{"id":"W3043439704","doi":"10.1111/jfir.12221","title":"PREDICTING SYSTEMATIC RISK WITH MACROECONOMIC AND FINANCIAL VARIABLES","year":2020,"lang":"en","type":"article","venue":"The Journal of Financial Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Predictive power; Benchmark (surveying); Autoregressive model; Econometrics; Economics; Bond; Order (exchange); Financial market; Sample (material); 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":[0.0091106,0.0001210182,0.0005510978,0.0001541356,0.0003531905,0.0001009922,0.0004151531,0.00008226691,0.00007436334],"category_scores_gemma":[0.005113516,0.00008556663,0.00007039755,0.0003502113,0.0001773876,0.0001877583,0.0001345196,0.0008595767,0.00001700908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007992125,"about_ca_system_score_gemma":0.0001965246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002089979,"about_ca_topic_score_gemma":0.00007938046,"domain_scores_codex":[0.9982316,0.0002444181,0.0008602844,0.0001849044,0.0001362103,0.0003425516],"domain_scores_gemma":[0.9979388,0.0007912269,0.0007295195,0.0001881241,0.0001854063,0.000166893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002202251,0.0001323133,0.9277098,0.004959773,0.0001567796,0.00005328687,0.006039503,0.0001599515,0.00006061771,0.05435652,0.001730853,0.002438346],"study_design_scores_gemma":[0.005867621,0.005313108,0.5607097,0.0031066,0.000210664,0.0003355662,0.001178651,0.2473125,0.0001003509,0.1617904,0.01300375,0.001071086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900175,0.002684419,0.003356913,0.001089397,0.0001136718,0.0003669094,0.00007115888,0.000006203662,0.002293855],"genre_scores_gemma":[0.9981862,0.0009488107,0.0003372235,0.00009577311,0.0003262308,0.000005390361,4.24796e-7,0.00001565299,0.00008428208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670001,"threshold_uncertainty_score":0.6121726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04761123628057603,"score_gpt":0.2660869641656746,"score_spread":0.2184757278850985,"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."}}