{"id":"W3022616347","doi":"10.1108/jes-03-2020-0091","title":"Market frictions and the geographical location of global stock exchanges. Evidence from the S&P Global Index","year":2020,"lang":"en","type":"article","venue":"Journal of Economic Studies","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Portfolio; Economics; Endogeneity; Diversification (marketing strategy); Equity (law); Stock (firearms); Financial economics; Index (typography); Stock market index; Stock market; Econometrics; Empirical research; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009944097,0.0002491886,0.0004054796,0.00211584,0.0002912276,0.001402664,0.0004084337,0.0004127812,0.002875983],"category_scores_gemma":[0.009954735,0.0001524649,0.0004803668,0.003822546,0.0006334145,0.00155554,0.001014023,0.0003926948,0.0003421594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005221325,"about_ca_system_score_gemma":0.0004847407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0221197,"about_ca_topic_score_gemma":0.02686474,"domain_scores_codex":[0.9994761,0.0001203789,0.00006968529,0.0001121331,0.0001539963,0.00006778095],"domain_scores_gemma":[0.9748674,0.003644616,0.01898299,0.0009272209,0.0007551025,0.0008227015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001217603,0.00002025688,0.9890422,0.00008389281,0.0001935859,0.0002133596,0.0002470506,0.00118131,0.0001690178,0.0008285073,0.0005268669,0.007372236],"study_design_scores_gemma":[0.000005966985,0.00002716719,0.9975726,0.00002330435,0.00005676548,0.0000723304,0.0003342569,0.0008267079,0.00008089843,0.000305378,0.0006884796,0.000006196451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932095,0.001530975,0.000464295,0.0002930627,0.0000102752,0.00001237531,0.001210187,0.00001796652,0.003251236],"genre_scores_gemma":[0.9988869,0.000289348,0.0001037254,0.0000187555,0.00001260677,0.000002700587,0.0005365511,0.000003115809,0.0001463553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0221197,"threshold_uncertainty_score":0.04398191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09299413047847514,"score_gpt":0.2811801169617176,"score_spread":0.1881859864832424,"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."}}