{"id":"W4405424795","doi":"10.2139/ssrn.5059380","title":"Bias Correcting Summary Statistics for Alphas","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Statistics; Summary statistics; Econometrics; 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":[0.06079298,0.001630707,0.003420536,0.007540955,0.001153276,0.004024372,0.003172469,0.004663038,0.02836312],"category_scores_gemma":[0.4461342,0.0009267984,0.003824253,0.009206626,0.002016544,0.003147104,0.001449529,0.003934534,0.007581287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009232418,"about_ca_system_score_gemma":0.00176267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134804,"about_ca_topic_score_gemma":0.001261684,"domain_scores_codex":[0.9164251,0.04774267,0.008470148,0.0162201,0.009388573,0.00175337],"domain_scores_gemma":[0.3546243,0.535771,0.02250172,0.07529937,0.01090803,0.0008955962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002342644,0.0004156052,0.08665248,0.005499898,0.01104458,0.001430922,0.001096002,0.0180817,0.004323979,0.09045577,0.1452799,0.6333765],"study_design_scores_gemma":[0.001304285,0.002310233,0.1593463,0.003074334,0.008449672,0.005525517,0.0009671134,0.1487219,0.01686883,0.4904106,0.1623505,0.0006707078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04319426,0.008403642,0.8934208,0.00204802,0.003427834,0.0008149017,0.03227932,0.008489988,0.007921268],"genre_scores_gemma":[0.5993008,0.002536244,0.345005,0.002400201,0.003833831,0.003608527,0.02700283,0.002537529,0.01377508],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06079298,"threshold_uncertainty_score":0.3215079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04718339979674671,"score_gpt":0.2576845574681075,"score_spread":0.2105011576713608,"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."}}