Publications and communications of Julien Hambuckers

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. (In press). Non-Standard Errors. Journal of Finance.

Hambuckers, J., & Ulm, M. (December 2023). On the role of interest rate differentials in the dynamic asymmetry of exchange rates. Economic Modelling, 129.

Hambuckers, J., Kratz, M., & Usseglio-Carleve, A. (18 August 2023). Efficient estimation for extreme value regression models of tail risks [Paper presentation]. Japanese Association of Financial Econometrics and Engineering International Symposium on Quantitative Finance, Tokyo, Japan.

Hübner, P., & Hambuckers, J. (01 August 2023). Hedge funds systemic risks: Which factors matter? [Paper presentation]. 6th International Conference on Econometrics and Statistics (EcoSta 2023).

Hübner, P., & Hambuckers, J. (29 June 2023). Hedge funds systemic risks: which factors matter? [Paper presentation]. 9th Annual Conference of the International Association for Applied Econometrics (IAAE), Oslo, Norway.

Ulm, M., & Hambuckers, J. (28 June 2023). Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model [Paper presentation]. Annual Conference of the International Association for Applied Econometrics (IAAE), Oslo, Norway.

Crucil, R., Hambuckers, J., & Maxand Simone. (27 June 2023). Do monetary policy shocks affect financial uncertainty? A non-Gaussian proxy SVAR approach [Paper presentation]. IAAE Annual Conference (Oslo 2023), Oslo, Norway.

Hambuckers, J., Kratz, M., & Usseglio-Carleve, A. (June 2023). Efficient estimation in extreme value regression models of hedge funds tail risks [Paper presentation]. Extreme Value Analysis conference 2023, Milan, Italy.

Crucil, R., Hambuckers, J., & Maxand Simone. (08 May 2023). Do monetary policy shocks affect financial uncertainty? A non-Gaussian proxy SVAR approach [Paper presentation]. Internationan Francqui Chair: Causal Inference in Macroeconomics.

Crucil, R., Hambuckers, J., & Maxand, S. (04 May 2023). Do monetary policy shocks affect financial uncertainty? A non-Gaussian proxy SVAR approach [Paper presentation]. HEC Liège Research Day 2023, Liège, Belgium.

Crucil, R., Hambuckers, J., & Maxand, S. (21 April 2023). Do monetary policy shocks affect financial uncertainty ? A non-Gaussian proxy-SVAR approach [Paper presentation]. 2023 Belgian Financial Research Forum (BFRF), Bruxelles, Belgium.

Hübner, P., & Hambuckers, J. (20 April 2023). Measuring the contribution of hedge funds to banks’ systemic risk: an extreme value approach [Paper presentation]. Belgian Financial Research Forum.

Crucil, R., Hambuckers, J., & Maxand Simone. (2023). Do monetary policy shocks affect financial uncertainty? A non-Gaussian proxy SVAR approach [Paper presentation]. International Francqui Chair: Causal Inference in Macroeconomics, Bruxelles, Belgium.

Hambuckers, J., & Kneib, T. (2023). Smooth-transition regression models for non-stationary extremes. Journal of Financial Econometrics, 21 (2), 445-484.

Wiemann, P., Kneib, T., & Hambuckers, J. (2023). Using the softplus function to construct alternative link functions in generalized linear models and beyond. Statistical Papers. doi:10.1007/s00362-023-01509-x

Hambuckers, J., & Hübner, P. (18 December 2022). Which hedge funds are systemically risky, and when: A dynamic extreme value regression approach [Paper presentation]. 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 presentation]. 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 presentation]. 2022 EcoStat conference, Kyoto, Japan.

Mhalla, L., Hambuckers, J., & Lambert, M. (June 2022). Extremal connectedness of hedge funds [Paper presentation]. 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., Kratz, M., & Usseglio-Carleve, A. (2022). Automatic threshold selection for extreme value regression models [Paper presentation]. 24th International Conference on Computational Statistics (COMPSTAT), Bologna, Italy.

Hambuckers, J., Sun, L., & Trapin, L. (2022). Non-stationary variable selection in time-varying extreme Value regression [Poster presentation]. 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, 37 (5), 988-1009. doi:10.1002/jae.2900

Sun, L., Hecq, A., Straetmans, S., & Hambuckers, J. (2022). VAR for VaR and CoVaR [Paper presentation]. 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 presentation]. HEC Lausanne - UNIL, séminaire du Département des Opérations, Lausanne, Switzerland.

Hambuckers, J., & Ulm, M. (24 June 2021). Interest rate differentials and the dynamic asymmetry of exchange rates [Paper presentation]. 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 presentation]. 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

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. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/256895.

Mhalla, L., Hambuckers, J., & Lambert, M. (11 December 2020). Extremal connectedness and systemic risk of hedge funds [Paper presentation]. 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 presentation]. 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). ORBi-University of Liège. https://orbi.uliege.be/handle/2268/257209.

Hambuckers, J., & Ulm, M. (2020). Interest rate differentials and the dynamic asymmetry of exchange rates. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/257214.

Mhalla, L., Hambuckers, J., & Lambert, M. (2020). Extremal connectedness and systemic risk of hedge funds. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/252040.

Hambuckers, J., & Ulm, M. (02 December 2019). Interest rate differentials and the dynamic asymmetry of exchange rates [Paper presentation]. 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 presentation]. 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 presentation]. 6th Annual Conference of the International Association for Applied Econometrics, Nicosia, Cyprus.

Hambuckers, J., & Ulm, M. (2019). Interest rate differentials. ORBi-University of Liège. https://orbi.uliege.be/handle/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 presentation]. 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 presentation]. 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. ORBi-University of Liège. https://orbi.uliege.be/handle/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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 2017 IWSM conference, Groeningen, Netherlands.

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

Hambuckers, J. (June 2017). Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach [Paper presentation]. 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 presentation]. 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 presentation]. ERCIM 2016, Seville, Spain.

Hambuckers, J. (August 2016). A semiparametric model for Generalized Pareto regressions, based on a dimension reduction assumption [Paper presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 8th Annual Society for Financial Econometrics Conference, Aarhus, Denmark.

Hambuckers, J. (2015). Nonparametric and bootstrap techniques applied to financial risk modeling [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/180100

Hambuckers, J., Heuchenne, C., & Lopez, O. (2015). A semiparametric model for Generalized Pareto regression based on a dimension reduction assumption. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/180099.

Hambuckers, J., & Heuchenne, C. (07 December 2014). Identifying the best technical trading rule: a .632 bootstrap approach [Paper presentation]. 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). ORBi-University of Liège. https://orbi.uliege.be/handle/2268/172453.

Hambuckers, J., & Heuchenne, C. (2014). A new methodological approach for error distributions selection in Finance. (Submitted version 30/04/2014). ORBi-University of Liège. https://orbi.uliege.be/handle/2268/168735.

Hambuckers, J., & Heuchenne, C. (April 2014). A new methodological approach for error distributions selection in Finance [Paper presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 presentation]. 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 [Master’s dissertation, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/133099