KRATZ Marie

ESSEC Full Professor, from Oct. 2011

Part time visting professor (July 2017-July 2020), Department of Statistics, Lund University, Sweden

Director of CREAR - Center of Research in Econo-finance and Actuarial Science on Risk - (see http://crear.essec.edu), from Jan. 2013

Fellow of the "Institut des Actuaires" (IA 2013; qualification 2015; certification 2015; fellow 2016)

ESSEC Associate Professor, Oct. 2006 - Sept. 2011

Maître de Conférences at the University René Descartes Paris V (UFR Mathématiques & Informatique) until Oct. 2006

Delegation C.N.R.S. (SAMOS-MATISSE, UMR 8595, 1999-2000)

Post-doctorat/delegation with S. Resnick (Fall sem. 1993, 94, 95), Cornell University (O.R.I.E.), Ithaca, N.Y., USA

PhD. in Applied Mathematics, made to a great extent at the Center for Stochastic Processes, UNC Chapel Hill, USA

• 2005 : HDR (Université Paris 1 Panthéon-Sorbonne, France)
• 1993 : Doctorate in Applied Mathematics (Université Pierre et Marie Curie (UPMC), France)

• 2010 : Global colloquium on participant-centered learning (Harvard Business School, United States of America)

Full-time academic appointments

• 2011 - Present : Full Professor (ESSEC Business School, France)
• 2013 - Present : Fellow of the French Institute of Actuaries (Institut des Actuaires, France)
• 2006 - 2011 : Associate Professor (ESSEC Business School, France)

Other Academic Appointments

• 2013 - Present : Affiliated member to RiskLab (ETH Zurich, Switzerland)
• 2017 - 2020 : Part-time Visiting Professor (Lund University. School of Economics and Management. Statistics Department, Sweden)
• 2012 : Internship at FINMA, Swiss Financial Market Supervisory Authority (Swiss Financial Market Supervisory Authority FINMA, Switzerland)
• 2004 - 2009 : Member of MAP5 (Applied Mathematics), UMR8145 (Université Paris Descartes (Paris V), France)
• 1994 - 2006 : Assistant, then associate professor (Université Paris Descartes (Paris V), France)
• 1999 - 2000 : Delegation C.N.R.S. (SAMOS-MATISSE, UMR 8595 (CNRS - Centre national de la recherche scientifique, France)
• 2012 - Present : Director of the ESSEC-ISUP actuarial track (ESSEC Business School, France)
• 2013 - Present : Director of CREAR - Center of Research in Econo-finance and Actuarial Science on Risk (ESSEC Business School, France)
• 2012 - 2016 : Scientific Coordinator of the European Project ‘RARE’ - Risk Analysis, Ruin and Extremes - FP7-PEOPLE-2012-IRSES - Marie Curie Actions, which aims to strengthen research partnerships through staff exchanges and networking activities between European research organizations and research organizations from other countries. (12 partners) (ESSEC Business School, France)
• 2011 - 2015 : Director of the research program ESSEC - SWISS LIFE ”Consequences of the population ageing on the insurances loss. Impacts on the automobile prevention” (ESSEC Business School, France)
• 2011 - 2014 : Director of the Research program with SWISS LIFE on: Consequences of the population ageing on the insurances loss. Impacts on the automobile prevention (ESSEC Business School, France)
• 2008 - 2012 : Co-responsible of the ESSEC-ISUP actuarial track (ESSEC Business School, France)

• 2013 : Fellow of the French Institute of Actuaries (Institut des Actuaires, France)

• 2018 : International chair labex MME-DII & ESSEC CREAR on Risk Analysis & Management, held by Dr. Michel Dacorogna (ESSEC CREAR, France)
• 2017 : ETH Risk Center (ETH Zurich, Switzerland)
• 2016 : Institute for Mathematical Research (FIM) (ETH Zurich, Switzerland)
• 2016 - 2019 : Visiting scholar and Member of the advisory board of QRFE (Durham University Business School, United Kingdom)
• 2014 - 2022 : Labex MME-DII (Labex MME-DII, France)
• 2014 - 2016 : Tata Institute for Fundamental Research (TIFR, India), by a grant from the Indo-French Center for Applied Mathematics (IFCAM) for a research project between M. Kratz & S. Vadlamani (Tata Institute for Fundamental Research)
• 2012 - 2016 : European FP7-RARE project
• 2012 - 2016 : FP7-PEOPLE-2012-IRSES - Marie Curie Actions (European Union, Belgium)
• 2010 : Ceressec Research projects grants

• BRÄUTIGAM, M., DACOROGNA, M. and KRATZ, M. (2023). Pro-cyclicality beyond business cycle. Mathematical Finance, 33(2), pp. 308-341.
• KRATZ, M. and PROKOPENKO, E. (2023). Multi-normex distributions for the sum of random vectors. Rates of convergence. Extremes, In press.
• BRÄUTIGAM, M. and KRATZ, M. (2023). How do empirical estimators of popular risk measures impact pro-cyclicality? Annals of Actuarial Science, In press, pp. 1-33.
• DACOROGNA, M. and KRATZ, M. (2023). Managing cyber risk, a science in the making. Scandinavian Actuarial Journal, In press, pp. 1-22.
• DACOROGNA, M., DEBBABI, N. and KRATZ, M. (2023). Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data. European Journal of Operational Research, In press.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2020). Probabilistic Forecasting of Bubbles and Flash Crashes. Econometrics Journal, 23(2).
• DAS, S. and KRATZ, M. (2020). Risk Concentration Under Second Order Regular Variation. Extremes, 23, pp. 381-410.
• CADENA, M., KRATZ, M. and OMEY, E. (2019). Characterization of a general class of tail probability distributions. Statistics and Probability Letters, 154, pp. 108553.
• CADENA, M., KRATZ, M. and OMEY, E. (2019). On functions bounded by Karamata functions. Journal of Mathematical Sciences, 237(5), pp. 621-630.
• KRATZ, M. (2019). L’approche statistique au service de l’humain : mieux comprendre les risques cyber pour une société plus résiliente. Revue de la Gendarmerie Nationale, (266), pp. 61-62.
• KRATZ, M., LOK, Y.H. and MCNEIL, A.J. (2018). Multinomial VaR Backtests: A Simple Implicit Approach to Backtesting Expected Shortfall. Journal of Banking and Finance, 88(C), pp. 393-407.
• DACOROGNA, M., ELBAHTOURI, L. and KRATZ, M. (2018). Validation of Aggregated Risks Models. Annals of Actuarial Science, 12(2), pp. 1-22.
• KRATZ, M. and VADLAMANI, S. (2017). Central Limit Theorem for Lipschitz–Killing Curvatures of Excursion Sets of Gaussian Random Fields. Journal of Theoretical Probability, 31(3), pp. 1729-1758.
• KRATZ, M. (2017). Discussion on the Paper: Elicitability and Backtesting: Perspectives for Banking Regulation. Annals of Applied Statistics, 11(4), pp. 1894-1900.
• CADENA, M., KRATZ, M. and OMEY, E. (2017). On the Order of Functions at Infinity. Journal of Mathematical Analysis and Applications, 452(1), pp. 109-125.
• DACOROGNA, M., ELBAHTOURI, L. and KRATZ, M. (2016). Explicit Diversification Benefit for Dependent Risks. SCOR.
• CADENA, M. and KRATZ, M. (2016). New Results for Tails of Probability Distributions According to Their Asymptotic Decay. Statistics and Probability Letters, 109, pp. 178-183.
• KRATZ, M. and NAGEL, W. (2016). On the Capacity Functional of Excursion Sets of Gaussian Random Fields on R². Advances in Applied Probability, 48(3), pp. 712-725.
• EMMER, S., KRATZ, M. and TASCHE, D. (2015). What Is the Best Risk Measure in Practice? A Comparison of Standard Measures. Journal of Risk, 18(2), pp. 31-60.
• GUILLOU, A., KRATZ, M. and LE STRAT, Y. (2014). An Extreme Value Theory Approach for the Early Detection of Time Clusters. A Simulation-Based Assessment and an Illustration to the Surveillance of Salmonella. Statistics in Medicine, 33(28), pp. 5015-5027.
• KRATZ, M. (2014). Normex, a New Method for Evaluating the Distribution of Aggregated Heavy Tailed Risks. Extremes, 17(4), pp. 661-691.
• BUSSE, M., DACAOROGNA, M. and KRATZ, M. (2014). The Impact of Systemic Risk on the Diversification Benefits of a Risk Portfolio. Risks, 2, pp. 260-276.
• DAS, S. and KRATZ, M. (2012). Alarm System for Insurance Companies: A Strategy for Capital Allocation. Insurance: Mathematics and Economics, 51(1), pp. 53-65.
• ESTRADE, A., IRIBARREN, I. and KRATZ, M. (2012). Chord-Length Distribution Functions and Rice Formulae. Application to Random Media. Extremes, 15(3), pp. 333-352.
• CAPA SANTOS, H., KRATZ, M. and MOSQUERA MUNOZ, F. (2012). Modeling Macroeconomic Effects and Expert Judgements in Operational Risk: A Bayesian Approach. Journal of Operational Risk, 7(4), pp. 3-23.
• DEMICHEL, Y., ESTRADE, A., KRATZ, M. and SAMARODNITSKY, S. (2011). How Fast Can the Chord-Length Distribution Decay? Advances in Applied Probability, 43(2), pp. 504-523.
• KRATZ, M. and LEON, J.R. (2010). Level Curves Crossings and Applications for Gaussian Models. Extremes, 13(3), pp. 315-351.
• KRATZ, M. (2006). Level Crossings and Other Level Functionals of Stationary Gaussian Processes. Probability Surveys, pp. 230-288.
• KRATZ, M. and LEON, J. (2006). On the second moment of the number of crossings by a stationary Gaussian process. Annals of Probability, 34(4), pp. 1601-1607.
• KRATZ, M. and PICCO, P. (2004). On a representation of Gibbs measure for R.E.M. Annals of Applied Probability, 14(2), pp. 651-677.
• KRATZ, M. and LEON, J. (2001). Central Limit Theorems for Level Functionals of Stationary Gaussian Processes and Fields. Journal of Theoretical Probability, 14(3), pp. 639-672.
• KRATZ, M. and LEON, J. (2000). Central limit theorems for the number of maxima and some estimator of the second spectral moment of a stationary Gaussian process. Applications in hydroscience. Extremes, 3(1), pp. 57-86.
• KRATZ, M. and LEON, J. (1997). Hermite polynomial expansion for non-smooth functionals of stationary Gaussian processes: crossings and extremes. Stochastic Processes and their Applications, 66(2), pp. 237-252.
• KRATZ, M. and ROOTZÉN, H. (1997). On the rate of convergence for extremes of mean square differentiable stationary normal processes. Journal of Applied Probability, 34(4), pp. 908-923.
• KRATZ, M., RESNICK, S. and FEIGIN, P. (1996). Parameter estimation for moving averages with positive innovations. Annals of Applied Probability, 6, pp. 1157-1190.
• KRATZ, M. and RESNICK, S. (1996). The Q-Q estimator and heavy tails. Stochastic Models, 12(4), pp. 699-724.
• KRATZ, M. and HÜSLER, J. (1995). Rate of Poisson approximation of the number of exceedances of nonstationary normal sequences. Stochastic Processes and their Applications, 55, pp. 301-313.
• KRATZ, M. (1993). Approximation Poissonnienne relative du processus empirique., 316, série I, pp. 1221-1224.

• KRATZ, M. and DACOROGNA, M. (2020). Moving from Uncertainty to Risk: the Case of Cyber Risk. In: Hugo Loiseau, Daniel Ventre, Hartmut Aden eds. Cybersecurity in Humanities and Social Sciences. A Research Methods Approach. 1st ed. London & Hoboken: ISTE - WILEY, pp. 123-152.
• KRATZ, M. (2019). Mathematics of Risk - Introduction to Extreme Value Theory. Applications to Risk Analysis & Management. In: 2017 MATRIX Annals - Mathematics of Risk. 1st ed. Springer, pp. 591-637.
• KRATZ, M. (2016). On the Estimation of the Distribution of Aggregated Heavy-Tailed Risks: Application to Risk Measures. In: Extreme Events in Finance: Handbook of Extreme Value Theory and Its Applications. 1st ed. Wiley, pp. 239-282.

• KRATZ, M. (2005). HDR. France.

• DACOROGNA, M. and KRATZ, M. (2022). Special Issue “Cyber Risk and Security”. Risks, 10.
• CONSTANTINESCU, C., HASHORVA, E. and KRATZ, M. (2018). Annals of Actuarial Science. Annals of Actuarial Science, 12.

• CADENA, M., KRATZ, M. and OMEY, E. (2017). On Functions Bounded by Karamata Functions. In: Proceedings of XXXIV International Seminar on Stability Problems for Stochastic Models. Journal of Mathematical Analysis and Applications.
• KRATZ, M., LOK, Y. and NCNEIL, A. (2016). A Multinomial Test to Discriminate Between Models. In: 2016 ASTIN Colloquium. Lisbon School of Economics and Management.
• DEBBABI, N., KRATZ, M., MBOUP, M. and EL ASMI, S. (2015). Distribution hybride pour la modélisation de données à deux queues lourdes: Application sur les données neuronales. In: 25ème Édition du Colloque GRETSI. École Normale Supérieure de Lyon.
• DEBBABI, N., KRATZ, M., MBOUP, M. and EL ASMI, S. (2012). Combining Algebraic Approach with Extreme Value Theory for Spike Detection. In: Proceedings of EUSIPCO 2012.
• KRATZ, M., ATENCIA, M. and JOYA, G. (2007). Fixed Points of the Abe Formulation of Stochastic Hopfield Networks. In: ICANN - LNCS 4668. Springer.
• KRATZ, M. and HÜSLER, J. (1994). On the convergence of the number of exceedances of nonstationary normal sequences. In: Extreme Value Theory and Applications. Gaithersburg: Journal of Research of the National Institute of Standards and Technology, pp. 539-542.

• KRATZ, M., HAMBUCKERS, J. and USSEGLIO-CARLEVE, A. (2023). Efficient Estimation in Extreme Value Regression Models of Hedge Fund Tail Risk. In: 2023 JAFEE-ISM International Symposium. Tokyo.
• KRATZ, M. and BRAUTIGAM, M. (2023). Joint Asymptotics for the Sample Quantile and Measures of Dispersion for Functionals of Mixing Processes. In: 43rd Conference on Stochastic Processes and their Applications 2023. Lisbon.
• KRATZ, M. and DACOROGNA, M. (2023). Cyber Risk Analysis: Overview and Focus on Extremes. In: 54èmes Journées de Statistique de la SFdS (JdS2023). Brussels.
• KRATZ, M. and PROKOPENKO, E. (2023). Multi-Normex for Evaluating the Distribution of Aggregated Heavy Tailed Risks. In: 13th Conference on Extreme Value Analysis, Probabilistic and Statistical Models and their Applications 2023. Milan.
• KRATZ, M. and PROKOPENKO, E. (2022). Multi-Normex Approach based on Ordered Statistics for evaluating the Sum of Heavy-tailed Random Vectors. In: 14th International Conference on Ordered Statistical Data. Vietri.
• KRATZ, M. and PROKOPENKO, E. (2022). Multi-Normex for evaluating the Distribution of Aggregated Heavy-tailed Risks. In: 53èmes Journées de Statistique de la Société Française de Statistique (SFdS). Lyon.
• DACOROGNA, M. and KRATZ, M. (2022). Consequences for risk management of the analysis of the GN database on cyber attacks. In: ASTIN Cyber Workshop – Capacity Crunch in the Cyber Market. London.
• KRATZ, M. and CHAAR, A. (2021). Combining Machine Learning & Extreme Value Theory for modelling multimodal non homogeneous data. In: 63rd World Statistics Congress 2021, Invited Session: Extreme Value Statistics. Virtual.
• KRATZ, M. and PROKOPENKO, P. (2021). Multi-Normex Distributions. In: 14th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2021). London.
• BRÄUTIGAM, M., KRATZ, M. and DACOROGNA , M. (2021). Pro-­Cyclicality of traditional risk measurement. In: 8th European Congress of Mathematics.
• KRATZ, M. (2021). Assurabilité des Risques Cyber. In: 1er Colloque International de l’Actuariat Francophone. Virtuel.
• KRATZ, M. and AMABA, T. (2019). On the Regularity of Functionals for Stationary Gaussian Processes. In: 41st conference on Stochastic Processes and their Applications (SPA) 2019.
• KRATZ, M., DEBBABI, N. and DACOROGNA, M. (2019). Data Analytics on Cyber Crimes Complaints Registered at C3N of Gendarmerie Nationale. In: 2019 Joint AFIR-ERM / ASTIN Symposium.
• KRATZ, M. (2019). The impact of traditional risk measurement on the pro-cyclicality. In: Paris Seine Initiative Scientific Day. Neuville.
• KRATZ, M. (2019). How does market price extremes of underlying shares in the options market? In: 14th International Conference on Computational and Financial Econometrics (CFE 2020). London.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2018). A Self-Calibrating Method for Heavy Tailed Data Modelling. Application in Neuroscience and Finance. In: 6th European Seminar on Computing (ESCO 2018).
• KRATZ, M. (2018). Exploration statistique de données d'attaques cyber et approche méthodologique. In: Colloque international 'Méthodes de recherche en sciences humaines et sociales sur la cybersécurité.
• KRATZ, M. (2018). Level Crossings and Applications. In: Workshop on 'Can Stochastic Geometry handle Dynamics of Risk Management?'.
• KRATZ, M. (2018). Level Functionals for Gaussian Fields and Applications to Oceanography. In: 2018 Random Waves in Oxford.
• BRÄUTIGAM, M. and KRATZ, M. (2018). On the Dependence between Quantile and Dispersion Estimators. Application to Quantitative Financial Risk Management. In: 7th Monash-Ritsumeikan Symposium on Probability and Related Fields 2018.
• KRATZ, M. (2018). On the Regularity of Time Occupation Functionals for Gaussian Processes. In: Conference on ’Rough Paths Theory and Malliavin Calculus’, Rencontres Mathématiques de Rouen.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2018). Probabilistic Forecasting of Bubbles and Flash Crashes. In: 2018 Asian Meeting of the Econometric Society.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2017). [Invited] A Self-Calibrating Method for Heavy Tailed Data Modeling. Applications in Finance and Insurance. In: CFA France Research Workshop.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2017). [Keynote] A Self-Calibrating Method for Heavy Tailed Data Modeling. Applications in Finance and Insurance. In: 2017 IRFRC Annual Conference.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2017). A Self-Calibrating Method for Heavy Tailed Data Modeling. Applications in Finance and Insurance. In: CMAstat 2017.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2017). A self-calibrating method for heavy-tailed modeling. In: 2017 ERCIM Working Group on Computational and Methodological Statistics (CMStatistics), Birkbeck University of London and King's College London.
• GUILLOU, A., KRATZ, M. and LE STRAT, Y. (2017). An EVT Approach for the Early Detection of Time Clusters. Application in Health Surveillance. In: Probability: from East to West (PEW 2017).
• KRATZ, M., LOK, Y. and MCNEIL, A. (2017). An Implicit Backtest for Expected Shortfall via a Simple Multinomial Approach. In: 2017 IASSL 3rd International Conference - Statistics for Good Governance.
• KRATZ, M. (2017). EVT and its Application to finance and insurance. In: ETH Risk Center March 2017 Workshop.
• KRATZ, M. (2017). Limit Theorems for Functionals of Excursion Sets of Gaussian Random Fields. In: 39th Conference on Stochastic Processes and their Applications.
• KRATZ, M. (2017). Modeling and Backtesting Heavy Tailed Data. In: Durham Business School Workshop.
• KRATZ, M. (2017). On Risk Aggregation. In: MATRIX workshop: "Mathematics of Risk".
• KRATZ, M. (2017). Overview of Copulas for Actuaries in Management. In: SAS Forum Singapore 2017.
• BRAÜTIGAM, M., DACOROGNA, M. and KRATZ, M. (2017). Procyclicality of Empirical Measurements of Risk in Financial Markets. In: 2017 Risk Measurement and Regulatory Issues in Business.
• BRAÜTIGAM, M., DACOROGNA, M. and KRATZ, M. (2017). Procyclicality of Empirical Measurements of Risk in Financial Markets. In: 10th International Conference on Extreme Value Analysis.
• KRATZ, M. (2016). An Implicit Backtest for ES via a Simple Multinomial Approach. In: 5th Iberian Congress of Actuaries.
• KRATZ, M. and VADLAMANI, S. (2016). CLT for Lipschitz-Killing Curvatures. In: 6th Ritsumeikan-Monash Symposium on Probability and Relative Fields.
• KRATZ, M. and VADLAMANI, S. (2016). CLT for Lipschitz-Killing Curvatures of Excursion Sets of Gaussian Fields. In: Monash Probability Conference in Honor of Robert Liptser’s 80th Birthday.
• KRATZ, M. (2016). On New IFRS Rules: When Actuaires Meet Accountants. In: International Round Table.
• KRATZ, M. and DAS, S. (2016). On Risk Concentration. In: 3rd ISNPS (International Society for Non-Parametric Statistics) Conference.
• KRATZ, M. and CHOTARD, R. (2016). Risk Measure Estimates in Quiet and Turbulent Times: an Empirical Study. In: 10th International Conference on Computational and Financial Econometrics (CFE 2016).
• KRATZ, M. (2016). Risk Models Validation [Keynote speaker]. In: 3rd ERM Conference-Singapore Actuarial Society (SAS).
• KRATZ, M. (2016). Standard Risk Measures: A Statistical Debate. In: 2015 IMS-China International Conference on Statistics and Probability.
• KRATZ, M. (2016). Validation of Risk Models. In: IFoA Asia conference.
• KRATZ, M. (2015). Key Issues and Challenges that Researchers of Risk And Practitioners from Industries, Perceive as Significant over the Next Few Years. In: RTLC Research workshop.
• KRATZ, M. and VADLAMANI, S. (2015). On Functionals of Excursion Sets of Gaussian Random Fields on R2. In: 5th Monash-Ritsumeikan Symposium.
• KRATZ, M. and VADLAMANI, S. (2015). On Functionals of Excursion Sets of Gaussian Random Fields on R2. In: 9th international conference on Extreme Value Analysis (EVA 2015).
• KRATZ, M. and DAS, S. (2015). On the Local Behavior of the Extreme Quantiles of the Sum of Heavy Tailed Distributed Random Variables. In: 60th ISI World Statistics Congress (WSC).
• EMMER, S., KRATZ, M. and TASCHE, D. (2015). What is the Best Risk Measure in Practice ? In: 2015 IMS-China International Conference on Statistics and Probability.
• EMMER, S., KRATZ, M. and TASCHE, D. (2015). What is the Best Risk Measure in Pratice? A Comparison of Standard Measures. In: 2nd International Conference of the Society for Economic Measurement.
• DEBBABI, N. and KRATZ, M. (2014). A New Unsupervised Threshold Determination for Hybrid Models. In: 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
• KRATZ, M. (2014). Contributions to Risk Theory. In: 2014 Actuarial Teachers and Researchers Conference.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Coefficient Model. In: 68th European Meeting of the Econometric Society.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2014). Detecting and Forecasting Large Deviations and Bubbles in a Near-Explosive Random Co-efficient Model. In: Summer Institute 2014 of the National Bureau of Economic Research.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Forecasting Bubbles in a Near Explosive Random Coefficient Model. In: 25th EC2 Conference on "Advances in Forecasting".
• KRATZ, M. and CADENA, M. (2014). On a Generalization of Some Karamata Results and Standard EVT Characterizations. In: 37th Conference on Stochastic Processes and their Applications.
• KRATZ, M. (2014). On risk aggregation and diversification benefits. In: Conference on Extreme Events in Finance.
• KRATZ, M. (2014). On the Generalization of Karamata and Standard EVT Characterizations. In: 7th International Workshop on Applied Probability.
• CHEVILLON, G., BANERJEE, A. and KRATZ, M. (2014). Sentiment Driven Buoyancy. In: 8th International Conference on Computational and Financial Econometrics (CFE 2014).
• KRATZ, M. (2014). Setting the risk appetite in the presence of systemic risk. In: Enterprise Risk Management (ERM) conference.
• KRATZ, M. (2013). A Shifted CLT: An Alternative Solution to Correctly Estimate in a Gaussian Realm the Var In Presence Of Heavy Tails. In: Workshop EVT - Extremes in Vimeiro 2013.
• KRATZ, M., BUSSE, M. and DACOROGNA, M. (2013). Does Risk Diversification Always Work? The Answer Through Simple Modelling. In: 13th Annual Conference of the European Network for Business and Industrial Statistics (ENBIS-13).
• KRATZ, M. and NAGEL, W. (2013). On the Capacity Functional of Excursion Sets of Gaussian Random Fields on R^2. In: EVA 2013.
• KRATZ, M. (2013). There is a VaR Beyond Usual Approximations. In: Workshop on Heavy-tailed Distributions and Extreme Value Theory.
• BANERJEE, A., CHEVILLON, G. and KRATZ, M. (2012). Detecting and Predicting Rational Asset Price Bubbles in a Near Explosive Random Coefficient Autoregressive Model. In: SMU-ESSEC Symposium on Empirical Finance and Financial Econometrics 2012.
• ELBAHTOURI, L., DACOROGNA, M. and KRATZ, M. (2012). Explicit Diversification Benefit Formulas for Dependent Risks. In: 1st European Actuarial Journal Conference.
• KRATZ, M. and NAGEL, W. (2012). The Tail Distributions of Functionals of Random Excursion Sets. In: Sixth International Workshop on Applied Probability (IWAP 2012).
• KRATZ, M. and NAGEL, W. (2012). The Tail Distributions of Functionals of Random Excursion Sets (co-author NAGEL W.). In: Stereology, Spatial Statistics and Stochastic Geometry 7th International Conference (S4G 2012).
• KRATZ, M. (2009). A Brief Review on EVT Basics and Operational Risk Measures. In: European Workshop on Risk Analysis and EVT.
• KRATZ, M. (2009). Franchissement de courbe de niveau, formules de Rice et extremum. In: MAS.
• KRATZ, M. (2009). On the decay of Chord-lengths. In: Stochastic Processes and their Applications.
• KRATZ, M. and SHUBHABRATA, D. (2008). On efficiency and Alarm System in Reinsurance Contracts. In: 7th World Congress in Probability and Statistics.
• KRATZ, M., ESTRADE, A. and IRIBARREN, I. (2007). Chord-distribution Functions and Rice Formulae. Application to Random Media.
• KRATZ, M., ATENCIA, M. and JOYA, G. (2007). Fixed points of the Abe formulation of Stochastic Hopfield Networks. In: 17th ICANN. Porto.
• KRATZ, M. and LEON, J. (2006). Curve crossings and specular points, d'après Longuet-Higgins. In: 31th Conference on Stochastic Processes and their Applications. Paris.
• KRATZ, M., ESTRADE, A. and IRIBARREN, I. (2006). Funciones de distribucion de cuerdas en medios porosos. In: Rencontres France-Espagne-Venezuela de probabilité et statistique mathématique. Choroni.
• KRATZ, M. (2005). On level functionals of Gaussian fields. In: 2nd Intern. Conf. of Applied Mathematics. Plovdiv.
• KRATZ, M. (2004). Estadisticas de valores extremos. In: IX Encuentro de Matem'atica y sus Aplicaciones y IV Seminario de Estad'istica Aplicada. Quito.

• KRATZ, M. (2019). Data Analytics on Cyber Crimes Complaints Registered at C3N of PJGN. In: Annual SCOR Group Actuarial Conference.
• KRATZ, M. (2019). Evaluating the cyber risk: the researcher point of view. In: Pôle Analyse : Peut-on évaluer les risques Cyber?, PJGN.
• KRATZ, M. (2019). On the regularity of functionals for stationary Gaussian processes [invited session]. In: 41th SPA (Stochastic Processes and its Applications) conference, Northwestern Univ.
• KRATZ, M. (2019). Data Analytics on Cyber Crimes Complaints Registered at C3N of PJGN. In: ASTIN-AFIR conference. Warsaw.
• KRATZ, M. (2019). Pro-Cyclicality of Traditional Risk Measurements: Quantifying and Highlighting Factors at its Source. In: Zurich-Hannover workshop on Insurance and Financial Mathematics. Hannover.

• CONSTANTINESCU, C., HASHORVA, E. and KRATZ, M. (2018). Editorial: Foreword by the Guest Editors of the RARE special issue. Annals of Actuarial Science, 12, pp. 209-210.

• KRATZ, M. and KHORAMI CHOKAMI, A. (2023). On the relation between extremal dependence and concomitants. WP 2301, ESSEC Business School Research Center.
• KRATZ, M. and DACOROGNA, M. (2023). Managing Cyber Risk, a Science in the Making. WP 2302, ESSEC Business School Research Center.
• KRATZ, M. (2022). Building up Cyber Resilience by Better Grasping Cyber Risk Via a New Algorithm for Modelling Heavy-Tailed Data. WP 2210, ESSEC Business School.
• KRATZ, M. and PROKOPENKO, E. (2021). Multi-Normex Distributions for the Sum of Random Vectors. Rates of Convergence. 2102, ESSEC Business School.
• BRÄUTIGAM, M. and KRATZ, M. (2019). Bivariate FCLT For The Sample Quantile And Measures Of Dispersion For Augmented Garch(p, q) Processes. WP1909, ESSEC Business School.
• BRÄUTIGAM, M. and KRATZ, M. (2018). On The Dependence Between Quantiles And Dispersion Estimators. ESSEC Business School.
• BRÄUTIGAM, M., DACOROGNA, M. and KRATZ, M. (2018). Predicting Risk with Risk Measures: An Empirical Study. ESSEC Business School.
• DAS, S. and KRATZ, M. (2017). Diversification Benefits Under Multivariate Second Order Regular Variation. ESSEC Business School.
• CADENA, M., KRATZ, M. and OMEY, E. (2017). New Results on the Order of Functions at Infinity. ESSEC Business School.
• DEBBABI, N., KRATZ, M. and MBOUP, M. (2016). A Self-Calibrating Method for Heavy Tailed Data Modeling. Application in Neuroscience and Nance. ESSEC Business School.
• KRATZ, M. and VADLAMANI, S. (2016). CLT for Lipschitz-Killing Curvatures of Excursion Sets of Gaussian Random Fields. ESSEC Business School.
• KRATZ, M., LOK, Y.H. and MCNEIL, A.J. (2016). Multinomial VaR Backtests: A Simple Implicit Approach to Backtesting Expected Shortfall. ESSEC Business School.
• CHOTARD, R., DACOROGNA, M. and KRATZ, M. (2016). Risk Measure Estimates in Quiet and Turbulent Times: An Empirical Study. ESSEC Business School.
• DACOROGNA, M., FRANCISCO MIGUELEZ, J.J. and KRATZ, M. (2016). Risk Neutral Versus Real-World Distribution of Publicly Listed Bank Corporations. ESSEC Business School.
• DACOROGNA, M., ELBAHTOURI, L. and KRATZ, M. (2015). Explicit Diversification Benefit for Dependent Risks. ESSEC Business School.
• DACOROGNA, M. and KRATZ, M. (2015). Living in a Stochastic World and Managing Complex Risks. ESSEC Business School.
• KRATZ, M. and CADENA, M. (2014). An Extension of the Class of Regularly Varying Functions. ESSEC Business School.
• KRATZ, M. and NAGEL, W. (2014). On the Capacity Functional of Excursion Sets of Gaussian Random Fields on R². ESSEC Business School.
• BUSSE, M., DACOROGNA, M. and KRATZ, M. (2013). The Impact of Systemic Risk on the Diversification Benefits of a Risk Portfolio. ESSEC Business School.
• KRATZ, M. (2013). There is a VaR Beyond Usual Approximations. ESSEC Business School.
• EMMER, S., KRATZ, M. and TASCHE, D. (2013). What Is the Best Risk Measure in Practice? A Comparison of Standard Measures. ESSEC Business School.
• CAPA SANTOS, H., KRATZ, M. and MOSQUERA MUÑOZ, F.V. (2012). Modelling Macroeconomic Effects and Expert Judgements in Operational Risk: A Bayesian Approach. ESSEC Business School.
• KRATZ, M. (2005). Some contributions in probability and statistics of extremes.
• KRATZ, M. (2000). Chaos expansions and level crossings.
• KRATZ, M. (1993). Statistics of tails of distributions and Poisson approximation.

• KRATZ, M. (2020). Understanding Procyclicality. ESSEC Knowledge.
• KRATZ, M. (2019). Adapting to the new risk landscape: is cyber insurable? ESSEC Knowledge.
• KRATZ, M. (2019). S’adapter au nouvel environnement des risques : peut-on assurer le risque cyber ? Reflets Essec Magazine.
• KRATZ, M. (2017). The Future of Insurance with the Advent of Artificial Intelligence. ESSEC Knowledge.
• DACOROGNA, M., KRATZ, M. and LECOMTE, P. (2016). Changing Times Require New Tools for Risk Management. Asia Insurance Review, pp. 98-99.
• KRATZ, M. (2016). L'actuariat, des activités et compétences en pleine évolution. Grandes Ecoles Magazine.
• KRATZ, M. (2015). Managing Risk Is about Raising Society’s Resilience. Business Times Singapore.

• 2019 - 2021 : Cyber risk ( ETH Risk Center Switzerland)
• 2017 1/2 day workshop on 'EVT and its Application to finance and insurance', ( ETH Risk Center Switzerland)
• 2017 CFA France Research Workshop, 'A self-Calibrating Method for Heavy Tailed Data Modeling' ( CFA Society France France)
• 2017 Mini-workshop on 'Modeling and Backtesting Heavy Tailed Data' ( Durham University Business School United Kingdom)
• 2017 Singapore Actuarial Society Forum on 'Overview of Copulas for Actuaries in Management' ( Singapore Actuarial Society Singapore)
• 2016 'A self-Calibrating Method for Heavy Tailed Data Modeling' ( Swiss Re Switzerland)
• 2016 'An implicit backtest for Expected Shortfall via a simple multinomial approach' ( Bank of International Settlements Switzerland)
• 2016 Two days executive seminar on Quantitative Risk Management ( National Institute of Securities Markets (NISM) India)
• 2013 'An Introduction to Quantitative Risk Management' - course given at the Summer School on Risk Management in Finance and Insurance ( National Economics University Vietnam)

• 2016 - 2022 : Risk analysis (3 grants from Labex MME-DII , from 2020) (Supervision of Research UV)
• 2012 - 2022 : Banks, Insurance companies, Consulting companies (Apprenticeship tutoring)
• 2012 - 2022 : Supervision of Master Thesis (Supervision of dissertation)