VaR and CVaR estimates in BRIC’s Oil Sector: A Normal Inverse Gaussian Distribution Approach
The Value at Risk (VaR) and the Conditional Value at Risk (CVaR) as measures that estimate risk, have been used in oil sector to measure extreme and unexpected scenarios of oil prices. Additionally, the Normal Inverse Gaussian (NIG) distribution, a special case of the Generalized Hyperbolic (GH) fam...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | México |
| Institución: | UNIVERSIDAD AUTÓNOMA METROPOLITANA |
| Repositorio: | Economía: Teoría y práctica |
| Idioma: | español inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/448 |
| Acceso en línea: | https://economiatyp.uam.mx/index.php/ETYP/article/view/448 |
| Access Level: | acceso abierto |
| Palabra clave: | Value at Risk (VaR) Conditional Value at Risk (CVaR) Normal Inverse Gaussian (NIG) distribution Oil Equity Returns BRIC economies G15 G11 |
| Sumario: | The Value at Risk (VaR) and the Conditional Value at Risk (CVaR) as measures that estimate risk, have been used in oil sector to measure extreme and unexpected scenarios of oil prices. Additionally, the Normal Inverse Gaussian (NIG) distribution, a special case of the Generalized Hyperbolic (GH) family, has been demonstrated to provide a better fit than Normal distribution to financial data. In this paper, we used NIG distribution to model a distribution of equity price returns in oil companies in Brazil, Russia, India and China (BRIC) economies in periods of unstable oil prices from 2004 to 2017, with the objective of demonstrating an underestimation of the risk measures when a Normal distribution is assumed and a more conservative estimate of those measures when considering a NIG distribution. |
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