@article{Cont:2013:10.1524/strm.2013.1132,
author = {Cont, R and Deguest, R and He, X},
doi = {10.1524/strm.2013.1132},
journal = {Statistics and Risk Modeling},
pages = {133--167},
title = {Loss-Based Risk Measures},
url = {http://dx.doi.org/10.1524/strm.2013.1132},
volume = {30},
year = {2013}
}

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TY  - JOUR
AB  - Starting from the requirement that risk measures of financial portfolios should be based on their losses, not their gains, we define the notion of loss-based risk measure and study the properties of this class of risk measures. We characterize loss-based risk measures by a representation theorem and give examples of such risk measures. We then discuss the statistical robustness of estimators of loss-based risk measures: we provide a general criterion for qualitative robustness of risk estimators and compare thiscriterion with sensitivity analysis of estimators based on influence functions. Finally, we provide examples of statistically robust estimators for loss-based risk measures.
AU  - Cont,R
AU  - Deguest,R
AU  - He,X
DO  - 10.1524/strm.2013.1132
EP  - 167
PY  - 2013///
SP  - 133
TI  - Loss-Based Risk Measures
T2  - Statistics and Risk Modeling
UR  - http://dx.doi.org/10.1524/strm.2013.1132
UR  - http://arxiv.org/abs/1110.1436v2
UR  - http://www.oldenbourg-link.com/doi/abs/10.1524/strm.2013.1132
VL  - 30
ER  - 

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