Robustness and sensitivity analysis of risk measurement procedures

Quantitative Finance

Volumn 10, Issue 6, 2010, Pages 593-606

  Cont, Rama ^a   Deguest, Romain ^b   Scandolo, Giacomo ^c  

^a Department of Earth and Environmental Sciences   (United States)

^b CNRS   (France)

^c UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Coherent risk measures; Expected shortfall; Law invariant risk measures; Risk management; Risk measurement; Value at Risk

Indexed keywords

EID: 77953483123     PISSN: 14697688     EISSN: 14697696     Source Type: Journal    
DOI: 10.1080/14697681003685597     Document Type: Article

References (22)

1. Acerbi, C., Spectral measures of risk: a coherent representation of subjective risk aversion. J. Bank. Finance, 2002, 26, 1505-1518.
2. Acerbi, C., Coherent measures of risk in everyday market practice. Quant. Finance, 2007, 7, 359-364.
3. Artzner, P., Delbaen, F., Eber, J. and Heath, D., Coherent measures of risk. Math. Finance, 1999, 9, 203-228.
4. Costa, V. and Deshayes, J., Comparaison des RLM estimateurs. Theorie de la robustesse et estimation d'un parametre. Asterisque, 1977, 43-44.
5. Czellar, V., Karolyi, G.A. and Ronchetti, E., Indirect robust estimation of the short-term interest rate process. J. Empir. Finance, 2007, 14, 546-563.
6. Danielsson, J., Jorgensen, B., Samorodnitsky, G., Sarma, M. and de Vries, C., Subadditivity re-examined: the case for Value-at-Risk. Preprint, London School of Economics, 2005.
7. Dell'Aquila, R. and Embrechts, P., Extremes and robustness: a contradiction? Financial Mkts Portfol. Mgmt, 2006, 20, 103-118.
8. Deniau, C., Oppenheim, G. and Viano, C., Courbe d'influence et sensibilite. Theorie de la robustesse et estimation d'un parametre. Asterisque, 1977, 43-44.
9. Dhaene, J., Laeven, R., Vanduffel, S., Darkiewicz, G. and Goovaerts, M., Can a coherent risk measure be too subadditive? J. Risk Insurance, 2008, 75, 365-386.
10. Follmer, H. and Schied, A., Convex measures of risk and trading constraints. Finance Stochast., 2002, 6, 429-447.
11. Follmer, H. and Schied, A., Stochastic Finance: An Introduction in Discrete Time, 2004 (Walter de Gruyter: Berlin).
12. Frittelli, M. and Rosazza Gianin, E., Putting order in risk measures. J. Bank. Finance, 2002, 26, 1473-1486.
13. Gourieroux, C., Laurent, J. and Scaillet, O., Sensitivity analysis of values at risk. J. Empir. Finance, 2000, 7, 225-245.
14. Gourieroux, C. and Liu, W., Sensitivity analysis of distortion risk measures. Working Paper, 2006.
15. Hampel, F., Ronchetti, E., Rousseeuw, P. and Stahel, W., Robust Statistics: The Approach Based on Influence Functions, 1986 (Wiley: New York).
16. Heyde, C., Kou, S. and Peng, X., What is a good risk measure: bridging the gaps between data, coherent risk measures, and insurance risk measures. Preprint, Columbia University, 2007.
17. Huber, P., Robust Statistics, 1981 (Wiley: New York).
18. Ibragimov, R. and Walden, J., The limits of diversification when losses may be large. J. Bank. Finance, 2007, 31, 2551-2569.
19. Kusuoka, S., On law invariant coherent risk measures. Adv. Math. Econ., 2001, 3, 83-95.
20. Rockafellar, R. and Uryasev, S., Conditional Value-at-Risk for general distributions. J. Bank. Finance, 2002, 26, 1443-1471.
21. Tasche, D., Expected shortfall and beyond. In Statistical Data Analysis Based on the L1-Norm and Related Methods, edited by Y. Dodge, pp. 109-123, 2002 (Birkhauser: Boston, Basel, Berlin).
22. Van Zwet, W., A strong law for linear functions of order statistics. Ann. Probab., 1980, 8, 986-990.