{"id":"W3134090484","doi":"10.3390/jrfm14030112","title":"Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spillover effect; Stock (firearms); Economics; Vector autoregression; Econometrics; Volatility (finance); Synchronicity; Stock market; Stock market index; Variance decomposition of forecast errors; Emerging markets; Financial economics; Frequency domain; Financial market; Geography; Macroeconomics; Mathematics; Finance","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":[0.0005834739,0.0001727882,0.0002343337,0.001180743,0.0002749174,0.0006386489,0.0001981912,0.0003186833,0.002025672],"category_scores_gemma":[0.002568585,0.000132668,0.0002553877,0.000989964,0.0003238407,0.0006464688,0.0007823264,0.0005387779,0.0001810241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002690807,"about_ca_system_score_gemma":0.0003204064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071261,"about_ca_topic_score_gemma":0.01280409,"domain_scores_codex":[0.9997868,0.00003981001,0.00001939961,0.00005901172,0.00004543642,0.00004957929],"domain_scores_gemma":[0.9986477,0.0002818931,0.0005715878,0.0001346244,0.0002459656,0.0001182355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003041094,0.0000977645,0.9578147,0.0001063551,0.0001687221,0.0008101114,0.001853478,0.0008141967,0.003039071,0.001538078,0.0009532876,0.03250024],"study_design_scores_gemma":[0.000002517078,0.00004442221,0.9972453,0.000034135,0.00003178311,0.00009990385,0.0007913555,0.000575377,0.0001738628,0.0001977033,0.0007960325,0.000007634452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969742,0.0006546093,0.0004328073,0.0001533111,0.0000133015,0.000007151393,0.0003103106,0.000005492835,0.001448711],"genre_scores_gemma":[0.9988759,0.0003223562,0.0001657981,0.00003537037,0.00002696506,0.000004381302,0.0003712312,0.000001728096,0.0001962482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01071261,"threshold_uncertainty_score":0.02130055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0214038374020267,"score_gpt":0.2351615108880039,"score_spread":0.2137576734859772,"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."}}