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David Wozabal

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Personal Details

First Name:David
Middle Name:
Last Name:Wozabal
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RePEc Short-ID:pwo178
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http://homepage.univie.ac.at/david.wozabal/

Affiliation

Institut für Betriebswirtschaftslehre
Fakultät für Wirtschaftswissenschaften
Universität Wien

Wien, Austria
https://ebusiness.univie.ac.at/
RePEc:edi:ibwwuat (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. David Wozabal & Ronald Hochreiter, 2009. "A Coupled Markov Chain Approach to Credit Risk Modeling," Papers 0911.3802, arXiv.org, revised Jan 2014.

Articles

  1. Georg Pflug & David Wozabal, 2007. "Ambiguity in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 435-442.

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.

Working papers

  1. David Wozabal & Ronald Hochreiter, 2009. "A Coupled Markov Chain Approach to Credit Risk Modeling," Papers 0911.3802, arXiv.org, revised Jan 2014.

    Cited by:

    1. Yibei Li & Ximei Wang & Boualem Djehiche & Xiaoming Hu, 2019. "Credit Scoring by Incorporating Dynamic Networked Information," Papers 1905.11795, arXiv.org, revised Oct 2019.
    2. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2016. "Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 989-1007, December.
    3. R. Dolzhenko A. & Р. Долженко А., 2018. "Ключевые Показатели Эффективности Работы С Проблемными Активами Банка И Их Расчет // Key Performance Indicators Of The Bank’S Distressed Assets And Their Calculation," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 130-145.
    4. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    5. W. Hölzl & S. Kaniovski & Y. Kaniovski, 2019. "Exploring the dynamics of business survey data using Markov models," Computational Management Science, Springer, vol. 16(4), pages 621-649, October.
    6. T. Gärtner & S. Kaniovski & Y. Kaniovski, 2021. "Numerical estimates of risk factors contingent on credit ratings," Computational Management Science, Springer, vol. 18(4), pages 563-589, October.
    7. David Conaly Martínez Vázquez & Christian Bucio Pacheco & Alejandra Cabello Rosales, 2021. "Proyección Markoviana para 2020 y 2021 de las Calificaciones Corporativas en México," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-21, Enero - M.
    8. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2017. "Numerical Modeling of Dependent Credit Rating Transitions with Asynchronously Moving Industries," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 499-516, March.
    9. Dmitri Boreiko & Serguei Kaniovski & Yuri Kaniovski & Georg Ch. Pflug, 2018. "Business Cycles and Conditional Credit-Rating Migration Matrices," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 1-19, December.

Articles

  1. Georg Pflug & David Wozabal, 2007. "Ambiguity in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 435-442.

    Cited by:

    1. Nilay Noyan & Gábor Rudolf, 2015. "Kusuoka representations of coherent risk measures in general probability spaces," Annals of Operations Research, Springer, vol. 229(1), pages 591-605, June.
    2. Dimitris Bertsimas & Shimrit Shtern & Bradley Sturt, 2023. "A Data-Driven Approach to Multistage Stochastic Linear Optimization," Management Science, INFORMS, vol. 69(1), pages 51-74, January.
    3. Zhi Chen & Melvyn Sim & Huan Xu, 2019. "Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets," Operations Research, INFORMS, vol. 67(5), pages 1328-1344, September.
    4. Francesca Maggioni & Matteo Cagnolari & Luca Bertazzi, 2019. "The value of the right distribution in stochastic programming with application to a Newsvendor problem," Computational Management Science, Springer, vol. 16(4), pages 739-758, October.
    5. Wang, Zhuolin & You, Keyou & Song, Shiji & Zhang, Yuli, 2020. "Wasserstein distributionally robust shortest path problem," European Journal of Operational Research, Elsevier, vol. 284(1), pages 31-43.
    6. Andrew L. Allan & Christa Cuchiero & Chong Liu & David J. Promel, 2021. "Model-free Portfolio Theory: A Rough Path Approach," Papers 2109.01843, arXiv.org, revised Oct 2022.
    7. Xin Hai & Gregoire Loeper & Kihun Nam, 2023. "Data-driven Multiperiod Robust Mean-Variance Optimization," Papers 2306.16681, arXiv.org, revised Jul 2023.
    8. Sophie N. Parragh & Fabien Tricoire & Walter J. Gutjahr, 2022. "A branch-and-Benders-cut algorithm for a bi-objective stochastic facility location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 419-459, June.
    9. Zhang, Xili & Zhang, Weiguo & Xiao, Weilin, 2013. "Multi-period portfolio optimization under possibility measures," Economic Modelling, Elsevier, vol. 35(C), pages 401-408.
    10. Max Nendel & Alessandro Sgarabottolo, 2022. "A parametric approach to the estimation of convex risk functionals based on Wasserstein distance," Papers 2210.14340, arXiv.org, revised Aug 2024.
    11. Martin Branda & Max Bucher & Michal Červinka & Alexandra Schwartz, 2018. "Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization," Computational Optimization and Applications, Springer, vol. 70(2), pages 503-530, June.
    12. Hu, Jian & Bansal, Manish & Mehrotra, Sanjay, 2018. "Robust decision making using a general utility set," European Journal of Operational Research, Elsevier, vol. 269(2), pages 699-714.
    13. Carole Bernard & Silvana M. Pesenti & Steven Vanduffel, 2024. "Robust distortion risk measures," Mathematical Finance, Wiley Blackwell, vol. 34(3), pages 774-818, July.
    14. Sebastian Jaimungal & Silvana Pesenti & Ye Sheng Wang & Hariom Tatsat, 2021. "Robust Risk-Aware Reinforcement Learning," Papers 2108.10403, arXiv.org, revised Dec 2021.
    15. Ran Ji & Miguel A. Lejeune, 2021. "Data-Driven Optimization of Reward-Risk Ratio Measures," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1120-1137, July.
    16. Daniel Bartl & Samuel Drapeau & Jan Obloj & Johannes Wiesel, 2020. "Sensitivity analysis of Wasserstein distributionally robust optimization problems," Papers 2006.12022, arXiv.org, revised Nov 2021.
    17. Black, Ben & Ainslie, Russell & Dokka, Trivikram & Kirkbride, Christopher, 2023. "Distributionally robust resource planning under binomial demand intakes," European Journal of Operational Research, Elsevier, vol. 306(1), pages 227-242.
    18. Stephan Eckstein & Michael Kupper & Mathias Pohl, 2018. "Robust risk aggregation with neural networks," Papers 1811.00304, arXiv.org, revised May 2020.
    19. Davide Lauria & Giorgio Consigli & Francesca Maggioni, 2022. "Optimal chance-constrained pension fund management through dynamic stochastic control," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 967-1007, September.
    20. Kellerer, Belinda, 2019. "Portfolio Optimization and Ambiguity Aversion," Junior Management Science (JUMS), Junior Management Science e. V., vol. 4(3), pages 305-338.
    21. Yannan Chen & Hailin Sun & Huifu Xu, 2021. "Decomposition and discrete approximation methods for solving two-stage distributionally robust optimization problems," Computational Optimization and Applications, Springer, vol. 78(1), pages 205-238, January.
    22. David Wozabal, 2012. "A framework for optimization under ambiguity," Annals of Operations Research, Springer, vol. 193(1), pages 21-47, March.
    23. Wolfram Wiesemann & Daniel Kuhn & Berç Rustem, 2012. "Multi-resource allocation in stochastic project scheduling," Annals of Operations Research, Springer, vol. 193(1), pages 193-220, March.
    24. Steffen Rebennack, 2022. "Data-driven stochastic optimization for distributional ambiguity with integrated confidence region," Journal of Global Optimization, Springer, vol. 84(2), pages 255-293, October.
    25. Xia Han & Ruodu Wang & Xun Yu Zhou, 2022. "Choquet regularization for reinforcement learning," Papers 2208.08497, arXiv.org.
    26. Jose Blanchet & Lin Chen & Xun Yu Zhou, 2022. "Distributionally Robust Mean-Variance Portfolio Selection with Wasserstein Distances," Management Science, INFORMS, vol. 68(9), pages 6382-6410, September.
    27. Bita Analui & Georg Pflug, 2014. "On distributionally robust multiperiod stochastic optimization," Computational Management Science, Springer, vol. 11(3), pages 197-220, July.
    28. Miguel A. Lejeune, 2012. "Game Theoretical Approach for Reliable Enhanced Indexation," Decision Analysis, INFORMS, vol. 9(2), pages 146-155, June.
    29. Jitka Dupačová & Miloš Kopa, 2012. "Robustness in stochastic programs with risk constraints," Annals of Operations Research, Springer, vol. 200(1), pages 55-74, November.
    30. Viet Anh Nguyen & Soroosh Shafiee & Damir Filipovi'c & Daniel Kuhn, 2021. "Mean-Covariance Robust Risk Measurement," Papers 2112.09959, arXiv.org, revised Nov 2023.
    31. Bart P. G. Van Parys & Peyman Mohajerin Esfahani & Daniel Kuhn, 2021. "From Data to Decisions: Distributionally Robust Optimization Is Optimal," Management Science, INFORMS, vol. 67(6), pages 3387-3402, June.
    32. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & Jose Blanchet & Erick Delage & Yinyu Ye, 2021. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Papers 2103.16451, arXiv.org, revised Apr 2024.
    33. Izhakian, Yehuda & Yermack, David, 2017. "Risk, ambiguity, and the exercise of employee stock options," Journal of Financial Economics, Elsevier, vol. 124(1), pages 65-85.
    34. Hakan Kaya, 2017. "Managing ambiguity in asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 18(3), pages 163-187, May.
    35. Chen, Qingxin & Ma, Shoufeng & Li, Hongming & Zhu, Ning & He, Qiao-Chu, 2024. "Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    36. Fuhrmann, Sven & Kupper, Michael & Nendel, Max, 2021. "Wasserstein Perturbations of Markovian Transition Semigroups," Center for Mathematical Economics Working Papers 649, Center for Mathematical Economics, Bielefeld University.
    37. Yehuda Izhakian & David Yermack & Jaime F. Zender, 2016. "Ambiguity and the Tradeoff Theory of Capital Structure," NBER Working Papers 22870, National Bureau of Economic Research, Inc.
    38. Petturiti, Davide & Vantaggi, Barbara, 2024. "The impact of ambiguity on dynamic portfolio selection in the epsilon-contaminated binomial market model," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1029-1039.
    39. Daniel Bartl & Johannes Wiesel, 2022. "Sensitivity of multiperiod optimization problems in adapted Wasserstein distance," Papers 2208.05656, arXiv.org, revised Jun 2023.
    40. Martin Glanzer & Georg Ch. Pflug & Alois Pichler, 2017. "Incorporating statistical model error into the calculation of acceptability prices of contingent claims," Papers 1703.05709, arXiv.org, revised Jan 2019.
    41. Bansal, Manish & Mehrotra, Sanjay, 2019. "On solving two-stage distributionally robust disjunctive programs with a general ambiguity set," European Journal of Operational Research, Elsevier, vol. 279(2), pages 296-307.
    42. Ch. Pflug, Georg & Timonina-Farkas, Anna & Hochrainer-Stigler, Stefan, 2017. "Incorporating model uncertainty into optimal insurance contract design," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 68-74.
    43. Thuener Silva & Davi Valladão & Tito Homem-de-Mello, 2021. "A data-driven approach for a class of stochastic dynamic optimization problems," Computational Optimization and Applications, Springer, vol. 80(3), pages 687-729, December.
    44. Luo, Fengqiao & Mehrotra, Sanjay, 2019. "Decomposition algorithm for distributionally robust optimization using Wasserstein metric with an application to a class of regression models," European Journal of Operational Research, Elsevier, vol. 278(1), pages 20-35.
    45. Manish Bansal & Yingqiu Zhang, 2021. "Scenario-based cuts for structured two-stage stochastic and distributionally robust p-order conic mixed integer programs," Journal of Global Optimization, Springer, vol. 81(2), pages 391-433, October.
    46. Andrew L. Allan & Christa Cuchiero & Chong Liu & David J. Prömel, 2023. "Model‐free portfolio theory: A rough path approach," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 709-765, July.
    47. Michael Kupper & Max Nendel & Alessandro Sgarabottolo, 2023. "Risk measures based on weak optimal transport," Papers 2312.05973, arXiv.org.
    48. Guanglin Xu & Samuel Burer, 2018. "A data-driven distributionally robust bound on the expected optimal value of uncertain mixed 0-1 linear programming," Computational Management Science, Springer, vol. 15(1), pages 111-134, January.
    49. David Wozabal, 2014. "Robustifying Convex Risk Measures for Linear Portfolios: A Nonparametric Approach," Operations Research, INFORMS, vol. 62(6), pages 1302-1315, December.
    50. Yehuda Izhakian & David Yermack, 2014. "Risk, Ambiguity, and the Exercise of Employee Stock Options," NBER Working Papers 19975, National Bureau of Economic Research, Inc.
    51. Gregory, Christine & Darby-Dowman, Ken & Mitra, Gautam, 2011. "Robust optimization and portfolio selection: The cost of robustness," European Journal of Operational Research, Elsevier, vol. 212(2), pages 417-428, July.
    52. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    53. Birghila, Corina & Pflug, Georg Ch., 2019. "Optimal XL-insurance under Wasserstein-type ambiguity," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 30-43.
    54. Hachmi Ben Ameur & Mouna Boujelbène & J. L. Prigent & Emna Triki, 2020. "Optimal Portfolio Positioning on Multiple Assets Under Ambiguity," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 21-57, June.
    55. Nilay Noyan & Gábor Rudolf & Miguel Lejeune, 2022. "Distributionally Robust Optimization Under a Decision-Dependent Ambiguity Set with Applications to Machine Scheduling and Humanitarian Logistics," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 729-751, March.
    56. Marlon Moresco & M'elina Mailhot & Silvana M. Pesenti, 2023. "Uncertainty Propagation and Dynamic Robust Risk Measures," Papers 2308.12856, arXiv.org, revised Feb 2024.
    57. Stephan Eckstein & Michael Kupper & Mathias Pohl, 2020. "Robust risk aggregation with neural networks," Mathematical Finance, Wiley Blackwell, vol. 30(4), pages 1229-1272, October.
    58. Len Patrick Dominic M. Garces & Yang Shen, 2024. "Robust optimal investment and consumption strategies with portfolio constraints and stochastic environment," Papers 2407.02831, arXiv.org.
    59. Lars Hellemo & Paul I. Barton & Asgeir Tomasgard, 2018. "Decision-dependent probabilities in stochastic programs with recourse," Computational Management Science, Springer, vol. 15(3), pages 369-395, October.
    60. Hsieh, Chung-Han, 2024. "On solving robust log-optimal portfolio: A supporting hyperplane approximation approach," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1129-1139.
    61. Ren, Ke & Bidkhori, Hoda, 2023. "A study of data-driven distributionally robust optimization with incomplete joint data under finite support," European Journal of Operational Research, Elsevier, vol. 305(2), pages 754-765.
    62. Pflug, Georg Ch. & Pichler, Alois & Wozabal, David, 2012. "The 1/N investment strategy is optimal under high model ambiguity," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 410-417.
    63. Bellini, Fabio & Klar, Bernhard & Müller, Alfred & Rosazza Gianin, Emanuela, 2014. "Generalized quantiles as risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 41-48.
    64. Arezoo Mohammadi & Mehrzad Minnoei & Zadollah Fathi & Mohamamd Ali Keramati & Hossein Baktiari, 2022. "Optimal allocation of bank resources and risk reduction through portfolio decentralization," International Journal of Economic Sciences, European Research Center, vol. 11(2), pages 92-143, November.
    65. Junichi Imai, 2022. "A Numerical Method for Hedging Bermudan Options under Model Uncertainty," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 893-916, June.
    66. Liu, Jia & Chen, Zhiping, 2018. "Time consistent multi-period robust risk measures and portfolio selection models with regime-switching," European Journal of Operational Research, Elsevier, vol. 268(1), pages 373-385.
    67. Kim, Jang Ho & Kim, Woo Chang & Fabozzi, Frank J., 2013. "Composition of robust equity portfolios," Finance Research Letters, Elsevier, vol. 10(2), pages 72-81.
    68. Silvana Pesenti & Sebastian Jaimungal, 2020. "Portfolio Optimisation within a Wasserstein Ball," Papers 2012.04500, arXiv.org, revised Jun 2022.
    69. Bingyan Han, 2022. "Distributionally robust risk evaluation with a causality constraint and structural information," Papers 2203.10571, arXiv.org, revised Aug 2024.
    70. Feng Liu & Zhi Chen & Shuming Wang, 2023. "Globalized Distributionally Robust Counterpart," INFORMS Journal on Computing, INFORMS, vol. 35(5), pages 1120-1142, September.
    71. Hosseini-Nodeh, Zohreh & Khanjani-Shiraz, Rashed & Pardalos, Panos M., 2023. "Portfolio optimization using robust mean absolute deviation model: Wasserstein metric approach," Finance Research Letters, Elsevier, vol. 54(C).
    72. Yang, Tingting & Huang, Xiaoxia, 2022. "Two new mean–variance enhanced index tracking models based on uncertainty theory," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    73. Sylvain Chassang, 2016. "Mostly Prior-Free Asset Allocation," Working Papers 077_2016, Princeton University, Department of Economics, Econometric Research Program..
    74. Yehuda Izhakian, 2012. "Capital Asset Pricing Under Ambiguity," Working Papers 12-02, New York University, Leonard N. Stern School of Business, Department of Economics.
    75. Wim Ackooij & Debora Daniela Escobar & Martin Glanzer & Georg Ch. Pflug, 2020. "Distributionally robust optimization with multiple time scales: valuation of a thermal power plant," Computational Management Science, Springer, vol. 17(3), pages 357-385, October.
    76. Ran Ji & Miguel A. Lejeune, 2021. "Data-driven distributionally robust chance-constrained optimization with Wasserstein metric," Journal of Global Optimization, Springer, vol. 79(4), pages 779-811, April.
    77. Ameur, H. Ben & Prigent, J.L., 2013. "Optimal portfolio positioning under ambiguity," Economic Modelling, Elsevier, vol. 34(C), pages 89-97.
    78. Ch. Pflug, Georg, 2023. "Multistage stochastic decision problems: Approximation by recursive structures and ambiguity modeling," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1027-1039.
    79. Daniel Bartl & Ariel Neufeld & Kyunghyun Park, 2023. "Sensitivity of robust optimization problems under drift and volatility uncertainty," Papers 2311.11248, arXiv.org.
    80. Zou, Zhenfeng & Wu, Qinyu & Xia, Zichao & Hu, Taizhong, 2023. "Adjusted Rényi entropic Value-at-Risk," European Journal of Operational Research, Elsevier, vol. 306(1), pages 255-268.
    81. Dupačová, Jitka & Kopa, Miloš, 2014. "Robustness of optimal portfolios under risk and stochastic dominance constraints," European Journal of Operational Research, Elsevier, vol. 234(2), pages 434-441.
    82. Takashi Hasuike & Hiroaki Ishii, 2009. "Probability maximization models for portfolio selection under ambiguity," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 17(2), pages 159-180, June.
    83. Jiang, Jie & Peng, Shen, 2024. "Mathematical programs with distributionally robust chance constraints: Statistical robustness, discretization and reformulation," European Journal of Operational Research, Elsevier, vol. 313(2), pages 616-627.
    84. Yongchao Liu & Alois Pichler & Huifu Xu, 2019. "Discrete Approximation and Quantification in Distributionally Robust Optimization," Mathematics of Operations Research, INFORMS, vol. 44(1), pages 19-37, February.
    85. Shuang Lin & Jie Zhang & Nan Shi, 2022. "An Alternating Iteration Algorithm for a Parameter-Dependent Distributionally Robust Optimization Model," Mathematics, MDPI, vol. 10(7), pages 1-12, April.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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-RMG: Risk Management (1) 2009-11-21

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