{"id":"W2072733280","doi":"10.1515/jtse-2013-0013","title":"Constrained Hamiltonian Monte Carlo in BEKK GARCH with Targeting","year":2013,"lang":"en","type":"article","venue":"Journal of Time Series Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Covariance; Curse of dimensionality; Mathematics; Monte Carlo method; Applied mathematics; Econometrics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001225109,0.0002126362,0.0008078952,0.001571005,0.00009170637,0.0001657008,0.0003351966,0.0001340609,0.0008313428],"category_scores_gemma":[0.0006022585,0.0002133486,0.0001612284,0.001100926,0.0001106644,0.001365049,0.00005756303,0.0004297119,0.0002655949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002374955,"about_ca_system_score_gemma":0.00009884279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004833721,"about_ca_topic_score_gemma":0.00005560443,"domain_scores_codex":[0.9976373,0.00002127496,0.001554052,0.0002784199,0.00007227284,0.0004367084],"domain_scores_gemma":[0.9982428,0.0001332176,0.001035863,0.000216566,0.0002069155,0.0001646449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000301471,0.0003996416,0.9466217,0.0001500563,0.0002458887,0.00008772188,0.002627899,0.02589707,0.00009199386,0.009893218,0.002599749,0.01108363],"study_design_scores_gemma":[0.01042251,0.004957811,0.5980851,0.0004572745,0.00007419178,0.0004318657,0.003615655,0.2212083,0.000395658,0.05085374,0.1060665,0.003431406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861935,0.002930807,0.00163524,0.0007893975,0.0002540272,0.0002290181,0.00004498187,0.0000142072,0.007908865],"genre_scores_gemma":[0.9872152,0.0005078437,0.01097662,0.00008972475,0.0001514227,0.000007072669,0.000002595596,0.00003330081,0.001016266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3485366,"threshold_uncertainty_score":0.9102621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882511673433412,"score_gpt":0.1866570955358486,"score_spread":0.1678319788015145,"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."}}