{"id":"W3163327181","doi":"10.1108/joic-01-2021-0001","title":"Contagion of COVID-19 pandemic between oil and financial assets: the evidence of multivariate Markov switching GARCH models","year":2021,"lang":"en","type":"article","venue":"Journal of Investment Compliance","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Economics; Volatility (finance); Stock market index; Econometrics; Spillover effect; Financial economics; Stock (firearms); Cryptocurrency; Financial asset; Index (typography); Stock market; Finance; Geography; Macroeconomics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002591985,0.0004841946,0.0006898278,0.001050055,0.0004916872,0.001388788,0.000700982,0.0008729484,0.003696339],"category_scores_gemma":[0.009905796,0.0003439701,0.001216124,0.0007732474,0.0008043024,0.001307377,0.0007531992,0.001306086,0.0002756329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005420431,"about_ca_system_score_gemma":0.0006323532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01201493,"about_ca_topic_score_gemma":0.006924134,"domain_scores_codex":[0.9990269,0.0002854669,0.00006056156,0.0002833467,0.0001726193,0.0001710716],"domain_scores_gemma":[0.9913669,0.00453001,0.002840769,0.0005575127,0.0004130705,0.0002916841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004840342,0.0003082415,0.6664031,0.0002695357,0.001521107,0.002724776,0.001285153,0.1726099,0.004403361,0.09154817,0.006086393,0.05235637],"study_design_scores_gemma":[0.00006269076,0.0002260015,0.1397168,0.00007746291,0.0003963195,0.0005083367,0.0005408517,0.8183143,0.001303435,0.03635648,0.002400131,0.00009722764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606499,0.001199841,0.03100754,0.001688521,0.00009227084,0.00004347929,0.0004575368,0.0002171191,0.004643791],"genre_scores_gemma":[0.9980222,0.0002880067,0.0007928887,0.00004544234,0.00004759823,0.000009116201,0.0001296844,0.000008772887,0.0006563462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01201493,"threshold_uncertainty_score":0.02388996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1886986023403748,"score_gpt":0.3320764504966225,"score_spread":0.1433778481562478,"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."}}