Chairs of Statistics and Econometrics



Julien Hambuckers

  • Postdoctoral researcher at the Chair of Statistics (Prof. Dr. Thomas Kneib), since February 2016
  • Member of RTG 1644 Scaling problems in Statistics and Leibniz-WissenschaftsCampus
  • Ph.D. Thesis : Nonparametric and bootstrap techniques applied to financial risk modelling (April 20, 2015), University of Liege. Adivsor : Prof. Dr. Cédric Heuchenne (ULg)
  • Research interests:

    • Financial econometrics
    • Extreme Value Theory and its applications
    • Distribution regression (Generalized Pareto, GAMLSS)
    • Bootstrap techniques in time series
    • Applications in operational risks, credit risk, empirical finance and ecology

    Teaching:

    • SoSe 2018: Generalized Linear Model
    • WiSe 2017: Statistical inference (Likelihood & Bayes)
    • SoSe 2017: Generalized Linear Model
    • WiSe 2016: Graduate seminar in Applied Statistics
    • 2013-2015: Introduction to MatLab and applications (HEC-ULg)
    • 2012-2015: Empircal methods in financial markets (HEC-ULg)
      • Publications in refereed journals:

        1. Hambuckers, J., Groll, A. and Kneib, T. (2018)
          Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach.
          Journal of Applied Econometrics, forthcoming. Download the paper, the supplementary and the data.

        2. Hambuckers, J., Kneib, T., Langrock, R. and Sohn, A. (2018)
          A Markov-switching Generalized Additive Model for Compound Poisson Processes, with Applications to Operational Losses Models.
          Quantitative Finance, forthcoming. Download the paper and the supplementary .

        3. Hambuckers, J., Dauvrin, A., Trolliet, F., Evrard, Q., Forget, P.-M. and Hambuckers, A. (2017)
          How to assess, fast and accurately, seed removal rate of zoochoric tree species?
          Forest Ecology and Management, 403(1), 152-160. Link.

        4. Hambuckers, J. and Heuchenne, C. (2017)
          A robust statistical approach to select adequate error distributions for financial returns.
          Journal of Applied Statistics, 44(1), 137-161. Link.

        5. Hambuckers, J. and Heuchenne, C. (2016)
          Estimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach.
          Journal of Forecasting, 35(4), 347–372. Link.

        Work under review

        • Hambuckers, J., Heuchenne, C. and Lopez, O. (2017) A semiparametric model for Generalized Pareto regression based on a dimension reduction assumption. Download the paper here.
        • Bee, M., Hambuckers, J. and Trapin, L. (2018) Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach.

        Past:

        • Credit risk analyst at Dexia Bank S. A. (10/2015 to 01/2016)
        • F.N.R.S (Belgian Fund for Scientific Research) research fellow, University of Liège (Belgium), (10/2011 to 09/2015)
        • Ph.D. in Economics and management science, University of Liège (10/2011 - 04/2015)
        • M.Sc. in Business Engineering (financial engineering), University of Liège (09/2009 to 09/2011 - magna cum laude)
        • B.Sc. in Business Engineering (mathematical modelling), University of Liège (09/2006 to 06/2009 - cum laude)