{"id":"W2117479135","doi":"10.1017/s0022109009990196","title":"Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks","year":2009,"lang":"en","type":"article","venue":"Journal of Financial and Quantitative Analysis","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Stock (firearms); Portfolio; Financial economics; Algorithmic trading; Business; Empirical evidence; Trading strategy; Volume (thermodynamics); Economics; Econometrics; Monetary economics","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":[0.0006157917,0.0001403543,0.0005137127,0.0005441532,0.0001573095,0.0002975481,0.0001653984,0.00007382542,0.0001525926],"category_scores_gemma":[0.0006950321,0.0001340382,0.000172528,0.0004632851,0.0001009215,0.002447255,0.00002516219,0.0001683715,0.000005270915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005502394,"about_ca_system_score_gemma":0.00003494978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002664691,"about_ca_topic_score_gemma":0.00004238,"domain_scores_codex":[0.9986313,0.00002352818,0.0009681422,0.0001449022,0.00008856998,0.0001435502],"domain_scores_gemma":[0.9984246,0.00008929193,0.001077902,0.00009017165,0.0002393391,0.00007868711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003994032,0.0001083684,0.8632594,0.00001736503,0.0007158978,0.00000936455,0.003964405,0.0001080356,0.0001002759,0.1191753,0.002587344,0.009554829],"study_design_scores_gemma":[0.0004875831,0.0004040514,0.9512802,0.00005944734,0.0001066034,0.000002097076,0.0001785001,0.007278723,0.00001188341,0.03551969,0.004509694,0.000161514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766461,0.003818862,0.01656285,0.001190241,0.0002326966,0.00006974102,0.000150698,0.000005421192,0.001323383],"genre_scores_gemma":[0.995346,0.001518611,0.002174576,0.0006938465,0.00009297168,0.000001428962,0.00001581332,0.000003307334,0.000153491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08802081,"threshold_uncertainty_score":0.5465919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05169116429688406,"score_gpt":0.2923734434599863,"score_spread":0.2406822791631022,"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."}}