{"id":"W3093001417","doi":"10.1007/s00780-023-00497-y","title":"Optimal insurance under maxmin expected utility","year":2023,"lang":"en","type":"article","venue":"Finance and Stochastics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Indemnity; Expected utility hypothesis; Ambiguity; Mathematical economics; Unobservable; Mathematical finance; Ex-ante; Actuarial science; Prior probability; Knightian uncertainty; Econometrics; Ambiguity aversion; Economics; Mathematics; Computer science; Bayesian probability; Financial economics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003720632,0.001226186,0.002413697,0.001014284,0.0005225763,0.002936232,0.00126585,0.002106758,0.003061454],"category_scores_gemma":[0.01262494,0.0008220753,0.0008356539,0.0007741444,0.001610648,0.003367683,0.001760446,0.001829282,0.000305869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002949774,"about_ca_system_score_gemma":0.001982694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00148562,"about_ca_topic_score_gemma":0.0006491616,"domain_scores_codex":[0.9985966,0.000731235,0.00005984723,0.0001876451,0.0002080424,0.0002165972],"domain_scores_gemma":[0.9962113,0.002838732,0.0002793133,0.0001978363,0.0002290638,0.0002437376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003598126,0.0001239689,0.001147945,0.0002757224,0.000125806,0.0001379602,0.0001526885,0.1746061,0.001507911,0.7929221,0.004093371,0.02454661],"study_design_scores_gemma":[0.00004543231,0.00008376978,0.0005479741,0.00006444517,0.00003070781,0.00009658233,0.00003274365,0.4074994,0.0006428579,0.5897023,0.001236074,0.00001762999],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2192731,0.005134047,0.7288342,0.008125333,0.0003364035,0.0001176653,0.0008069951,0.0006076929,0.03676448],"genre_scores_gemma":[0.9645157,0.001298767,0.02520819,0.0003297152,0.0002841966,0.00009678879,0.0001615762,0.0001318489,0.007973171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003720632,"threshold_uncertainty_score":0.02140224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09140263138684938,"score_gpt":0.3585068105406871,"score_spread":0.2671041791538377,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}