IDEAS home Printed from https://ideas.repec.org/r/bla/jrinsu/v84y2017i3p923-959.html

Value-at-Risk Bounds With Variance Constraints

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Lauzier, Jean-Gabriel & Lin, Liyuan & Wang, Ruodu, 2023. "Pairwise counter-monotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 279-287.
  2. Wiesel Johannes & Zhang Erica, 2023. "An optimal transport-based characterization of convex order," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-15, January.
  3. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
  4. Lux, Thibaut & Papapantoleon, Antonis, 2019. "Model-free bounds on Value-at-Risk using extreme value information and statistical distances," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 73-83.
  5. Alfred Müller & Marco Scarsini & Ilia Tsetlin & Robert L. Winkler, 2025. "Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty," Operations Research, INFORMS, vol. 73(2), pages 879-893, March.
  6. Carole Bernard & Ludger Rüschendorf & Steven Vanduffel & Ruodu Wang, 2017. "Risk bounds for factor models," Finance and Stochastics, Springer, vol. 21(3), pages 631-659, July.
  7. Carole Bernard & Oleg Bondarenko & Steven Vanduffel, 2021. "A model-free approach to multivariate option pricing," Review of Derivatives Research, Springer, vol. 24(2), pages 135-155, July.
  8. Cornilly, Dries & Vanduffel, Steven, 2019. "Equivalent distortion risk measures on moment spaces," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 187-192.
  9. Corrado De Vecchi & Max Nendel & Jan Streicher, 2024. "Upper Comonotonicity and Risk Aggregation under Dependence Uncertainty," Papers 2406.19242, arXiv.org.
  10. Tuitman, Jan & Vanduffel, Steven & Yao, Jing, 2020. "Correlation matrices with average constraints," Statistics & Probability Letters, Elsevier, vol. 165(C).
  11. Rüschendorf L., 2018. "Risk bounds with additional information on functionals of the risk vector," Dependence Modeling, De Gruyter, vol. 6(1), pages 102-113, June.
  12. Yuyu Chen & Peng Liu & Yang Liu & Ruodu Wang, 2022. "Ordering and inequalities for mixtures on risk aggregation," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 421-451, January.
  13. Chen, Yuyu & Lin, Liyuan & Wang, Ruodu, 2022. "Risk aggregation under dependence uncertainty and an order constraint," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 169-187.
  14. Yuyu Chen & Liyuan Lin & Ruodu Wang, 2021. "Risk Aggregation under Dependence Uncertainty and an Order Constraint," Papers 2104.07718, arXiv.org, revised Oct 2021.
  15. Carole Bernard & Oleg Bondarenko & Steven Vanduffel, 2018. "Rearrangement algorithm and maximum entropy," Annals of Operations Research, Springer, vol. 261(1), pages 107-134, February.
  16. Jonathan Ansari & Eva Lutkebohmert, 2024. "Robust Bernoulli Mixture Models for Credit Portfolio Risk," Papers 2411.11522, arXiv.org, revised Dec 2025.
  17. Yuyu Chen & Peng Liu & Yang Liu & Ruodu Wang, 2020. "Ordering and Inequalities for Mixtures on Risk Aggregation," Papers 2007.12338, arXiv.org, revised Jun 2021.
  18. De Vecchi, Corrado & Scherer, Matthias, 2025. "Pricing insurance contracts with an existing portfolio as background risk," Insurance: Mathematics and Economics, Elsevier, vol. 122(C), pages 180-193.
  19. Valeria Bignozzi & Corrado De Vecchi, 2025. "Risk bounds under right-tail uncertainty," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 48(2), pages 2025-2059, December.
  20. Stephan Eckstein & Michael Kupper & Mathias Pohl, 2018. "Robust risk aggregation with neural networks," Papers 1811.00304, arXiv.org, revised May 2020.
  21. Roberto Fontana & Elisa Luciano & Patrizia Semeraro, 2021. "Model risk in credit risk," Mathematical Finance, Wiley Blackwell, vol. 31(1), pages 176-202, January.
  22. Rüschendorf, L., 2019. "Analysis of risk bounds in partially specified additive factor models," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 115-121.
  23. Giovanni Puccetti & Pietro Rigo & Bin Wang & Ruodu Wang, 2019. "Centers of probability measures without the mean," Journal of Theoretical Probability, Springer, vol. 32(3), pages 1482-1501, September.
  24. De Vecchi, Corrado & Nendel, Max & Streicher, Jan, 2025. "Upper Comonotonicity and Risk Aggregation under Dependence Uncertainty," Center for Mathematical Economics Working Papers 739, Center for Mathematical Economics, Bielefeld University.
  25. Hanbali, Hamza & Dhaene, Jan & Linders, Daniël, 2022. "Dependence bounds for the difference of stop-loss payoffs on the difference of two random variables," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 22-37.
  26. Zhiping Chen & Wentao Ma & Bingbing Ji, 2025. "Data-driven approximation of distributionally robust chance constraints using Bayesian credible intervals," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 47(3), pages 969-1009, September.
  27. Bernard, Carole & Kazzi, Rodrigue & Vanduffel, Steven, 2020. "Range Value-at-Risk bounds for unimodal distributions under partial information," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 9-24.
  28. Carole Bernard & Jinghui Chen & Ludger Rüschendorf & Steven Vanduffel, 2026. "Improved block rearrangement algorithm," Annals of Operations Research, Springer, vol. 357(1), pages 605-632, February.
  29. Rüschendorf Ludger, 2025. "Generalized Hoeffding-Fréchet functionals and mass transportation," Dependence Modeling, De Gruyter, vol. 13(1), pages 1-15.
  30. Fangda Liu & Ruodu Wang, 2021. "A Theory for Measures of Tail Risk," Mathematics of Operations Research, INFORMS, vol. 46(3), pages 1109-1128, August.
  31. Jinghui Chen & Edward Furman & Stephano Ricci & Judeto Shanthirajah, 2025. "Mean-tail Gini framework for optimal portfolio selection," Papers 2509.17225, arXiv.org.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.