Abstract
We investigate the relative performance of a wide array of Value at risk (VaR) and Expected Tail Loss (ETL) risk models in the energy commodities markets. The risk models are tested on a sample of daily spot prices of WTI oil, Brent oil, natural gas, heating oil, coal and uranium yellow cake during the recent global financial crisis. The analysed sample includes periods of backwardation and contango. After obtaining the VaR and ETL estimates we proceed to evaluate the statistical significance of the differences in performance of the analysed risk models. We employ a novel methodology for comparing VaR performance allowing us to rank competing models. Our simulation results show that for a significant number of different VaR models there is no statistical difference in the performance.
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Žiković, S. (2017). Measuring Financial Risk in Energy Markets. In: Härdle, W., Chen, CH., Overbeck, L. (eds) Applied Quantitative Finance. Statistics and Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54486-0_15
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DOI: https://doi.org/10.1007/978-3-662-54486-0_15
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