{"id":"W2913070268","doi":"10.3390/economies7010007","title":"Market Efficiency and News Dynamics: Evidence from International Equity Markets","year":2019,"lang":"en","type":"article","venue":"Economies","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Drexel University","keywords":"Economics; Equity (law); Volatility (finance); Stock market; Financial economics; Econometrics; Stock (firearms); Null hypothesis; Conditional variance; Market efficiency; Efficient-market hypothesis; Autoregressive conditional heteroskedasticity; Monetary economics; Geography; Political science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008642498,0.0001776158,0.0003790082,0.0001360591,0.00006548206,0.0002278119,0.0004163325,0.0001023865,0.01134352],"category_scores_gemma":[0.0002390509,0.0002114432,0.00009381265,0.00006071354,0.00007334627,0.0005608332,0.0004157106,0.0001413952,0.0004261289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000233479,"about_ca_system_score_gemma":0.0000210301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008680907,"about_ca_topic_score_gemma":0.0005636935,"domain_scores_codex":[0.9984882,0.00002277778,0.0005657892,0.0006319445,0.00003324975,0.0002579646],"domain_scores_gemma":[0.9988083,0.0003357322,0.0002960297,0.0004490694,0.00002214402,0.00008877963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006987518,0.00002924116,0.9838135,0.00002200182,0.00004875735,9.019417e-7,0.0001064061,0.00001179977,0.000002206535,0.0103334,0.001417136,0.00414478],"study_design_scores_gemma":[0.0003083851,0.00002229894,0.46494,0.00002754053,0.000002961146,0.000001251951,0.00006314978,0.4942931,0.000001614617,0.02686943,0.01324022,0.0002300466],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7698123,0.0009577598,0.0008729356,0.001096128,0.001161505,0.000181061,0.0003997312,0.00002905913,0.2254896],"genre_scores_gemma":[0.9905545,0.0008017795,0.0006326367,0.0001951122,0.0001065919,0.00001242143,0.00003215072,0.00001716326,0.007647678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5188735,"threshold_uncertainty_score":0.9895602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380518103902852,"score_gpt":0.2425365736525338,"score_spread":0.2187313926135052,"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."}}