{"id":"W1967959634","doi":"10.1080/00036846.2014.1002885","title":"Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy","year":2015,"lang":"en","type":"article","venue":"Applied Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Economics; Heteroscedasticity; Volatility (finance); Proxy (statistics); Econometrics; Stock (firearms); Financial economics; Autoregressive model; Stock market; Autoregressive conditional heteroskedasticity; Emerging markets; Macroeconomics","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":[0.001663665,0.0001756353,0.0003535963,0.001348862,0.0002578001,0.00152004,0.0003838253,0.0003326934,0.0009806541],"category_scores_gemma":[0.009890762,0.0001510923,0.0002943324,0.001764555,0.0006182068,0.001658038,0.0007743945,0.0008831772,0.0001668154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001923826,"about_ca_system_score_gemma":0.0002107146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004230495,"about_ca_topic_score_gemma":0.005271416,"domain_scores_codex":[0.9996601,0.0001022829,0.00005390159,0.0000667969,0.0000846665,0.00003228978],"domain_scores_gemma":[0.983007,0.01137787,0.003300067,0.0007751468,0.001159264,0.0003806293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002653278,0.0001517715,0.9675289,0.00008296446,0.0002518192,0.0008093173,0.001061992,0.001830507,0.001538921,0.004138174,0.0002574428,0.02208292],"study_design_scores_gemma":[0.00001544693,0.0001204376,0.9880794,0.00003457612,0.0001337129,0.0002890898,0.001162633,0.005875474,0.0007559176,0.002222677,0.00129105,0.00001956431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971769,0.0005564469,0.0008250342,0.0001516771,0.000006811717,0.000002882247,0.00008290437,0.000002436125,0.001194867],"genre_scores_gemma":[0.9984474,0.0008695756,0.0002730359,0.00002581843,0.00002863542,0.000001541467,0.0002151237,0.000002070737,0.0001369351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004230495,"threshold_uncertainty_score":0.00879842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1894520810670558,"score_gpt":0.2789954605292309,"score_spread":0.08954337946217511,"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."}}