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VaR and CVaR estimates in BRIC’s Oil Sector: A Normal Inverse Gaussian Distribution Approach

Eduardo Sánchez Ruenes (), José Antonio Núñez Mora () and Martha Beatriz Mota Aragón ()
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Eduardo Sánchez Ruenes: Tecnológico de Monterrey, México.
José Antonio Núñez Mora: Tecnológico de Monterrey, México.
Martha Beatriz Mota Aragón: Universidad Autónoma Metropolitana, Mexico.

Economía: teoría y práctica, 2020, vol. 52, issue 1, 207-236

Abstract: 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.

Keywords: Value at Risk (VaR); Conditional Value at Risk (CVaR); Normal Inverse Gaussian (NIG) distribution; oil equity returns; BRIC economies. (search for similar items in EconPapers)
JEL-codes: G11 G15 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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