Prof. Dr. Axel Bücher

Lehr­stuhl­in­haber Mathematische Statistik

Adresse:
Ruhr-Uni­ver­si­tät Bo­chum
Fa­kul­tät für Ma­the­ma­tik
Lehr­stuhl für Mathematische Statistik
Ge­bäu­de IB 2/179
Uni­ver­si­täts­stra­ße 150
D-44780 Bo­chum

Te­le­fon:
+49 234/32-27548

E-Mail:
Axel(dot)Buecher(at)ruhr-uni-bochum(dot)de

Sprechzeiten

Nach Ver­ein­ba­rung

Über mich

Von 2003 bis 2008 habe ich Mathematik an der Ruhr-Universität Bochum studiert und im Anschluss meine Promotion unter der Betreuung von Prof. Holger Dette abgeschlossen. Mein Forschungsschwerpunkt lag dabei auf statistischen Verfahren für Copulafunktionen. Seitdem arbeite ich an vielfältigen Themen in der mathematischen Statistik. Zunächst war ich als wissenschaftlicher Mitarbeiter tätig und später wurde ich Teilprojektleiter in einem von der DFG finanzierten Sonderforschungsbereich in Bochum.

Nach einem PostDoc-Aufenthalt an der Université catholique de Louvain in Belgien im Jahr 2013 und zwei Professurvertretungen in Heidelberg und Dortmund, wurde ich 2018 auf eine W3-Professur für Mathematische Statistik an die Heinrich-Heine-Universität Düsseldorf berufen. Seit Oktober 2023 bin ich zurück an der Ruhr-Universität und hier ebenfalls als Professor für Mathematische Statistik tätig.

Arbeitsgebiete

  • Extremwertstatistik
  • Nichtparametrische Statistik, insbesondere für Copulafunktionen
  • Empirische Prozesse
  • Zeitreihenanalyse
  • Strukturbruchanalyse
  • Statistik für stochastische Prozesse

Publikationen

Zur Veröffentlichung eingereicht:

  1. Bücher, A. und Pakzad, C. (2024+):
    The empirical copula process in high dimensions: Stute's representation and applications.
    https://arxiv.org/abs/2405.05597
  2. Bücher, A. und Staud, T. (2023+):
    Limit theorems for non-degenerate U-statistics of block maxima for time series.
    https://arxiv.org/abs/2308.13761

In referierten Zeitschriften:

  1. Bücher, A. und Rosenstock, A. (2024+):
    Combined modelling of micro-leveloutstanding claim counts and individualclaim frequencies in general insurance.
    Erscheint in: European Actuarial Journal.
    https://doi.org/10.1007/s13385-024-00383-7
  2. Bücher, A. und Jennessen T. (2023+):
    Statistics for Heteroscedastic Time Series Extremes.
    Erscheint in: Bernoulli.
    https://arxiv.org/abs/2204.09534
  3. Bücher, A. und Pakzad, C. (2024):
    Testing for independence in high dimensions based on empirical copulas.
    Annals of Statistics, Vol. 52(1): 311-334.
    https://doi.org/10.1214/23-AOS2348
  4. Zanger, L., Bücher, A., Kreienkamp, F., Lorenz, P. und Tradowsky, J. (2024):
    Regional Pooling in Extreme Event Attribution Studies: an Approach Based on Multiple Statistical Testing.
    Extremes, Vol. 27, 1–32.
    https://doi.org/10.1007/s10687-023-00480-y
  5. Bücher, A. und Jennessen T. (2024):
    Weighted weak convergence of the sequential tail empirical process for heteroscedastic time series with an application to tail index estimation.
    Extremes, Vol. 27, 163–184.
    https://doi.org/10.1007/s10687-023-00476-8
  6. Bücher, A. und Zanger, L. (2023):
    On the Disjoint and Sliding Block Maxima method for piecewise stationary time series.
    Annals of Statistics, Vol. 51(2), 573-598
    https://doi.org/10.1214/23-AOS2260
  7. Bücher, A., Dette, H. und Heinrichs, F. (2023):
    A Portmanteau-type test for detecting serial correlation in locally stationary functional time series.
    Statistical Inference for Stochastic Processes, Vol. 26, 255–278
    https://doi.org/10.1007/s11203-022-09285-5
  8. Bücher, A., Genest, C., Lockhart, R., und Nešlehová, J. (2023):
    Asymptotic behavior of an intrinsic rank-based estimator of the Pickands dependence function constructed from B-splines.
    Extremes, Vol. 26, 101–138
    https://doi.org/10.1007/s10687-022-00451-9
  9. Lilienthal, J., Zanger, L., Bücher, A. und Fried, R. (2022):
    A note on statistical tests for homogeneities in multivariate extreme value models for block maxima.
    Environmetrics, e2746.
    https://doi.org/10.1002/env.2746
  10. Bücher, A. und Rosenstock, A. (2023):
    Micro-level Prediction of Outstanding Claim Counts using Neural Networks.
    European Actuarial Journal, Vol. 13, 55–90
    https://doi.org/10.1007/s13385-022-00314-4
  11. Bücher, A. und Jennessen T. (2022):
    Statistical analysis for stationary time series at extreme levels: new estimators for the limiting cluster size distribution.
    Stochastic Processes and their Applications, Vol. 149, 75-106.
    https://doi.org/10.1016/j.spa.2022.03.004
  12. Bücher, A., Dette, H. und Heinrichs, F. (2021):
    Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators.
    Annals of Statistics, Vol. 49, No. 6, 3583-3617.
    http://dx.doi.org/10.1214/21-AOS2098
  13. Bücher A. Jaser, M. und Min, A. (2021):
    Detecting departures from meta-ellipticity for multivariate stationary time series.
    Dependence Modeling, Vol. 9, No. 1, 121-140.
    https://doi.org/10.1515/demo-2021-0105
  14. Bücher, A. und Zhou, C. (2021):
    A horse race between the block maxima method and the peak-over-threshold approach.
    Statistical Science, Vol. 36, No. 3, 360-378.
    https://doi.org/10.1214/20-STS795
  15. Bücher, A., Fried, R., Kinsvater, P. und Lilienthal, J. (2021):
    Penalized Quasi-Maximum-Likelihood Estimation for Extreme Value Models with Application to Flood Frequency Analysis.
    Extremes, Vol. 24, 325–348.
    http://dx.doi.org/10.1007/s10687-020-00379-y
  16. Bücher, A., Volgushev, S. und Zou, N. (2021):
    Multiple block sizes and overlapping blocks for multivariate time series extremes.
    Annals of Statistics, Vol. 49, No. 1, 295-320.
    http://dx.doi.org/10.1214/20-AOS1957
  17. Bücher, A. und Jennessen T. (2020):
    Method of moments estimators for the extremal index of a stationary time series.
    Electronic Journal Of Statistics, Vol. 14, No. 2, 3103-3156.
    https://doi.org/10.1214/20-EJS1734
  18. Bücher, A., Dette, H. und Heinrichs, F. (2020):
    Detecting deviations from second-order stationarity in locally stationary functional time series.
    Annals of the Institute of Statistical Mathematics, Vol. 72(4), 1055-1094.
    https://doi.org/10.1007/s10463-019-00721-7
  19. Bücher, A., Posch, P. N. und Schmidtke, P. (2020):
    Using the Extremal Index for Value-at-Risk Backtesting.
    Journal of Financial Econometrics, Vol. 18 (3), 556–584.
    https://doi.org/10.1093/jjfinec/nbaa011
  20. Bücher, A., Volgushev, S. und Zou, N. (2019):
    On second order conditions in the multivariate block maxima and peak over threshold method.
    Journal of Multivariate Analysis, Vol. 173, 604-619.
    https://doi.org/10.1016/j.jmva.2019.04.011
  21. Bücher, A., Fermanian, J.-D. und Kojadinovic, I. (2019):
    Combining cumulative sum change-point detection tests for assessing the stationarity of univariate time series.
    Journal of Time Series Analysis, Vol. 40, 124-150.
    https://doi.org/10.1111/jtsa.12431
  22. Bücher, A. und Kojadinovic, I. (2019):
    A note on conditional versus joint unconditional weak convergence in bootstrap consistency results.
    Journal of Theoretical Probability, Vol. 32(3), 1145-1165.
    https://doi.org/10.1007/s10959-018-0823-3
  23. Berghaus, B. und Bücher, A. (2018):
    Weak Convergence of a Pseudo Maximum Likelihood Estimator for the Extremal Index.
    Annals of Statistics, Vol. 46(5), 2307-2335.
    https://doi.org/10.1214/17-AOS1621
  24. Bücher, A. und Segers, J. (2018):
    Inference for heavy tailed stationary time series based on sliding blocks.
    Electronic Journal of Statistics, Vol. 12(1), 1098–1125.
    https://doi.org/10.1214/18-EJS1415
  25. Bücher, A. und Segers, J. (2018):
    Maximum likelihood estimation for the Fréchet distribution based on block maxima extracted from a time series.
    Bernoulli Vol. 24(2), 1427–1462.
    https://doi.org/10.3150/16-BEJ903
  26. Bücher, A. und Segers, J. (2017):
    On the maximum likelihood estimator for the Generalized Extreme-Value distribution.
    Extremes, Vol. 20(4), 839–872.
    https://doi.org/10.1007/s10687-017-0292-6
  27. Bücher, A., Irresberger, F. und Weiß, G. (2017):
    Testing Asymmetry in Dependence with Copula-Coskewness.
    North American Actuarial Journal, Vol. 21, 267–280.
    https://doi.org/10.1080/10920277.2017.1282876
  28. Bücher, A., Kinsvater, P. und Kojadinovic, I. (2017):
    Detecting breaks in the dependence of multivariate extreme-value distributions.
    Extremes, Vol. 20(1), 53-89.
    https://doi.org/10.48550/arXiv.1505.00954
  29. Berghaus, B. und Bücher, A. (2017):
    Goodness-of-fit tests for multivariate copula-based time series models.
    Econometric Theory, Vol. 33(2), 292–330.
    https://doi.org/10.1017/S0266466615000419
  30. Berghaus, B., Bücher, A. und Volgushev, S. (2017):
    Weak convergence of the empirical copula process with respect to weighted metrics.
    Bernoulli, Vol. 23(1), 743–772.
    https://doi.org/10.3150/15-BEJ751
  31. Bücher, A., Hoffmann, M., Vetter, M. und Dette, H. (2017):
    Nonparametric tests for detecting breaks in the jump behaviour of a time-continuous process.
    Bernoulli, Vol. 23(2), 1335–1364.
    https://doi.org/10.3150/15-BEJ780
  32. Bücher, A. und Kojadinovic, I. (2016):
    A dependent multiplier bootstrap for the sequential empirical copula process under strong mixing.
    Bernoulli, Vol. 22(2), 927–968.
    https://doi.org/10.3150/14-BEJ682
  33. Bücher, A., Jäschke, S. und Wied, D. (2015):
    Nonparametric tests for constant tail dependence with an application to energy and finance.
    Journal of Econometrics, Vol. 187(1), 154–168.
    https://doi.org/10.1016/j.jeconom.2015.02.002
  34. Bücher, A. (2015):
    A note on weak convergence of the sequential multivariate empirical process under strong mixing.
    Journal of Theoretical Probability, Vol. 28(3), 1028–1037.
    https://doi.org/10.1007/s10959-013-0529-5
  35. Bücher, A. und Kojadinovic, I. (2015):
    Dependent multiplier bootstraps for nondegenerate U-statistics under mixing conditions with applications.
    Journal of Statistical Planning and Inference, Vol. 170, 83–105.
    https://doi.org/10.1016/j.jspi.2015.09.006
  36. Bücher, A., Segers, J. und Volgushev, S. (2014):
    When uniform weak convergence fails: empirical processes for dependence functions and residuals via epi- and hypographs.
    Annals of Statistics, Vol. 42, 1598–1634.
    https://doi.org/10.1214/14-AOS1237
  37. Bücher, A. und Segers, J. (2014):
    Extreme value copula estimation based on block maxima of a multivariate stationary time series.
    Extremes, Vol. 13, 495–528.
    https://doi.org/10.1007/s10687-014-0195-8
  38. Bücher, A. (2014):
    A note on nonparametric estimation of bivariate tail dependence.
    Statistics & Risk Modeling, Vol. 31, 151–162.
    https://doi.org/10.1515/strm-2013-1143
  39. Bücher, A., Kojadinovic, I., Rohmer, T. und Segers, J. (2014):
    Detecting changes in cross-sectional dependence in multivariate time series.
    Journal of Multivariate Analysis, Vol. 132, 111–128.
    https://doi.org/10.1016/j.jmva.2014.07.012
  40. Berghaus, B. und Bücher, A. (2014):
    Nonparametric tests for tail monotonicity.
    Journal of Econometrics, Vol. 180(2), 117–126.
    https://doi.org/10.1016/j.jeconom.2014.03.005
  41. Bücher, A. und Vetter, M. (2013):
    Nonparametric Inference on Lévy measures and copulas.
    Annals of Statistics, Vol. 41, 1485–1515.
    https://doi.org/10.1214/13-AOS1116
  42. Bücher, A. und Dette, H. (2013):
    Multiplier bootstrap of tail copulas – with applications.
    Bernoulli, Vol. 5(A), 1655–1687.
    https://doi.org/10.3150/12-BEJ425
  43. Bücher, A. und Ruppert, M. (2013):
    Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique.
    Journal of Multivariate Analysis, Vol. 116, 208–229.
    https://doi.org/10.1016/j.jmva.2012.12.002
  44. Bücher, A. und Volgushev, S. (2013):
    Empirical and sequential empirical copula processes under serial dependence.
    Journal of Multivariate Analysis, Vol. 119, 61–70.
    https://doi.org/10.1016/j.jmva.2013.04.003
  45. Berghaus, B., Bücher, A. und Dette H. (2013):
    Minimum distance estimators of the Pickands dependence function and related tests of multivariate extreme-value dependence.
    Journal de la Societé Francaise de Statistique, Vol. 154, 116– 137.
    http://www.numdam.org/item/JSFS_2013__154_1_116_0/
  46. Bücher, A., Dette, H. und Volgushev, S. (2012):
    A test for Archimedeanity in bivariate copula models.
    Journal of Multivariate Analysis, Vol. 110, 121–132.
    https://doi.org/10.1016/j.jmva.2012.01.026
  47. Bücher, A., Dette, H. und Volgushev, S. (2011):
    New estimators of the Pickands dependence function and a test for extreme-value dependence.
    Annals of Statistics, Vol. 39, No. 4, 1963–2006.
    https://doi.org/10.1214/11-AOS890
  48. Bücher, A., Dette, H. und Wieczorek, G. (2011):
    Testing model assumptions in functional regression models.
    Journal of Multivariate Analysis, Vol. 102, 1472– 1488.
    https://doi.org/10.1016/j.jmva.2011.05.014
  49. Bücher, A. und Dette, H. (2010):
    A note on bootstrap approximations for the empirical copula process.
    Statistics and Probability Letters, Vol. 80, 1925–1932.
    https://doi.org/10.1016/j.spl.2010.08.021
  50. Bücher, A. und Dette, H. (2010):
    Some comments on goodness-of-fit tests for the parametric form of the copula based on L2-distances.
    Journal of Multivariate Analysis, Vol. 101, 749–763.
    https://doi.org/10.1016/j.jmva.2009.09.014

Referierte Buchkapitel:

  1. Bücher, A., El Ghouch, A. und Van Keilegom, I. (2021):
    Single-index quantile regression models for censored data. In: Daouia A., Ruiz-Gazen A. (eds)Advances in Contemporary Statistics and Econometrics.
    Springer, Cham,
    177–196.
    https://link.springer.com/chapter/10.1007/978-3-030-73249-3_10
  2. Bücher, A. und Kojadinovic, I. (2015):
    An overview of nonparametric tests of extremevalue dependence. In: Dey, D. and Yan, J: Extreme Value Modeling and Risk Analysis: Methods and Applications.
    Crc Press Inc
    , 2015, 377–398.
    https://arxiv.org/abs/1410.6784

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