{"id":"W4281681547","doi":"10.1108/jrf-03-2021-0037","title":"The cross-section of expected stock returns and components of idiosyncratic volatility","year":2022,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Stock (firearms); Economics; Econometrics; Portfolio; Volatility (finance); Financial economics; Predictability; Systematic risk; Modern portfolio theory; Covariance; Capital asset pricing model; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001883828,0.00008531237,0.000319058,0.00006558512,0.000407167,0.00002161394,0.0002968678,0.00002774598,0.00003207596],"category_scores_gemma":[0.0002617773,0.00005943445,0.0000900465,0.0002103319,0.0002327243,0.0001674988,0.00008210858,0.000301328,4.68044e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004601775,"about_ca_system_score_gemma":0.00002705517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000270778,"about_ca_topic_score_gemma":0.00002389397,"domain_scores_codex":[0.9987407,0.0001149243,0.0008456092,0.00008864498,0.00008695343,0.0001231597],"domain_scores_gemma":[0.997373,0.0002614394,0.002041478,0.0002286636,0.00007882716,0.0000165746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001359966,0.0002625641,0.9383224,0.00007438321,0.0001433723,0.000002530938,0.004799962,0.001710406,0.0007705148,0.04921855,0.001566139,0.001769173],"study_design_scores_gemma":[0.0004491243,0.0003599918,0.9625713,0.00001686221,0.00001234399,0.00001492203,0.0002925143,0.001594456,0.0001392384,0.03132249,0.003159977,0.00006676225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904725,0.008096823,0.000152654,0.0001233148,0.0004987908,0.0001096301,0.0000961566,0.000002337495,0.0004478069],"genre_scores_gemma":[0.9962573,0.003491085,0.00008163095,0.00001302254,0.00004791611,0.000003010746,8.060733e-7,0.000006906873,0.00009829105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02424887,"threshold_uncertainty_score":0.3131641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672392019308921,"score_gpt":0.2283950702890412,"score_spread":0.201671150095952,"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."}}