  | Hambuckers, J., & Ulm, M. (December 2023). On the role of interest rate differentials in the dynamic asymmetry of exchange rates. Economic Modelling, 129.  Peer Reviewed verified by ORBi |
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. Peer reviewed |
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). Editorial reviewed |
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. Peer reviewed |
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. Peer reviewed |
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. Peer reviewed |
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. Peer reviewed |
 | 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. Peer reviewed |
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. Peer reviewed |
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. Peer reviewed |
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. Peer reviewed |
  | 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. (2023). Non-Standard Errors. Journal of Finance. Peer Reviewed verified by ORBi |
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. Peer reviewed |
 | 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 Peer Reviewed verified by ORBi |
 | Hambuckers, J., & Kneib, T. (2023). Smooth-transition regression models for non-stationary extremes. Journal of Financial Econometrics, 21 (2), 445-484. Peer Reviewed verified by ORBi |
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. Editorial reviewed |
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. Editorial reviewed |
Mhalla, L., Hambuckers, J., & Lambert, M. (June 2022). Extremal connectedness of hedge funds [Paper presentation]. Quantitative Finance and Financial Econometrics (QFFE) conference, Marseille, France. Peer reviewed |
 | 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 Peer reviewed |
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. Editorial reviewed |
 | 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 Peer Reviewed verified by ORBi |
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. |
 | 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 Peer Reviewed verified by ORBi |
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. Editorial reviewed |
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). Peer reviewed |
 | 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 Peer Reviewed verified by ORBi |
 | 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 Peer Reviewed verified by ORBi |
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 Peer Reviewed verified by ORBi |
 | 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. |
 | 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 Peer Reviewed verified by ORBi |
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). |
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. |
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. |
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 Peer Reviewed verified by ORBi |
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. Editorial reviewed |
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. Peer reviewed |
 | 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. Peer reviewed |
 | 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 Peer Reviewed verified by ORBi |
 | 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 Peer Reviewed verified by ORBi |
 | 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 Peer Reviewed verified by ORBi |
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. Editorial reviewed |
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. Peer reviewed |
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. (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., 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 Peer Reviewed verified by ORBi |
 | 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 Peer Reviewed verified by ORBi |
Hambuckers, J. (December 2017). On conditional dynamic skewness and directional forecast of currency exchange rates [Paper presentation]. 2017 ERCIM - CMstatistics conference, London, United Kingdom. Editorial reviewed |
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. Peer reviewed |
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. Peer reviewed |
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. Peer reviewed |
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. Editorial reviewed |
 | 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 Peer Reviewed verified by ORBi |
 | 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 Peer Reviewed verified by ORBi |
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. Editorial reviewed |
Hambuckers, J. (August 2016). A semiparametric model for Generalized Pareto regressions, based on a dimension reduction assumption [Paper presentation]. COMPSTAT 2016, Oviedo, Spain. Editorial reviewed |
 | 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 Peer Reviewed verified by ORBi |
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. Editorial reviewed |
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. Peer reviewed |
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. Peer reviewed |
 | 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. Editorial reviewed |
 | 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. Peer reviewed |
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 |