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Julien Hambuckers

Personal Details

First Name:Julien
Middle Name:
Last Name:Hambuckers
Suffix:
RePEc Short-ID:pha1318
[This author has chosen not to make the email address public]

Affiliation

(50%) HEC École de Gestion
Université de Liège

Liège, Belgium
http://www.hec.ulg.ac.be/
RePEc:edi:feulgbe (more details at EDIRC)

(50%) Centre de Méthodes Quantitatives et Operations Management (QuantOM)
HEC École de Gestion
Université de Liège

Liège, Belgium
http://www.quantom.hec.ulg.ac.be/
RePEc:edi:geulgbe (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Marco Bee & Julien Hambuckers & Luca Trapin, 2019. "An improved approach for estimating large losses in insurance analytics and operational risk using the g-and-h distribution," DEM Working Papers 2019/11, Department of Economics and Management.
  2. Andreas Groll & Julien Hambuckers & Thomas Kneib & Nikolaus Umlauf, 2018. "LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape," Working Papers 2018-16, Faculty of Economics and Statistics, Universität Innsbruck.
  3. Marco Bee & Julien Hambuckers & Luca Trapin, 2018. "Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach," DEM Working Papers 2018/08, Department of Economics and Management.
  4. Hambuckers, Julien & Heuchenne, Cedric, 2017. "A robust statistical approach to select adequate error distributions for financial returns," LIDAM Reprints ISBA 2017031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  5. Hambuckers, J. & Heuchenne, Cedric, 2016. "Estimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach," LIDAM Reprints ISBA 2016028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  6. Hambuckers, Julien & Heuchenne, Cedric, 2014. "A new methodological approach for error distributions selection in Finance," LIDAM Discussion Papers ISBA 2014052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

Articles

  1. Lurkin, Virginie & Hambuckers, Julien & van Woensel, Tom, 2021. "Urban low emissions zones: A behavioral operations management perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 222-240.
  2. M. Bee & J. Hambuckers & L. Trapin, 2019. "Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1255-1266, August.
  3. Groll, Andreas & Hambuckers, Julien & Kneib, Thomas & Umlauf, Nikolaus, 2019. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 140(C), pages 59-73.
  4. J. Hambuckers & T. Kneib & R. Langrock & A. Silbersdorff, 2018. "A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1679-1698, October.
  5. Julien Hambuckers & Andreas Groll & Thomas Kneib, 2018. "Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 898-935, September.
  6. J. Hambuckers & C. Heuchenne, 2017. "A robust statistical approach to select adequate error distributions for financial returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 137-161, January.
  7. Julien Hambuckers & Cédric Heuchenne, 2016. "Estimating the Out‐of‐Sample Predictive Ability of Trading Rules: A Robust Bootstrap Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(4), pages 347-372, July.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Julien Hambuckers & Andreas Groll & Thomas Kneib, 2018. "Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 898-935, September.

    Mentioned in:

    1. Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach (Journal of Applied Econometrics 2018 ) in ReplicationWiki ()

Working papers

  1. Andreas Groll & Julien Hambuckers & Thomas Kneib & Nikolaus Umlauf, 2018. "LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape," Working Papers 2018-16, Faculty of Economics and Statistics, Universität Innsbruck.

    Cited by:

    1. Barbagli, Matteo & François, Pascal & Gauthier, Geneviève & Vrins, Frédéric, 2024. "The role of CDS spreads in explaining bond recovery rates," LIDAM Discussion Papers LFIN 2024002, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
    3. Hendrik van der Wurp & Andreas Groll, 2023. "Introducing LASSO-type penalisation to generalised joint regression modelling for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 127-151, March.
    4. Muschinski, Thomas & Mayr, Georg J. & Simon, Thorsten & Umlauf, Nikolaus & Zeileis, Achim, 2024. "Cholesky-based multivariate Gaussian regression," Econometrics and Statistics, Elsevier, vol. 29(C), pages 261-281.
    5. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    6. Marco Bee & Julien Hambuckers & Flavio Santi & Luca Trapin, 2021. "Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach," Computational Statistics, Springer, vol. 36(3), pages 2177-2200, September.
    7. M. Carvalho & S. Pereira & P. Pereira & P. Zea Bermudez, 2022. "An Extreme Value Bayesian Lasso for the Conditional Left and Right Tails," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 222-239, June.
    8. Linda Mhalla & Julien Hambuckers & Marie Lambert, 2022. "Extremal connectedness of hedge funds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 988-1009, August.
    9. Paul F. V. Wiemann & Thomas Kneib & Julien Hambuckers, 2024. "Using the softplus function to construct alternative link functions in generalized linear models and beyond," Statistical Papers, Springer, vol. 65(5), pages 3155-3180, July.
    10. Amon, Julian & Hornik, Kurt, 2022. "Is it all bafflegab? – Linguistic and meta characteristics of research articles in prestigious economics journals," Journal of Informetrics, Elsevier, vol. 16(2).

  2. Marco Bee & Julien Hambuckers & Luca Trapin, 2018. "Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach," DEM Working Papers 2018/08, Department of Economics and Management.

    Cited by:

    1. Marco Bee & Julien Hambuckers & Luca Trapin, 2019. "An improved approach for estimating large losses in insurance analytics and operational risk using the g-and-h distribution," DEM Working Papers 2019/11, Department of Economics and Management.
    2. Marco Bee, 2022. "The truncated g-and-h distribution: estimation and application to loss modeling," Computational Statistics, Springer, vol. 37(4), pages 1771-1794, September.

  3. Hambuckers, Julien & Heuchenne, Cedric, 2017. "A robust statistical approach to select adequate error distributions for financial returns," LIDAM Reprints ISBA 2017031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Paul R. Dewick, 2022. "On Financial Distributions Modelling Methods: Application on Regression Models for Time Series," JRFM, MDPI, vol. 15(10), pages 1-15, October.

Articles

  1. Lurkin, Virginie & Hambuckers, Julien & van Woensel, Tom, 2021. "Urban low emissions zones: A behavioral operations management perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 222-240.

    Cited by:

    1. Stefano Bortolomiol & Virginie Lurkin & Michel Bierlaire, 2022. "Price-based regulation of oligopolistic markets under discrete choice models of demand," Transportation, Springer, vol. 49(5), pages 1441-1463, October.
    2. Usman Ahmed & Matthew J. Roorda, 2023. "Joint and sequential models for freight vehicle type and shipment size choice," Transportation, Springer, vol. 50(5), pages 1613-1629, October.
    3. Sluijk, Natasja & Florio, Alexandre M. & Kinable, Joris & Dellaert, Nico & Van Woensel, Tom, 2023. "Two-echelon vehicle routing problems: A literature review," European Journal of Operational Research, Elsevier, vol. 304(3), pages 865-886.
    4. Orhan, Cosku Can & Goez, Julio Cesar & Guajardo, Mario & Osicka, Ondrej & Wallace, Stein W., 2024. "Assessing macro effects of freight consolidation on the livability of small cities using vehicle routing as micro models: The case of Bergen, Norway," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    5. Gonzalez, Juan Nicolas & Gomez, Juan & Vassallo, Jose Manuel, 2023. "Are low emission zones and on-street parking management effective in reducing parking demand for most polluting vehicles and promoting greener ones?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    6. Choi, Minje & Ku, DongGyun & Kim, Sion & Kwak, Juhyeon & Jang, Yoonjung & Lee, Doyun & Lee, Seungjae, 2023. "Action plans on the reduction of mobility energy consumption based on personal mobility activation," Energy, Elsevier, vol. 263(PD).
    7. Balaguer, Jacint & Pernías, José C. & Ripollés, Jordi, 2023. "Is vehicle scrapping affected by low-emission zones? The case of Madrid," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    8. Maha Attia & Taslim Alade & Shady Attia, 2023. "The Influence of Passenger Car Banning Policies on Modal Shifts: Rotterdam’s Case Study," Sustainability, MDPI, vol. 15(9), pages 1-23, April.

  2. M. Bee & J. Hambuckers & L. Trapin, 2019. "Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1255-1266, August.
    See citations under working paper version above.
  3. Groll, Andreas & Hambuckers, Julien & Kneib, Thomas & Umlauf, Nikolaus, 2019. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 140(C), pages 59-73.
    See citations under working paper version above.
  4. J. Hambuckers & T. Kneib & R. Langrock & A. Silbersdorff, 2018. "A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1679-1698, October.

    Cited by:

    1. Timo Adam & Roland Langrock & Christian H. Weiß, 2019. "Penalized estimation of flexible hidden Markov models for time series of counts," METRON, Springer;Sapienza Università di Roma, vol. 77(2), pages 87-104, August.
    2. Francesca Biagini & Tobias Huber & Johannes G. Jaspersen & Andrea Mazzon, 2021. "Estimating extreme cancellation rates in life insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(4), pages 971-1000, December.
    3. Antonello Maruotti & Antonio Punzo, 2021. "Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies," International Statistical Review, International Statistical Institute, vol. 89(3), pages 447-480, December.
    4. Michels, Rouven & Ötting, Marius & Langrock, Roland, 2023. "Bettors’ reaction to match dynamics: Evidence from in-game betting," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1118-1127.
    5. Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).

  5. Julien Hambuckers & Andreas Groll & Thomas Kneib, 2018. "Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 898-935, September.

    Cited by:

    1. James, Robert & Leung, Henry & Leung, Jessica Wai Yin & Prokhorov, Artem, 2023. "Forecasting tail risk measures for financial time series: An extreme value approach with covariates," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 29-50.
    2. Hendrik van der Wurp & Andreas Groll, 2023. "Introducing LASSO-type penalisation to generalised joint regression modelling for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 127-151, March.
    3. Marco Bee & Julien Hambuckers & Luca Trapin, 2018. "Estimating Value-at-Risk for the g-and-h distribution: an indirect inference approach," DEM Working Papers 2018/08, Department of Economics and Management.
    4. Francesca Biagini & Tobias Huber & Johannes G. Jaspersen & Andrea Mazzon, 2021. "Estimating extreme cancellation rates in life insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(4), pages 971-1000, December.
    5. Gu, Zheng & Li, Yunxian & Zhang, Minghui & Liu, Yifei, 2023. "Modelling economic losses from earthquakes using regression forests: Application to parametric insurance," Economic Modelling, Elsevier, vol. 125(C).
    6. Andreas Groll & Julien Hambuckers & Thomas Kneib & Nikolaus Umlauf, 2018. "LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape," Working Papers 2018-16, Faculty of Economics and Statistics, Universität Innsbruck.
    7. Marco Bee & Julien Hambuckers & Luca Trapin, 2019. "An improved approach for estimating large losses in insurance analytics and operational risk using the g-and-h distribution," DEM Working Papers 2019/11, Department of Economics and Management.
    8. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation In Extreme Value Regression Models Of Hedge Fund Tail Risks," Working Papers hal-04090916, HAL.
    9. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation in Extreme Value Regression Models of Hedge Fund Tail Risks," Papers 2304.06950, arXiv.org.
    10. Julien Hambuckers & Li Sun & Luca Trapin, 2023. "Measuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors," Papers 2301.01362, arXiv.org.
    11. Marco Bee & Julien Hambuckers & Flavio Santi & Luca Trapin, 2021. "Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach," Computational Statistics, Springer, vol. 36(3), pages 2177-2200, September.
    12. Linda Mhalla & Julien Hambuckers & Marie Lambert, 2022. "Extremal connectedness of hedge funds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 988-1009, August.

  6. J. Hambuckers & C. Heuchenne, 2017. "A robust statistical approach to select adequate error distributions for financial returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 137-161, January.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (3) 2018-09-10 2018-12-24 2019-07-15
  2. NEP-ORE: Operations Research (3) 2018-09-10 2018-12-24 2019-07-15
  3. NEP-RMG: Risk Management (2) 2018-12-24 2019-07-15
  4. NEP-IAS: Insurance Economics (1) 2019-07-15

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