{"id":"W4413758615","doi":"10.1080/1540496x.2025.2544650","title":"Tail Risk Spillovers in Stock Markets Between G7 and BRICS: New Evidence from CAViaR and TVP-VAR Connectedness Approach","year":2025,"lang":"en","type":"article","venue":"Emerging Markets Finance and Trade","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education Key Projects of Philosophy and Social Sciences Research; National Natural Science Foundation of China","keywords":"Social connectedness; Stock (firearms); Spillover effect; Economics; Monetary economics; Vector autoregression; Econometrics; Financial economics; Macroeconomics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001221412,0.0003334772,0.0007290979,0.000286882,0.0002010478,0.0001392052,0.0002169692,0.0002116452,0.00005255506],"category_scores_gemma":[0.0004123678,0.0003942402,0.00006057027,0.0004737507,0.0001480869,0.0004251923,0.000173047,0.0004228753,0.000001437625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007339953,"about_ca_system_score_gemma":0.00005083411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003332328,"about_ca_topic_score_gemma":0.0001819595,"domain_scores_codex":[0.9976571,0.00009787465,0.0007089873,0.001025924,0.00006508509,0.000444997],"domain_scores_gemma":[0.998566,0.0005754094,0.0003136756,0.0004095457,0.00001321962,0.0001220995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001153144,0.00003707033,0.964169,0.0001279896,0.00006435053,0.000005488371,0.0004409634,0.000004806873,0.000002224725,0.001800729,0.0008875186,0.03234453],"study_design_scores_gemma":[0.001110192,0.00002488731,0.9287093,0.0002273887,0.00003182758,0.000001692408,0.00007269435,0.04422057,0.000003453522,0.013264,0.01195128,0.0003826756],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729263,0.01775286,0.002768995,0.001068649,0.0001918418,0.0003769929,0.0002604298,0.00003197243,0.004621981],"genre_scores_gemma":[0.9825616,0.01499019,0.001532018,0.00012827,0.00006629403,0.00001924748,0.00002352528,0.00002355327,0.0006552845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04421576,"threshold_uncertainty_score":0.9998509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02185392729819076,"score_gpt":0.2304950009717261,"score_spread":0.2086410736735354,"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."}}