Profil

Hambuckers Julien

HEC Liège : UER > UER Finance et Droit : Finance de Marché

HEC Liège Research: Financial Management for the Future

See author's contact details
Main Referenced Co-authors
Heuchenne, Cédric  (15)
Kneib, Thomas (11)
Kratz, Marie (10)
Usseglio-Carleve, Antoine (10)
Lambert, Marie  (8)
Main Referenced Keywords
error distribution (8); operational loss (7); semiparametric (7); operational losses (6); operational risk (6);
Main Referenced Unit & Research Centers
QuantOM (4)
Centre for Quantitative Methods and Operation Management (QuantOM) (2)
Chair of Statistics, Faculty of Business and Economics (University of Göttingen) (2)
Asset and Risk Management (1)
Asset and Risk Management (HEC Recherche) (1)
Main Referenced Disciplines
Quantitative methods in economics & management (65)
Finance (15)
Macroeconomics & monetary economics (9)
Environmental sciences & ecology (4)
Special economic topics (health, labor, transportation...) (2)

Publications (total 90)

The most downloaded
560 downloads
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 https://hdl.handle.net/2268/186808

The most cited

28 citations (Scopus®)

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 https://hdl.handle.net/2268/253701

Hambuckers, J. (12 August 2024). Instrument-free endogeneity correction for beyond-the-mean regression, with application to sectorial Growth-at-Risk estimation [Paper presentation]. Bernouilli-IMS 11th World Congress in Probability and Statistics, Bochum, Germany.
Peer reviewed

Hambuckers, J., Kratz, M., & Usseglio-Carleve, A. (03 July 2024). Efficient estimation in extreme value regression models of hedge funds tail risks [Paper presentation]. ESSEC CREAR seminar, Paris, France.

Crucil, R., Hambuckers, J., & Ulm, M. (07 June 2024). Does monetary policy influence the uncertainty of financial markets? [Paper presentation]. HEC Liège FM4F seminars.

Hambuckers, J. (22 May 2024). LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape for finance [Paper presentation]. Louvain Finance seminar, Louvain-la-Neuve, Belgium.

Hambuckers, J., & Hübner, P. (2024). Measuring the time-varying systemic risks of hedge funds. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/316747.

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. (2024). Non-Standard Errors. Journal of Finance, 79, 2339-2390.
Peer Reviewed verified by ORBi

Hambuckers, J., Kratz, M., & Usseglio-Carleve, A. (2024). Efficient estimation in extreme value regression models of hedge funds tail risks. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/316771.

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. (December 2023). Efficient estimation in extreme value regression models of hedge funds tail risks [Paper presentation]. Quantitative Economics seminar at UMaastricht, Maastricht, Netherlands.

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

Crucil, R., Hambuckers, J., & Maxand, S. (2023). Do Monetary Policy Shocks Affect Financial Uncertainty? A Non-gaussian Proxy SVAR Approach. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/316669. doi:10.2139/ssrn.4469420

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]. International 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

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

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

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

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

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., 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

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., 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

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.

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

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. (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., 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. (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., 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., & 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. (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

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