{"id":"W2098921899","doi":"10.1016/j.mulfin.2014.06.008","title":"Dependence patterns across Gulf Arab stock markets: A copula approach","year":2014,"lang":"en","type":"article","venue":"Journal of Multinational Financial Management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Copula (linguistics); Tail dependence; Economics; Econometrics; Equity (law); Stock (firearms); Bivariate analysis; Volatility (finance); Financial economics; Geography; Statistics; Multivariate statistics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002931186,0.0001788472,0.0004097243,0.0002180459,0.000159652,0.00009633508,0.0004668663,0.00009152813,0.0001606133],"category_scores_gemma":[0.0004353586,0.0001908517,0.0002185243,0.0001915568,0.00003822182,0.0002868224,0.0001624554,0.0002575575,0.00002154232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001873529,"about_ca_system_score_gemma":0.00001797403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003071547,"about_ca_topic_score_gemma":0.00001758719,"domain_scores_codex":[0.9980496,0.00004970206,0.001068154,0.0003117178,0.0002112334,0.0003096394],"domain_scores_gemma":[0.9984057,0.00009451675,0.0009862081,0.0002465319,0.0001693012,0.00009773137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003009778,0.0009028818,0.6006342,0.000331835,0.0001423535,0.00002843942,0.000350002,0.0008603968,0.000003045185,0.3211891,0.001960669,0.07329614],"study_design_scores_gemma":[0.001297523,0.00007549601,0.8345047,0.00004455172,0.000009712488,0.00001403256,0.00004133886,0.09586886,0.00000155615,0.0241438,0.04377289,0.0002254937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4495351,0.0001778869,0.527757,0.0003911441,0.0008216547,0.0003007646,0.0001515539,0.00001283189,0.02085204],"genre_scores_gemma":[0.9869557,0.00009063665,0.01133602,0.0002491279,0.0002781272,0.00001586502,0.00001552501,0.00001667796,0.001042306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5374206,"threshold_uncertainty_score":0.7782707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967672097988194,"score_gpt":0.2438933883995385,"score_spread":0.2242166674196566,"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."}}