{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001597741,0.0003433807,0.0004219327,0.002002222,0.0003339569,0.001577174,0.0003714626,0.0005788429,0.002026068],"category_scores_gemma":[0.01014009,0.0002678702,0.0004407068,0.002557289,0.0005266282,0.001198255,0.0009412805,0.0005023159,0.0003418406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295559,"about_ca_system_score_gemma":0.0001632843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00747269,"about_ca_topic_score_gemma":0.006704102,"domain_scores_codex":[0.9994892,0.0001564571,0.00006666801,0.00009295779,0.0001395464,0.00005511791],"domain_scores_gemma":[0.9833681,0.007033017,0.007019822,0.0009218675,0.0008627434,0.0007944778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001654524,0.0001352007,0.9928432,0.00001580158,0.0002475449,0.0001363222,0.0002293302,0.0009937285,0.0004293069,0.000262695,0.0001523345,0.00438908],"study_design_scores_gemma":[0.00001619758,0.0001081055,0.9946647,0.00001107638,0.0001102591,0.0001069072,0.0002765643,0.003547117,0.0003746286,0.0005014772,0.0002678305,0.00001523451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991148,0.0001943584,0.0001066114,0.00006185283,0.00000237231,0.000001850412,0.0001404807,0.000003010908,0.0003745971],"genre_scores_gemma":[0.9993508,0.0001392748,0.00006736308,0.00001433837,0.00001324838,0.000001555254,0.0003133232,0.000001407265,0.00009859047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00747269,"threshold_uncertainty_score":0.01485842,"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."}}