{"id":"W3022616347","doi":"10.1108/jes-03-2020-0091","title":"Market frictions and the geographical location of global stock exchanges. Evidence from the S&amp;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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007031641,0.0001252192,0.0005058934,0.00002160274,0.0001528921,0.00005984052,0.0002708873,0.00005006071,0.0000724082],"category_scores_gemma":[0.0007726953,0.00008133467,0.0001350696,0.0001999335,0.0004535578,0.0002846615,0.0001200076,0.0001259926,0.00001042219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001212029,"about_ca_system_score_gemma":0.00006067934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006145173,"about_ca_topic_score_gemma":0.0004084003,"domain_scores_codex":[0.998842,0.00005022417,0.000770224,0.00016938,0.00003979012,0.0001283528],"domain_scores_gemma":[0.9983776,0.0004269052,0.0009052795,0.0001476037,0.00009294756,0.00004968741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004607435,0.00002592522,0.7944567,0.00003603144,0.0006915533,8.03536e-7,0.001180079,0.0002006363,5.261106e-7,0.167118,0.03509052,0.0007384941],"study_design_scores_gemma":[0.0009331945,0.0001275292,0.8888134,0.00008674803,0.00006002076,0.000006840495,0.001215619,0.0007588267,6.112422e-7,0.0998166,0.008070477,0.0001100743],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8066857,0.1461806,0.0008141259,0.04144767,0.0009400701,0.0002423384,0.0001797844,0.000007378494,0.003502243],"genre_scores_gemma":[0.9804465,0.01825604,0.0001402653,0.0007232669,0.0004077485,0.000007134551,4.163259e-7,0.000004133548,0.00001449334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1737608,"threshold_uncertainty_score":0.3316732,"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."}}