{"id":"W2059476787","doi":"10.1111/1540-6261.00521","title":"Asset Pricing with Conditioning Information: A New Test","year":2003,"lang":"en","type":"article","venue":"The Journal of Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Capital asset pricing model; Stochastic discount factor; Econometrics; Nonparametric statistics; Economics; Sharpe ratio; Test (biology); Risk premium; Factor analysis; Asset (computer security); Financial economics; Computer science","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":[0.01835288,0.001084391,0.002264009,0.003412239,0.0007073032,0.002858195,0.003255332,0.003212219,0.01305681],"category_scores_gemma":[0.1773112,0.0004382354,0.001369622,0.002594727,0.003658516,0.007635967,0.003218466,0.004052375,0.0008662166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009234907,"about_ca_system_score_gemma":0.001911411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001114529,"about_ca_topic_score_gemma":0.0004534253,"domain_scores_codex":[0.9839011,0.008240361,0.000774166,0.002519768,0.003870409,0.0006941747],"domain_scores_gemma":[0.7396368,0.2337988,0.007921171,0.01215536,0.004058293,0.002429639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002094012,0.001516756,0.1649161,0.0004609801,0.002336971,0.001199468,0.0005838009,0.1032953,0.003966463,0.4228008,0.01149454,0.2853348],"study_design_scores_gemma":[0.0005353497,0.001131424,0.02379978,0.0001104717,0.0002717483,0.0008192487,0.0001769245,0.7553037,0.002328171,0.2106171,0.004732857,0.0001732172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2716517,0.0006420188,0.7037889,0.002673654,0.0005096377,0.0002771151,0.001919042,0.001126451,0.01741139],"genre_scores_gemma":[0.9379788,0.0002318705,0.05649193,0.0006939937,0.0007025728,0.0002588124,0.001660827,0.0001328304,0.001848471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01835288,"threshold_uncertainty_score":0.0970605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01751677946498289,"score_gpt":0.1936451599088187,"score_spread":0.1761283804438358,"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."}}