/
https://www.ncbi.nlm.nih.gov/pubmed/30978225
http://dx.doi.org/10.1371/journal.pone.0215032
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author Han, Jianlei
Linnenluecke, Martina
Liu, Zhangxin
Pan, Zheyao
Smith, Tom
author_facet Han, Jianlei
Linnenluecke, Martina
Liu, Zhangxin
Pan, Zheyao
Smith, Tom
author_sort Han, Jianlei
collection PubMed
description This paper provides a general equilibrium approach to pricing volatility. Existing models (e.g., ARCH/GARCH, stochastic volatility) take a statistical approach to estimating volatility, volatility indices (e.g., CBOE VIX) use a weighted combination of options, and utility based models assume a specific type of preferences. In contrast we treat volatility as an asset and price it using the general equilibrium state pricing framework. Our results show that the general equilibrium volatility method developed in this paper provides superior forecasting ability for realized volatility and serves as an effective fear gauge. We demonstrate the flexibility and generality of our approach by pricing downside risk and upside opportunity. Finally, we show that the superior forecasting ability of our approach generates significant economic value through volatility timing.
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spelling pubmed-64612932019-05-03 A general equilibrium approach to pricing volatility risk Han, Jianlei Linnenluecke, Martina Liu, Zhangxin Pan, Zheyao Smith, Tom PLoS One Research Article This paper provides a general equilibrium approach to pricing volatility. Existing models (e.g., ARCH/GARCH, stochastic volatility) take a statistical approach to estimating volatility, volatility indices (e.g., CBOE VIX) use a weighted combination of options, and utility based models assume a specific type of preferences. In contrast we treat volatility as an asset and price it using the general equilibrium state pricing framework. Our results show that the general equilibrium volatility method developed in this paper provides superior forecasting ability for realized volatility and serves as an effective fear gauge. We demonstrate the flexibility and generality of our approach by pricing downside risk and upside opportunity. Finally, we show that the superior forecasting ability of our approach generates significant economic value through volatility timing. Public Library of Science 2019-04-12 /pmc/articles/PMC6461293/ /pubmed/30978225 http://dx.doi.org/10.1371/journal.pone.0215032 Text en © 2019 Han et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Han, Jianlei
Linnenluecke, Martina
Liu, Zhangxin
Pan, Zheyao
Smith, Tom
A general equilibrium approach to pricing volatility risk
title A general equilibrium approach to pricing volatility risk
title_full A general equilibrium approach to pricing volatility risk
title_fullStr A general equilibrium approach to pricing volatility risk
title_full_unstemmed A general equilibrium approach to pricing volatility risk
title_short A general equilibrium approach to pricing volatility risk
title_sort general equilibrium approach to pricing volatility risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461293/
https://www.ncbi.nlm.nih.gov/pubmed/30978225
http://dx.doi.org/10.1371/journal.pone.0215032
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