Publications and communications of Julien Hambuckers

Hambuckers, J., & Hübner, P. (18 December 2022). Which hedge funds are systemically risky, and when: A dynamic extreme value regression approach. Paper presented at 16th International Conference Computational and Financial Econometrics (CFE 2022), Londres, United Kingdom.

Hambuckers, J., Usseglio-Carleve, A., & Kratz, M. (01 December 2022). Automatic threshold selection for extreme value regression models of tail risks. Paper presented at Erasmus Econometric Institute Seminar, Rotterdam, Netherlands.

Hambuckers, J., Usseglio-Carleve, A., & Kratz, M. (05 June 2022). Automatic Threshold selection for extreme value regression models. Paper presented at 2022 EcoStat conference, Kyoto, Japan.

Mhalla, L., Hambuckers, J., & Lambert, M. (June 2022). Extremal connectedness of hedge funds. Paper presented at Quantitative Finance and Financial Econometrics (QFFE) conference, Marseille, France.

Bee, M., & Hambuckers, J. (2022). Modeling multivariate operational losses via copula-based distributions with g-and-h marginals. Journal of Operational Risk. doi:10.21314/JOP.2021.016

Hambuckers, J., Sun, L., & Trapin, L. (2022). Non-stationary variable selection in time-varying extreme Value regression. Poster session presented at Workshop on Dimensionality Reduction and Inference in High-Dimensional Time Series.

Mhalla, L., Hambuckers, J., & Lambert, M. (2022). Extremal connectedness of hedge funds. Journal of Applied Econometrics. doi:10.1002/jae.2900

Sun, L., Hecq, A., Straetmans, S., & Hambuckers, J. (2022). VAR for VaR and CoVaR. Paper presented at Quantitative Finance and Financial Econometrics (QFFE) conference, Marseille, France.

Ulm, M., & Hambuckers, J. (2022). Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model. Journal of Empirical Finance, 65, 125-148. doi:10.1016/j.jempfin.2021.12.004

Hambuckers, J., Usseglio-Carleve, A., & Kratz, M. (22 October 2021). Automatic threshold selection and efficient estimation in extreme value regression. Paper presented at HEC Lausanne - UNIL, séminaire du Département des Opérations, Lausanne, Switzerland.

Hambuckers, J., & Kneib, T. (2021). Smooth-transition regression models for non-stationary extremes. Journal of Financial Econometrics.

Hambuckers, J., & Ulm, M. (24 June 2021). Interest rate differentials and the dynamic asymmetry of exchange rates. Paper presented at Annual conference of the International Association for Applied Econometrics (IAAE 2021).

Bee, M., Hambuckers, J., Santi, F., & Trapin, L. (2021). Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach. Computational Statistics, 36, 2177–2200. doi:10.1007/s00180-021-01078-3

Bee, M., Hambuckers, J., & Trapin, L. (2021). Estimating large losses in insurance analytics and operational risk using the g-and-h distribution. Quantitative Finance, 21 (7), 1207-1221. doi:10.1080/14697688.2020.1849778

Hambuckers, J., Usseglio-Carleve, A., & Kratz, M. (2021). Automatic threshold selection and efficient estimation in extreme value regression. Paper presented at Statistics and Econometrics Seminar Humboldt-Universität Berlin, Berlin, Germany.

Lurkin, V., Hambuckers, J., & Van Woensel, T. (2021). Urban Low Emissions Zones: A Behavioral Operations Management Perspective. Transportation Research. Part A, Policy and Practice, 144, 222-240. doi:10.1016/j.tra.2020.11.015

Menkveld, A. J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, U., Abad, D., Abudy, M. M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., ... Dare, W. (2021). Non-Standard Errors. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/267437.

Montanari, D., O'Hearn, W., Hambuckers, J., Fisher, J., & Zinner, D. (2021). Coordination during group departures and progressions in the tolerant multi-level society of wild Guinea baboons (Papio papio). Scientific Reports, 11. doi:10.1038/s41598-021-01356-6

Ulm, M., & Hambuckers, J. (2021). Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/256895.

Mhalla, L., Hambuckers, J., & Lambert, M. (11 December 2020). Extremal connectedness and systemic risk of hedge funds. Paper presented at University of Trento STaTA (Statistics: Theory and Applications) Seminar, Trento, Italy.

Mhalla, L., Hambuckers, J., & Lambert, M. (29 October 2020). Extremal connectedness and systemic risk of hedge funds. Paper presented at KU Leuven Statistics Seminar (research groups Faculty of Science and Faculty of Economics and Business Leuven Statistics Research Centre).

Bee, M., & Hambuckers, J. (2020). Modeling multivariate operational losses via copula-based distributions with g-and-h marginals. (July 2020). Eprint/Working paper retrieved from https://orbi.uliege.be/2268/257209.

Hambuckers, J., & Ulm, M. (2020). Interest rate differentials and the dynamic asymmetry of exchange rates. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/257214.

Mhalla, L., Hambuckers, J., & Lambert, M. (2020). Extremal connectedness and systemic risk of hedge funds. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/252040.

Hambuckers, J., & Ulm, M. (02 December 2019). Interest rate differentials and the dynamic asymmetry of exchange rates. Paper presented at Seminar of the Quantitative Economics research group, Maastricht University.

Groll, A., Hambuckers, J., Kneib, T., & Umlauf, N. (December 2019). LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape. Computational Statistics and Data Analysis, 140, 59-74. doi:10.1016/j.csda.2019.06.005

Hambuckers, J., Mhalla, L., & Lambert, M. (December 2019). Tail risk and style dependence in the fund industry: a multivariate extreme value approach. Paper presented at CM Statistics conference 2019, London, Birbeck University, United Kingdom.

Hambuckers, J., & Kneib, T. (27 June 2019). Operational risk, uncertainty, and the economy: a smooth transition extreme value approach. Paper presented at 6th Annual Conference of the International Association for Applied Econometrics, Nicosia, Cyprus.

Hambuckers, J., & Ulm, M. (2019). Interest rate differentials. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/236318.

Mhalla, L., Hambuckers, J., & Lambert, M. (June 2019). Tail risk and style dependence in the fund industry: a multivariate extreme value approach. Paper presented at HEC Lausanne Operation Research Seminar.

Hambuckers, J., & Kneib, T. (26 May 2019). Operational risk, uncertainty, and the economy: a smooth transition extreme value approach. Paper presented at Nordic Econometrics Meeting 2019, Sweden.

Bee, M., Hambuckers, J., & Trapin. (2019). Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach. Quantitative Finance. doi:10.1080/14697688.2019.1580762

Hambuckers, J., & Kneib, T. (2019). Operational risk, uncertainty, and the economy: a smooth transition extreme value approach. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/235956.

Heymann, E. W., Culot, L., Knogge, C., Smith, A. C., Tirado Herrera, E. R., Stojan-Dolar, M., Ferrer, Y. L., Kubisch, P., Kupsch, D., Slana, D., Koopmann, M. L., Ziegenhagen, B., Bialozyt, R., Mengel, C., Hambuckers, J., & Heer, K. (2019). Small Neotropical primates promote the natural regeneration of anthropogenically disturbed areas. Scientific Reports, 9. doi:10.1038/s41598-019-46683-x

Peckre, L., Fabre, A.-C., Hambuckers, J., Wall, C., Socias-Martinez, L., & Pouydebat, E. (2019). Food properties influence grasping strategies in strepsirrhines. Biological Journal of the Linnean Society. doi:10.1093/biolinnean/bly215

Hambuckers, J., & Kneib, T. (15 December 2018). Modeling non-stationary operational risk: A smooth-transition distributional regression approach. Paper presented at 12th International Conference on Computational and Financial Econometrics, Pisa, Italy.

Hambuckers, J. (27 June 2018). Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach. Paper presented at Annual conference of the International Association for Applied Econometrics (IAAE), Montreal, Canada.

Hambuckers, J., & Kneib, T. (April 2018). Operational risk, uncertainty, and the economy: a smooth transition extreme value approach. Paper presented at UNIL Internal Seminar, Operation department.

Hambuckers, J., Groll, A., & Kneib, T. (2018). Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach. Journal of Applied Econometrics, 33 (6), 898-935. doi:10.1002/jae.2638

Hambuckers, J., Groll, A., & Kneib, T. (January 2018). Understanding the determinants of operational loss severity distribution -a regularized generalized Pareto regression Approach. Paper presented at Statistics Seminar, Department of Statistics, Faculty of Economics and Statistics (University of Innsbruck), Innsbruck, Austria.

Hambuckers, J., Kneib, T., Langrock, R., & Silbersdorff, A. (2018). A Markov-switching Generalized additive model for compound Poisson processes, with applications to operational losses models. Quantitative Finance, 18 (10), 1679-1698. doi:10.1080/14697688.2017.1417625

Hambuckers, J. (December 2017). On conditional dynamic skewness and directional forecast of currency exchange rates. Paper presented at 2017 ERCIM - CMstatistics conference, London, United Kingdom.

Hambuckers, J. (July 2017). A Markov-switching Generalized additive model for compound Poisson processes, with applications to operational losses models. Paper presented at 2017 European Meeting of Statisticians, Helsinki, Finland.

Hambuckers, J. (July 2017). A Markov-switching Generalized additive model for compound Poisson processes, with applications to operational losses models. Paper presented at 2017 IWSM conference, Groeningen, Netherlands.

Hambuckers, J. (June 2017). Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach. Paper presented at 10th Extreme Value Conference, Delft, Netherlands.

Hambuckers, J. (May 2017). Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approac. Paper presented at 49th conference of Société Française de Statistique, Avignon, France.

Hambuckers, J., Dauvrin, A., Trolliet, F., Evrard, Q., Forget, P.-M., & Hambuckers, A. (2017). How can seed removal rates of zoochoric tree species be assessed quickly and accurately? Forest Ecology and Management, 403, 152-160. doi:10.1016/j.foreco.2017.07.042

Hambuckers, J., & Heuchenne, C. (2017). A robust statistical approach to select adequate error distributions for financial returns. Journal of Applied Statistics, 44 (1), 137-161. doi:10.1080/02664763.2016.1165803

Hambuckers, J. (December 2016). A Markov-switching Generalized additive model for compound Poisson processes, with applications to operational losses models. Paper presented at ERCIM 2016, Seville, Spain.

Hambuckers, J. (August 2016). A semiparametric model for Generalized Pareto regressions, based on a dimension reduction assumption. Paper presented at COMPSTAT 2016, Oviedo, Spain.

Hambuckers, J., & Heuchenne, C. (July 2016). Estimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach. Journal of Forecasting, 35 (4), 347-372. doi:10.1002/for.2380

Hambuckers, J., Heuchenne, C., & Lopez, O. (09 March 2016). Modeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption. Paper presented at Internal seminar, Operations Department UNIL (HEC Lausanne), Lausanne, Switzerland.

Hambuckers, J. (March 2016). A semiparametric model for Generalized Pareto regression based on a dimension reduction assumption. Poster session presented at Fourth Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik "Statistics under one Umbrella" (DAGstat), Goettingen, Germany.

Hambuckers, J., Heuchenne, C., & Lopez, O. (24 February 2016). Modeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption. Paper presented at Seminar Chair of Statistics Göttingen, Göttingen, Germany.

Hambuckers, J., Heuchenne, C., & Lopez, O. (December 2015). Modeling the dependence between extreme operational losses and economic factors: a conditional semi-parametric Generalized Pareto approach. Paper presented at 13th International Paris Finance Meeting 2015, Paris, France.

Hambuckers, J., Heuchenne, C., & Lopez, O. (June 2015). What are the determinants of the operational losses severity distribution ? A multivariate analysis based on a semiparametric approach. Poster session presented at 8th Annual Society for Financial Econometrics Conference, Aarhus, Denmark.

Hambuckers, J. (2015). Nonparametric and bootstrap techniques applied to financial risk modeling. Unpublished doctoral thesis, ULiège - Université de Liège.
Jury: Heuchenne, C. (Promotor), Hübner, G., Palm, F., Lopez, O., ... Chavez-Demoulin, V.

Hambuckers, J., Heuchenne, C., & Lopez, O. (2015). A semiparametric model for Generalized Pareto regression based on a dimension reduction assumption. Eprint/Working paper retrieved from https://orbi.uliege.be/2268/180099.

Hambuckers, J., & Heuchenne, C. (07 December 2014). Identifying the best technical trading rule: a .632 bootstrap approach. Paper presented at 8th International Conference on Computational and Financial Econometrics and 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, Pisa, Italy.

Hambuckers, J., & Heuchenne, C. (2014). Estimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach. (Submitted version 20/11/2014). Eprint/Working paper retrieved from https://orbi.uliege.be/2268/172453.

Hambuckers, J., & Heuchenne, C. (2014). A new methodological approach for error distributions selection in Finance. (Submitted version 30/04/2014). Eprint/Working paper retrieved from https://orbi.uliege.be/2268/168735.

Hambuckers, J., & Heuchenne, C. (April 2014). A new methodological approach for error distributions selection in Finance. Paper presented at Skewness, Heavy Tails, Market Crashes, and Dynamics conference, Cambridge, United Kingdom.

Hambuckers, J., & Heuchenne, C. (15 December 2013). A new methodological approach for error distributions selection. Paper presented at 7th International Conference on Computational and Financial Econometrics and 6th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, United Kingdom.

Hambuckers, J., & Heuchenne, C. (November 2013). A new methodological approach for error distributions selection. Paper presented at IAP Project StUDyS seminars 2012-2017, Liège, Belgium.

Hambuckers, J., & Heuchenne, C. (30 April 2013). New issues for the Goodness-of-fit test of the error distribution : a comparison between Sinh-arscinh and Generalized Hyperbolic distribution. Paper presented at 4th Mathematical Finance Days 2013, Montréal, Canada.

Hambuckers, J., & Heuchenne, C. (19 April 2013). New issues for the Goodness-of-fit test of the error distribution : a comparison between Sinh-arcsinh and Generalized Hyperbolic distributions. Paper presented at Liège-Luxembourg-Maastricht Phd Workshop 2013, Luxemburg, Luxembourg.

Hambuckers, J. (23 October 2012). Comments to 'The time inconsistency factor: how banks adapt to their savers mix' (C. Laureti and A. Szafarz, working paper, 2012). Paper presented at Journée scientifique de rentrée de l'Ecole Doctorale Thématique en Sciences de Gestion ULB-ULg-UMONS, Mons, Belgium.

Hambuckers, J. (2011). Modélisation d'évènements rares à l'aide de distributions non normales : application en finance avec la fonction sinh-arcsinh. Unpublished master thesis, ULiège - Université de Liège.
Jury: Heuchenne, C. (Promotor), Van Caillie, D., ... Haesbroeck, G.