{"id":"W4394828443","doi":"10.2139/ssrn.4773791","title":"Multivariate Affine GARCH in portfolio optimization","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Download; Computer science; Portfolio; Affine transformation; Autoregressive conditional heteroskedasticity; Multivariate statistics; Econometrics; World Wide Web; Financial economics; Economics; Mathematics; Machine learning","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":[0.002726079,0.000854097,0.001777946,0.001033336,0.0003394267,0.001950211,0.0009203763,0.001880988,0.002404751],"category_scores_gemma":[0.01011418,0.0008708071,0.0008277095,0.002227509,0.001064563,0.002657395,0.001135733,0.002214784,0.0004285184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009321669,"about_ca_system_score_gemma":0.0006605198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003230566,"about_ca_topic_score_gemma":0.001935863,"domain_scores_codex":[0.9990749,0.000561871,0.00004307076,0.00009952006,0.0001733618,0.00004707271],"domain_scores_gemma":[0.9957153,0.003415733,0.0003827614,0.00016711,0.0001959639,0.0001231006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007168379,0.00004987745,0.001673777,0.0001433399,0.0001871792,0.0001285502,0.00006447097,0.5049188,0.0006566877,0.4529875,0.003252794,0.03586534],"study_design_scores_gemma":[0.00001030433,0.00001481887,0.0004624338,0.00001065998,0.00001857922,0.0000173296,0.000006168486,0.8060957,0.00008118168,0.1924059,0.0008641939,0.00001279346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06085982,0.01314573,0.9108016,0.004199982,0.0008614787,0.00002332264,0.0002412913,0.0003983027,0.009468412],"genre_scores_gemma":[0.9017395,0.01056114,0.06083662,0.0004121063,0.002370619,0.00006799964,0.0002708966,0.000261472,0.0234795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003230566,"threshold_uncertainty_score":0.01441705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957727055438191,"score_gpt":0.2440554477387267,"score_spread":0.2244781771843448,"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."}}