{"id":"W4214903477","doi":"10.3390/jrfm15030116","title":"A Study of the Machine Learning Approach and the MGARCH-BEKK Model in Volatility Transmission","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cryptocurrency; Volatility (finance); Diversification (marketing strategy); Economics; Portfolio; Spillover effect; Econometrics; Financial economics; Stock market; Monetary economics; Business; Computer science; Microeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002936667,0.000681015,0.001175471,0.001001663,0.0006357951,0.001582454,0.001197324,0.001803929,0.002166668],"category_scores_gemma":[0.01292714,0.0004362254,0.0009790536,0.001014029,0.001618297,0.003549115,0.001075105,0.002145819,0.0002429763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059988,"about_ca_system_score_gemma":0.000826395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004778464,"about_ca_topic_score_gemma":0.001923331,"domain_scores_codex":[0.9992028,0.0004340144,0.00003249924,0.0001303919,0.0001167122,0.00008357397],"domain_scores_gemma":[0.9936206,0.005090673,0.0006933493,0.000227041,0.0002312697,0.0001370324],"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":[0.00006460877,0.00006479851,0.007901739,0.0001032671,0.0002047475,0.000370066,0.0002288746,0.6540436,0.0007552378,0.3201125,0.0009554428,0.01519509],"study_design_scores_gemma":[0.00001118888,0.0000295514,0.00122935,0.00001457928,0.00001683035,0.00006032178,0.00002752737,0.9190855,0.00009872107,0.0790774,0.0003316588,0.00001729409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4814343,0.005326326,0.4850543,0.006884332,0.0002541381,0.00005305684,0.0002046713,0.0001894133,0.02059953],"genre_scores_gemma":[0.9859113,0.001053969,0.009851701,0.0001764306,0.0001451343,0.00002376354,0.00005499565,0.00001775486,0.002765023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004778464,"threshold_uncertainty_score":0.01553071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01473765257235253,"score_gpt":0.1994536345017099,"score_spread":0.1847159819293573,"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."}}