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Learning from ambiguous urns

Citations

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Cited by:

  1. Li, Wenhui & Wilde, Christian, 2020. "Belief formation and belief updating under ambiguity: Evidence from experiments," SAFE Working Paper Series 251, Leibniz Institute for Financial Research SAFE, revised 2020.
  2. Amarante, Massimiliano, 2009. "Foundations of neo-Bayesian statistics," Journal of Economic Theory, Elsevier, vol. 144(5), pages 2146-2173, September.
  3. Massimiliano AMARANTE, 2014. "What is Ambiguity?," Cahiers de recherche 04-2014, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  4. Farzad Pourbabaee, 2022. "Robust experimentation in the continuous time bandit problem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(1), pages 151-181, February.
  5. Lennart Struth & Max Thon, 2022. "Discrimination, Quotas, and Stereotypes," ECONtribute Discussion Papers Series 188, University of Bonn and University of Cologne, Germany.
  6. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
  7. Kellerer, Belinda, 2019. "Portfolio Optimization and Ambiguity Aversion," Junior Management Science (JUMS), Junior Management Science e. V., vol. 4(3), pages 305-338.
  8. Larry G. Epstein & Martin Schneider, 2007. "Learning Under Ambiguity," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1275-1303.
  9. Knispel, Thomas & Laeven, Roger J.A. & Svindland, Gregor, 2016. "Robust optimal risk sharing and risk premia in expanding pools," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 182-195.
  10. Epstein, Larry G. & Seo, Kyoungwon, 2015. "Exchangeable capacities, parameters and incomplete theories," Journal of Economic Theory, Elsevier, vol. 157(C), pages 879-917.
  11. Gemayel, Roland & Preda, Alex, 2021. "Performance and learning in an ambiguous environment: A study of cryptocurrency traders," International Review of Financial Analysis, Elsevier, vol. 77(C).
  12. Cecchi, Francesco & Lensink, Robert & Slingerland, Edwin, 2024. "Ambiguity attitudes and demand for weather index insurance with and without a credit bundle: experimental evidence from Kenya," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
  13. Enrica Carbone & Konstantinos Georgalos & Gerardo Infante, 2019. "Individual vs. group decision-making: an experiment on dynamic choice under risk and ambiguity," Theory and Decision, Springer, vol. 87(1), pages 87-122, July.
  14. Alexander Zimper & Alexander Ludwig, 2009. "On attitude polarization under Bayesian learning with non-additive beliefs," Journal of Risk and Uncertainty, Springer, vol. 39(2), pages 181-212, October.
  15. Ludwig, Alexander & Zimper, Alexander, 2014. "Biased Bayesian learning with an application to the risk-free rate puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 79-97.
  16. Chen, Jaden Yang, 2022. "Biased learning under ambiguous information," Journal of Economic Theory, Elsevier, vol. 203(C).
  17. Paul Viefers, 2012. "Should I Stay or Should I Go?: A Laboratory Analysis of Investment Opportunities under Ambiguity," Discussion Papers of DIW Berlin 1228, DIW Berlin, German Institute for Economic Research.
  18. Kellner, Christian, 2015. "Tournaments as a response to ambiguity aversion in incentive contracts," Journal of Economic Theory, Elsevier, vol. 159(PA), pages 627-655.
  19. Zimper, Alexander, 2009. "Half empty, half full and why we can agree to disagree forever," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 283-299, August.
  20. Werner, Jan, 2022. "Speculative trade under ambiguity," Journal of Economic Theory, Elsevier, vol. 199(C).
  21. Larry G. Epstein & Shaolin Ji, 2022. "Optimal Learning Under Robustness and Time-Consistency," Operations Research, INFORMS, vol. 70(3), pages 1317-1329, May.
  22. Marinacci, Massimo & Massari, Filippo, 2019. "Learning from ambiguous and misspecified models," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 144-149.
  23. Konstantinos Georgalos, 2019. "An experimental test of the predictive power of dynamic ambiguity models," Journal of Risk and Uncertainty, Springer, vol. 59(1), pages 51-83, August.
  24. Cinfrignini, Andrea & Petturiti, Davide & Vantaggi, Barbara, 2023. "Dynamic bid–ask pricing under Dempster-Shafer uncertainty," Journal of Mathematical Economics, Elsevier, vol. 107(C).
  25. Xiaoyu Cheng, 2022. "Robust Data-Driven Decisions Under Model Uncertainty," Papers 2205.04573, arXiv.org.
  26. Nicky Nicholls & Aylit Romm & Alexander Zimper, 2015. "The impact of statistical learning on violations of the sure-thing principle," Journal of Risk and Uncertainty, Springer, vol. 50(2), pages 97-115, April.
  27. Li, Jian, 2019. "The K-armed bandit problem with multiple priors," Journal of Mathematical Economics, Elsevier, vol. 80(C), pages 22-38.
  28. Roxane Bricet, 2018. "Preferences for information precision under ambiguity," THEMA Working Papers 2018-09, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  29. Ronald Klingebiel & Feibai Zhu, 2023. "Ambiguity aversion and the degree of ambiguity," Journal of Risk and Uncertainty, Springer, vol. 67(3), pages 299-324, December.
  30. Alexander Zimper, 2011. "Do Bayesians Learn Their Way Out of Ambiguity?," Decision Analysis, INFORMS, vol. 8(4), pages 269-285, December.
  31. Massari, Filippo & Newton, Jonathan, 2020. "When does ambiguity fade away?," Economics Letters, Elsevier, vol. 194(C).
  32. Massimo Marinacci, 2015. "Model Uncertainty," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1022-1100, December.
  33. Cerreia-Vioglio, Simone & Maccheroni, Fabio & Marinacci, Massimo & Montrucchio, Luigi, 2013. "Ambiguity and robust statistics," Journal of Economic Theory, Elsevier, vol. 148(3), pages 974-1049.
    • Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Luigi Montrucchio, 2011. "Ambiguity and Robust Statistics," Working Papers 382, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  34. Chambers, Robert G. & Melkonyan, Tigran, 2009. "Smoothing preference kinks with information," Mathematical Social Sciences, Elsevier, vol. 58(2), pages 173-189, September.
  35. Alexander Zimper & Wei Ma, 2017. "Bayesian learning with multiple priors and nonvanishing ambiguity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 64(3), pages 409-447, October.
  36. Battigalli, P. & Francetich, A. & Lanzani, G. & Marinacci, M., 2019. "Learning and self-confirming long-run biases," Journal of Economic Theory, Elsevier, vol. 183(C), pages 740-785.
  37. Qiu, Jianying & Weitzel, Utz, 2013. "Experimental Evidence on Valuation and Learning with Multiple Priors," MPRA Paper 43974, University Library of Munich, Germany.
  38. Simon Grant & Idione Meneghel & Rabee Tourky, 2022. "Learning under unawareness," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(2), pages 447-475, September.
  39. Larry G. Epstein & Shaolin Ji, 2017. "Optimal Learning and Ellsberg’s Urns," Boston University - Department of Economics - Working Papers Series WP2017-010, Boston University - Department of Economics.
  40. Massimiliano Amarante, 2017. "Information and Ambiguity: Toward a Foundation of Nonexpected Utility," Mathematics of Operations Research, INFORMS, vol. 42(4), pages 1254-1279, November.
  41. Lahno, Amrei M., 2014. "Social anchor effects in decision-making under ambiguity," Discussion Papers in Economics 20960, University of Munich, Department of Economics.
  42. Farzad Pourbabaee, 2021. "Robust Experimentation in the Continuous Time Bandit Problem," Papers 2104.00102, arXiv.org.
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