{"id":"W2115914057","doi":"10.1002/fut.20190","title":"Jumping hedges: An examination of movements in copper spot and futures markets","year":2005,"lang":"en","type":"article","venue":"Journal of Futures Markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Wilfrid Laurier University","funders":"","keywords":"Futures contract; Jump; Volatility (finance); Economics; Spot contract; Autoregressive model; Bivariate analysis; Econometrics; Cash; Autoregressive conditional heteroskedasticity; Sample (material); Financial economics; Cash flow; Mathematics; Statistics; Finance","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":[0.003261577,0.0001720518,0.0005094613,0.0005348325,0.00006817488,0.00005430455,0.0002362395,0.0001410559,0.0003137449],"category_scores_gemma":[0.0002309447,0.0001736762,0.0001098566,0.0001816189,0.00004762872,0.0005726405,0.00005674643,0.0002669896,0.000001223485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001211559,"about_ca_system_score_gemma":0.0000241898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002425043,"about_ca_topic_score_gemma":0.0001355769,"domain_scores_codex":[0.9981534,0.0001118236,0.001148326,0.000244077,0.0001126125,0.0002297155],"domain_scores_gemma":[0.9984671,0.000113177,0.0009815267,0.0002236672,0.00009666172,0.0001178056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008884547,0.0007085603,0.8257974,0.0002576298,0.0001596104,0.00002343131,0.00254778,0.00007662216,0.0003230324,0.002712125,0.001557342,0.164948],"study_design_scores_gemma":[0.001080117,0.0001020875,0.9779377,0.00007371652,0.000005607271,0.00001580189,0.0003472351,0.01315025,0.00004679382,0.001940568,0.005134381,0.0001657649],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861841,0.002579251,0.000120707,0.000258456,0.0004223033,0.0001295581,0.00003372417,0.000004304999,0.01026761],"genre_scores_gemma":[0.9969552,0.001182623,0.001089798,0.0001616378,0.0003466084,0.000001995332,0.000004730593,0.00001738821,0.0002400501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1647823,"threshold_uncertainty_score":0.7082309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01656497474840852,"score_gpt":0.2363930900006145,"score_spread":0.219828115252206,"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."}}