{"id":"W4414592730","doi":"10.48550/arxiv.2509.09865","title":"Linear fractional relative risk aversion","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Social Sciences and Humanities Research Council of Canada","keywords":"Monopolistic competition; Constant (computer programming); Risk aversion (psychology); Aggregate (composite); Isoelastic utility; Marginal utility; Competition (biology); Measure (data warehouse)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001799851,0.000804435,0.0006375393,0.0008327675,0.0004745034,0.002150687,0.0006797166,0.0008833829,0.002742534],"category_scores_gemma":[0.007734155,0.0002476946,0.0008407363,0.0007516254,0.001575262,0.001760477,0.0009100444,0.001226525,0.0005753713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007842652,"about_ca_system_score_gemma":0.0004835945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000879023,"about_ca_topic_score_gemma":0.000323616,"domain_scores_codex":[0.9986992,0.0006392758,0.00003900792,0.0002162939,0.0002273476,0.0001788001],"domain_scores_gemma":[0.997863,0.001069077,0.0004188366,0.0002654294,0.0002386987,0.0001449476],"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":[0.00007660204,0.00006048877,0.002092066,0.00006505261,0.000072205,0.0002076142,0.0002346668,0.09640907,0.003663481,0.8612321,0.001423887,0.0344628],"study_design_scores_gemma":[0.00001448929,0.0000798551,0.001069193,0.00003186033,0.00002324537,0.0002291655,0.0000718577,0.251209,0.001055988,0.7432448,0.00293598,0.000034614],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1295805,0.0008597187,0.8401435,0.001083251,0.00006299697,0.00004464317,0.0001471689,0.0002042786,0.02787402],"genre_scores_gemma":[0.9591303,0.0007016848,0.03410342,0.0001854159,0.0001027196,0.00007169331,0.00007191586,0.00003386345,0.00559915],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002742534,"threshold_uncertainty_score":0.009518623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1191778333748204,"score_gpt":0.3950923346295649,"score_spread":0.2759145012547445,"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."}}