{"id":"W4400238468","doi":"10.1080/14697688.2024.2358954","title":"Weight bound constraints in mean-variance models: a robust control theory foundation via machine learning","year":2024,"lang":"en","type":"article","venue":"Quantitative Finance","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Foundation (evidence); Variance (accounting); Econometrics; Robust control; Control (management); Economics; Mathematical economics; Mathematics; Computer science; Artificial intelligence; Mathematical optimization; Engineering; Control system; Political 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":[0.007490617,0.001946996,0.002017876,0.001799291,0.0006969044,0.003332593,0.002997444,0.002848709,0.002745582],"category_scores_gemma":[0.02942573,0.0008547621,0.002092951,0.002209678,0.003984953,0.004704041,0.004096831,0.004282121,0.000448775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002342817,"about_ca_system_score_gemma":0.001428112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942207,"about_ca_topic_score_gemma":0.001580135,"domain_scores_codex":[0.9954386,0.002478722,0.0001697942,0.0006514864,0.0009936207,0.0002678362],"domain_scores_gemma":[0.9876921,0.008809904,0.00166998,0.001012252,0.0006185933,0.0001971867],"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":[0.00001780344,0.00002478982,0.0002742605,0.00007636867,0.00006197063,0.00005305868,0.00007376198,0.3077973,0.0003630903,0.6750023,0.0009962685,0.0152591],"study_design_scores_gemma":[0.00000766414,0.00001723539,0.0001023391,0.00002343758,0.00001081882,0.00001369311,0.000008525678,0.595301,0.000213421,0.403277,0.001006216,0.00001855754],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00256308,0.0005813967,0.9942094,0.0006058998,0.00003705019,0.00001292695,0.00003299925,0.000051942,0.001905381],"genre_scores_gemma":[0.6587164,0.00459494,0.325493,0.0009541407,0.000847582,0.0006128997,0.0002826994,0.0002980678,0.00820028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007490617,"threshold_uncertainty_score":0.03961468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1038937411042086,"score_gpt":0.365634405823522,"score_spread":0.2617406647193133,"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."}}