{"id":"W2996984992","doi":"10.2139/ssrn.3508860","title":"Portfolio Optimization under Correlation Constraint","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Constraint (computer-aided design); Correlation; Portfolio optimization; Portfolio; Computer science; Econometrics; Mathematical optimization; Mathematics; Economics; Financial economics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005216207,0.0001613036,0.000238145,0.0004146742,0.0002086316,0.0002942012,0.0004157954,0.0001358209,0.001678851],"category_scores_gemma":[0.0003076378,0.0001251382,0.0001505173,0.0007497827,0.00005060005,0.0007810306,0.00003486265,0.0009900396,0.0008026018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000453837,"about_ca_system_score_gemma":0.001890572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001659824,"about_ca_topic_score_gemma":0.00004118378,"domain_scores_codex":[0.996345,0.0001900812,0.0007484899,0.0003332504,0.001111267,0.001271924],"domain_scores_gemma":[0.998309,0.0002003764,0.0005887768,0.0003362314,0.0004532424,0.0001124048],"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":[0.0000330682,0.0000263757,0.0160249,2.45452e-7,0.00003054558,0.000001143373,0.00005905376,0.7897944,0.00002119162,0.1670833,0.0004407449,0.02648499],"study_design_scores_gemma":[0.001387948,0.0003557711,0.00401056,0.00001344648,0.00004055386,0.0009722777,0.00464335,0.3297453,0.0000256609,0.6525115,0.005914206,0.0003795011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07990876,0.0005022657,0.8958556,0.000663363,0.000993799,0.0002128028,0.000001946928,0.00004031134,0.02182117],"genre_scores_gemma":[0.9803402,0.003379683,0.001447648,0.0001938868,0.0001847022,0.000001882307,0.00001633264,0.00002083895,0.01441482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9004315,"threshold_uncertainty_score":0.9999754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0213773400565773,"score_gpt":0.3057633723025269,"score_spread":0.2843860322459496,"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."}}