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Huang, W., Liu Q., Ghon Rhee S., Feng W. (2012) ‘Extreme downside risk and expected stock returns ’, Journal of Banking & Finance, Vol. 36 pp 1492-1502.

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Article

Risk Measurement in Commodities Markets Using Conditional Extreme Value Theory

1Business, Economics Statistics Modelling Laboratory (BESTMOD), Faculty of Economics and Management, Sfax-Tunisia


International Journal of Econometrics and Financial Management. 2014, Vol. 2 No. 5, 188-205
DOI: 10.12691/ijefm-2-5-4
Copyright © 2014 Science and Education Publishing

Cite this paper:
Ahmed GHORBEL, Sameh SOUILMI. Risk Measurement in Commodities Markets Using Conditional Extreme Value Theory. International Journal of Econometrics and Financial Management. 2014; 2(5):188-205. doi: 10.12691/ijefm-2-5-4.

Correspondence to: Ahmed  GHORBEL, Business, Economics Statistics Modelling Laboratory (BESTMOD), Faculty of Economics and Management, Sfax-Tunisia. Email: ahmed_isg@yahoo.fr

Abstract

The aim of this paper is to quantify risk in oil, gas natural and phosphates markets by the Value at Risk and Expected Shortfull using McNeil and Frey (2000) two-steps approach based on the combination of the theory of extreme values and the GARCH model. A comparison is made between this method and various conventional methods such as GARCH models, Filtered hsitoriacal simulation, unconditional EVT-POT and unconditional EVT Bloc. Particular attention is given to study the quality of VaR forecasts obtained from conditional EVT method. The results we report show that this method is the best one for quantile superior to 99%. In all other cases, it offer acceptable VaR’s forecasts but not statistically better than GARCH methods.

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