{"id":"W3197096319","doi":"10.1002/cjs.11658","title":"Direct local linear estimation for Sharpe ratio function","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; China Postdoctoral Science Foundation; Natural Science Foundation of Shanghai; National Science Foundation","keywords":"Sharpe ratio; Estimator; Heteroscedasticity; Nonparametric statistics; Econometrics; Monte Carlo method; Mathematics; Statistics; Nonparametric regression; Function (biology); Economics; Finance; Portfolio","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004089242,0.001000218,0.0010798,0.00145856,0.0004411816,0.001153562,0.001521455,0.001153736,0.005831111],"category_scores_gemma":[0.02227927,0.0004545557,0.001243303,0.00131299,0.001111066,0.002283755,0.00154299,0.002137993,0.002237555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007431821,"about_ca_system_score_gemma":0.0009700171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002834357,"about_ca_topic_score_gemma":0.002949289,"domain_scores_codex":[0.9978248,0.001164124,0.00006369667,0.00042371,0.0004078747,0.0001158431],"domain_scores_gemma":[0.9910083,0.006607065,0.0006724943,0.0006829868,0.0009364057,0.00009283028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002107948,0.0001936496,0.009450829,0.0009545245,0.0002640674,0.0004367535,0.0004210219,0.4030248,0.01893597,0.1676285,0.006852194,0.391627],"study_design_scores_gemma":[0.00002531646,0.00008542425,0.001683159,0.00004330903,0.0000480731,0.0002047707,0.00004761027,0.9601633,0.004828982,0.02989983,0.002926722,0.00004340682],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003797261,0.0003143867,0.9945211,0.00007649875,0.00001541928,0.00002682902,0.00004726,0.0002989132,0.0009022159],"genre_scores_gemma":[0.381258,0.001523253,0.6062819,0.0004065734,0.0002560648,0.0005592346,0.0005255166,0.0004806145,0.008708891],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005831111,"threshold_uncertainty_score":0.02162623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04181004814151597,"score_gpt":0.2255382015520228,"score_spread":0.1837281534105068,"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."}}