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Risks 2014, 2(4), 411-424; doi:10.3390/risks2040411

Measuring Risk When Expected Losses Are Unbounded

University Carlos III of Madrid. C/ Madrid, 126. 28903 Getafe, Madrid, Spain
Concordia University. Department of Mathematics and Statistics. 1455 de Maisonneuve Blvd. W., Montreal, QC H3G 1M8, Canada
Author to whom correspondence should be addressed.
Received: 26 May 2014 / Revised: 5 September 2014 / Accepted: 10 September 2014 / Published: 30 September 2014
(This article belongs to the Special Issue Risk Management Techniques for Catastrophic and Heavy-Tailed Risks)
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This paper proposes a new method to introduce coherent risk measures for risks with infinite expectation, such as those characterized by some Pareto distributions. Extensions of the conditional value at risk, the weighted conditional value at risk and other examples are given. Actuarial applications are analyzed, such as extensions of the expected value premium principle when expected losses are unbounded. View Full-Text
Keywords: heavy tail; risk measures; representation theorem; applications heavy tail; risk measures; representation theorem; applications
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Balbás, A.; Blanco, I.; Garrido, J. Measuring Risk When Expected Losses Are Unbounded. Risks 2014, 2, 411-424.

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