{"id":"W2483372187","doi":"10.4018/978-1-59140-702-7.ch021","title":"Online Methods for Portfolio Selection","year":2006,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Portfolio; Selection (genetic algorithm); Portfolio optimization; Computer science; Econometrics; Investment strategy; Post-modern portfolio theory; Investment portfolio; Investment (military); Stock (firearms); Stock market; Economics; Financial economics; Replicating portfolio; Artificial intelligence; Finance; Engineering; Geography","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":[0.002928767,0.002012165,0.002027061,0.001986891,0.0005777951,0.002562091,0.001999347,0.0018437,0.01583436],"category_scores_gemma":[0.01197155,0.0007252123,0.001223197,0.002910048,0.001011742,0.002675317,0.002128176,0.002981005,0.008305038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009234674,"about_ca_system_score_gemma":0.001031126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001348244,"about_ca_topic_score_gemma":0.001088153,"domain_scores_codex":[0.9975794,0.0009151705,0.0001344973,0.0003480579,0.0009174237,0.0001054273],"domain_scores_gemma":[0.9959643,0.002915049,0.0001894779,0.0004674166,0.0003919139,0.000071765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008763446,0.0001603406,0.0006450241,0.0005490491,0.0002026134,0.00009281289,0.00005804992,0.1237117,0.001328654,0.1947392,0.02302683,0.6553981],"study_design_scores_gemma":[0.00005332653,0.0000515117,0.0002777925,0.0001117994,0.0000347574,0.0001612905,0.00001867579,0.6583681,0.000906929,0.3066855,0.03330155,0.00002870738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004707692,0.003314084,0.9914833,0.000229601,0.0001993863,0.00005350109,0.000103441,0.0004260878,0.003719748],"genre_scores_gemma":[0.08519894,0.01357385,0.8692203,0.0007519435,0.00194505,0.001192811,0.001453664,0.0006339002,0.02602967],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01583436,"threshold_uncertainty_score":0.05297124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1245174220392064,"score_gpt":0.4819105692302763,"score_spread":0.35739314719107,"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."}}