C. Acerbi and B. Szekely, Back-testing expected shortfall, Risk, pp.1-6, 2014.
DOI : 10.1002/9780470061602.eqf15005

C. Acerbi and B. Székely, L'ES est mort, vive l'ES! Talk at ETH Zurich, 2016.

C. Acerbi and D. Tasche, On the coherence of expected shortfall, Journal of Banking & Finance, vol.26, issue.7, pp.1487-1503, 2002.
DOI : 10.1016/S0378-4266(02)00283-2

P. Artzner, F. Delbaen, J. M. Eber, and D. Heath, Coherent Measures of Risk, Mathematical Finance, vol.9, issue.3, pp.203-228, 1999.
DOI : 10.1111/1467-9965.00068

F. Bellini and V. Bignozzi, On elicitable risk measures, Quantitative Finance, vol.1, issue.5, pp.725-733, 2015.
DOI : 10.1111/j.1467-9965.2006.00277.x

J. Berkowitz, Testing Density Forecasts, With Applications to Risk Management, Journal of Business & Economic Statistics, vol.19, issue.4, pp.465-474, 2001.
DOI : 10.1198/07350010152596718

J. Berkowitz, P. Christoffersen, and D. Pelletier, Evaluating Value-at-Risk Models with Desk-Level Data, Management Science, vol.57, issue.12, pp.2213-2227, 2011.
DOI : 10.1287/mnsc.1080.0964

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.6824

P. Blum, On some mathematical aspects of dynamic financial analysis, 2004.

Y. Cai and K. Krishnamoorthy, Exact Size and Power Properties of Five Tests for Multinomial Proportions, Communications in Statistics - Simulation and Computation, vol.46, issue.1, pp.149-160, 2006.
DOI : 10.1080/14786440009463897

P. Christoffersen, Evaluating Interval Forecasts, International Economic Review, vol.39, issue.4, 1998.
DOI : 10.2307/2527341

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.41.8009

P. F. Christoffersen and D. Pelletier, Backtesting Value-at-Risk: A duration-based approach, Journal of Econometrics, vol.2, pp.84-108, 2004.

R. Cont, R. Deguest, and G. Scandolo, Robustness and sensitivity analysis of risk measurement procedures, Quantitative Finance, vol.3, issue.6, pp.593-606, 2010.
DOI : 10.1214/aop/1176994626

URL : https://hal.archives-ouvertes.fr/hal-00497668

N. Costanzino and M. Curran, Backtesting general spectral risk measures with application to expected shortfall, Journal of Risk Model, vol.9, pp.21-31, 2015.
DOI : 10.21314/jrmv.2015.131

N. Costanzino and M. Curran, A Simple Traffic Light Approach to Backtesting Expected Shortfall, SSRN Electronic Journal, 2016.
DOI : 10.2139/ssrn.2603976

R. Davé and G. Stahl, On the accuracy of var estimates based on the variancecovariance approach, Risk Measurement, Econometrics and Neural Networks, pp.198-232, 1998.

M. H. Davis, Consistency of Risk Measure Estimates, SSRN Electronic Journal, 2013.
DOI : 10.2139/ssrn.2342279

F. Diebold, T. Gunther, and A. Tay, Evaluating Density Forecasts with Applications to Financial Risk Management, International Economic Review, vol.39, issue.4, pp.863-883, 1998.
DOI : 10.2307/2527342

URL : http://archive.nyu.edu/bitstream/2451/14779/1/SOR-98-6.pdf

F. Diebold, J. Hahn, and A. Tay, Multivariate Density Forecast Evaluation and Calibration In Financial Risk Management: High-Frequency Returns on Foreign Exchange, Review of Economics and Statistics, vol.20, issue.4, pp.661-673, 1999.
DOI : 10.1016/0022-1996(93)90003-G

F. Diebold and R. Mariano, Comparing preictive accuracy, Journal of Business and Economic Statistics, vol.13, pp.253-265, 1995.
DOI : 10.1080/07350015.1995.10524599

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.9389

P. Embrechts, C. Klüppelberg, and T. Mikosch, Modelling of extremal events in insurance and finance, ZOR Zeitschrift f???r Operations Research Mathematical Methods of Operations Research, vol.73, issue.1, 1997.
DOI : 10.1007/BF01440733

S. Emmer, M. Kratz, and D. Tasche, What is the best risk measure in practice? A comparison of standard measures, The Journal of Risk, vol.18, issue.2, pp.31-60, 2015.
DOI : 10.21314/JOR.2015.318

URL : https://hal.archives-ouvertes.fr/hal-00921283

R. Engle and S. Manganelli, CAViaR, Journal of Business & Economic Statistics, vol.22, issue.4, pp.367-381, 2004.
DOI : 10.1198/073500104000000370

C. Fernández and M. Steel, On Bayesian modeling of fat tails and skewness, Journal of the American Statistical Association, vol.93, pp.359-371, 1998.

T. Fissler and J. Ziegel, Higher order elicitability and Osband???s principle, The Annals of Statistics, vol.44, issue.4, pp.1680-1707, 2016.
DOI : 10.1214/16-AOS1439SUPP

URL : http://arxiv.org/abs/1503.08123

H. Föllmer and A. Schied, Convex measures of risk and trading constraints, Finance and Stochastics, vol.6, issue.4, pp.429-447, 2002.
DOI : 10.1007/s007800200072

H. Föllmer and A. Schied, Stochastic Finance An Introduction in Discrete Time, 2011.

R. Giacomini and H. White, Tests of Conditional Predictive Ability, Econometrica, vol.74, issue.6, pp.1545-1578, 2006.
DOI : 10.1111/j.1468-0262.2006.00718.x

T. Gneiting, Making and Evaluating Point Forecasts, Journal of the American Statistical Association, vol.106, issue.494, pp.746-762, 2011.
DOI : 10.1198/jasa.2011.r10138

URL : http://arxiv.org/abs/0912.0902

J. Kerkhof and B. Melenberg, Backtesting for risk-based regulatory capital, Journal of Banking & Finance, vol.28, issue.8, pp.1845-1865, 2004.
DOI : 10.1016/j.jbankfin.2003.06.007

M. Kratz, Y. Lok, and A. Mcneil, A multinomial test to discriminate between models, ASTIN 2016 Proceedings, available online, 2016.

P. H. Kupiec, Techniques for Verifying the Accuracy of Risk Measurement Models, The Journal of Derivatives, vol.3, issue.2, pp.73-84, 1995.
DOI : 10.3905/jod.1995.407942

N. Lambert, D. Pennock, and Y. Shoham, Eliciting properties of probability distributions, Proceedings of the 9th ACM Conference on Electronic Commerce. EC'08, 2008.

A. J. Mcneil and R. Frey, Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach, Journal of Empirical Finance, vol.7, issue.3-4, pp.271-300, 2000.
DOI : 10.1016/S0927-5398(00)00012-8

A. J. Mcneil, R. Frey, and P. Embrechts, Quantitative Risk Management: Concepts, Techniques and Tools, 2015.

C. Nass, A ? 2 -test for small expectations in contingency tables, with special reference to accidents and absenteeism, Biometrika, vol.46, pp.365-385, 1959.

K. H. Osband, Providing Incentives for Better Cost Forecasting, 1985.

K. Pearson, On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can reasonably be supposed to have arisen from random sampling, Philosophical Magazine Series, vol.5, pp.50-157, 1900.

M. Rosenblatt, Remarks on a Multivariate Transformation, The Annals of Mathematical Statistics, vol.23, issue.3, pp.470-472, 1952.
DOI : 10.1214/aoms/1177729394

D. Tasche, Expected shortfall and beyond, Journal of Banking & Finance, vol.26, issue.7, pp.1519-1533, 2002.
DOI : 10.1016/S0378-4266(02)00272-8

URL : http://arxiv.org/abs/cond-mat/0203558

J. F. Ziegel, COHERENCE AND ELICITABILITY, Mathematical Finance, vol.16, issue.3, pp.901-918, 2016.
DOI : 10.1111/mafi.12080

URL : http://arxiv.org/abs/1303.1690