{"id":"W4232609382","doi":"10.55365/1923.x2021.19.34","title":"Asset allocation by Unsupervised Learning","year":2021,"lang":"en","type":"article","venue":"Review of Economics and Finance","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Portfolio; Asset allocation; Modern portfolio theory; Computer science; Black–Litterman model; Replicating portfolio; Portfolio optimization; Post-modern portfolio theory; Asset (computer security); Capital asset pricing model; Unsupervised learning; Actuarial science; Artificial intelligence; Economics; Econometrics; Financial economics; Business; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003213977,0.00006817072,0.0003467828,0.00002486083,0.00004831818,0.00003750843,0.0001660287,0.0000301215,0.00008531685],"category_scores_gemma":[0.004278786,0.00006071332,0.00006609564,0.0001964035,0.00003343417,0.0001041425,0.00007437643,0.00006864984,0.00001403338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001146979,"about_ca_system_score_gemma":0.00006484995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003395509,"about_ca_topic_score_gemma":0.000002610748,"domain_scores_codex":[0.9988552,0.0001876184,0.0005188643,0.0002798794,0.00006983285,0.00008855364],"domain_scores_gemma":[0.9984593,0.0007611638,0.0003209654,0.0002799296,0.0001571884,0.00002141171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002493377,0.00001196259,0.00140327,0.0002223969,0.000005498435,5.187799e-7,0.00002174276,0.00007701676,0.00008514489,0.00735115,0.005238978,0.9855798],"study_design_scores_gemma":[0.0001243014,0.00002551263,0.003935174,0.0008363356,0.000008422813,0.00001094263,0.00001833602,0.0082311,0.0005276637,0.006668521,0.9795026,0.0001110642],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.5363386,0.4410086,0.00458878,0.003079888,0.0003117603,0.000233586,0.00003111962,0.00001045396,0.01439718],"genre_scores_gemma":[0.07804172,0.8980646,0.02074282,0.0007544475,0.00003117169,0.00001086793,0.00001598658,0.00001065141,0.002327794],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9854687,"threshold_uncertainty_score":0.5122415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08311525017615526,"score_gpt":0.3647671301548081,"score_spread":0.2816518799786528,"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."}}