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Title: Estimating VaR and ES of the spot price of oil using futures-varying centiles

 

Author: Giacomo Scandroglio; Andrea Gori; Emiliano Vaccaro; Vlasios Voudouris

 

Addresses:
ABM Analytics Ltd., Suite 17 125 145-157 St John Street, EC1V 4PW, London, UK; Centre for International Business and Sustainability, City of London Business School, 84 Moorgate, London EC2M 6SQ, UK
ABM Analytics Ltd., Suite 17 125 145-157 St John Street, EC1V 4PW, London, UK; Centre for International Business and Sustainability, City of London Business School, 84 Moorgate, London EC2M 6SQ, UK
ABM Analytics Ltd., Suite 17 125 145-157 St John Street, EC1V 4PW, London, UK; Centre for International Business and Sustainability, City of London Business School, 84 Moorgate, London EC2M 6SQ, UK
ABM Analytics Ltd., Suite 17 125 145-157 St John Street, EC1V 4PW, London, UK; Centre for International Business and Sustainability, City of London Business School, 84 Moorgate, London EC2M 6SQ, UK

 

Journal: Int. J. of Financial Engineering and Risk Management, 2013 Vol.1, No.1, pp.6 - 19

 

Abstract: This paper illustrates the power of modern statistical modelling in estimating measures of market risk, here applied to the Brent and WTI spot price of oil. Both Value-at-Risk (VaR) and Expected Shortfall (ES) are cast in terms of conditional centiles based upon semi-parametric regression models. Using the GAMLSS statistical framework, we stress the important aspects of selecting a highly flexible parametric distribution (skewed Student's t-distribution) and of modelling both skewness and kurtosis as non-parametric functions of the price of oil futures. Furthermore, an empirical application characterises the relationship between spot oil prices and oil futures - exploiting the futures market to explain the dynamics of the physical market. Our results suggest that NYMEX WTI has heavier tails compared with the ICE Brent. Contrary to the common platitude of the industry, we argue that 'somebody knows something' in the oil business.

 

Keywords: semi-parametric regression; conditional market risk; oil prices; West Texas Intermediate; Brent; VaR; value-at-risk; expected shortfall; spot prices; futures-varying centiles; statistical modelling; oil futures.

 

DOI: http://dx.doi.org/10.1504/IJFERM.2013.053713

 

Available online 04 May 2013

 

 

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