{"id":"W1487783860","doi":"","title":"Optimal Rationing in IPOs with Risk Averse Institutional Investors","year":2005,"lang":"en","type":"article","venue":"Rivista di Politica Economica","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Rationing; Initial public offering; Institutional investor; Information asymmetry; Credit rationing; Microeconomics; Mechanism (biology); Economics; Optimal allocation; Mechanism design; Business; Risk aversion (psychology); Monetary economics; Expected utility hypothesis; Financial economics; Finance; Mathematical optimization; Interest rate; Mathematics","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":[0.008122988,0.0008895505,0.001586154,0.001024679,0.0005359011,0.003674472,0.001472882,0.002199015,0.005048247],"category_scores_gemma":[0.02542509,0.0008299873,0.00129551,0.0008512848,0.002727965,0.004664843,0.001929026,0.001627334,0.0007095077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002008002,"about_ca_system_score_gemma":0.001599412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005258845,"about_ca_topic_score_gemma":0.0003367288,"domain_scores_codex":[0.9951384,0.003112933,0.0003100625,0.0005508357,0.0003707807,0.0005168779],"domain_scores_gemma":[0.9870868,0.00736376,0.003060743,0.001392392,0.0005572347,0.000539052],"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":[0.0009525476,0.0003128048,0.002943988,0.0004297971,0.0002022179,0.0004043327,0.0003711461,0.1415489,0.007015462,0.7951571,0.002236325,0.0484253],"study_design_scores_gemma":[0.0006391549,0.0004041076,0.001033874,0.00009426123,0.0001045757,0.0002999326,0.0001184883,0.3424842,0.003535424,0.6477079,0.003517725,0.00006031649],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2074736,0.001298754,0.7634316,0.001738944,0.0001536847,0.0005625764,0.0002048927,0.0002660547,0.02486996],"genre_scores_gemma":[0.9190822,0.0007738137,0.0736208,0.0001839915,0.0001029105,0.0002724088,0.00004933267,0.00004889086,0.00586553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008122988,"threshold_uncertainty_score":0.04295903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748288772474904,"score_gpt":0.3109915948348725,"score_spread":0.2735087071101234,"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."}}