{"id":"W2086041263","doi":"10.3905/jod.2005.580517","title":"Life after VaR","year":2005,"lang":"en","type":"article","venue":"The Journal of Derivatives","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Value at risk; Tail risk; Extreme value theory; Quantile; Econometrics; Expected shortfall; Economics; Time horizon; Measure (data warehouse); Coherent risk measure; Horizon; Vector autoregression; Cutoff; Actuarial science; Mathematics; Computer science; Statistics; Risk management; 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":[0.002302511,0.00006353903,0.000150315,0.0001308856,0.00007638695,0.00007601461,0.0004632363,0.00002425347,0.0006378103],"category_scores_gemma":[0.002326131,0.00002904738,0.00007550507,0.0003439216,0.00008311625,0.000548584,0.00003875333,0.0001183654,0.0001244423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009276931,"about_ca_system_score_gemma":0.00008395661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.751664e-7,"about_ca_topic_score_gemma":0.000001918979,"domain_scores_codex":[0.9983608,0.0002575421,0.0005395467,0.00005507883,0.0006888061,0.0000982215],"domain_scores_gemma":[0.9981919,0.000665125,0.0005069325,0.0001933385,0.0003365977,0.0001060874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002138188,0.0004295929,0.1001265,0.000003213046,0.0003048541,0.00003798182,0.06989183,0.09946349,0.00371459,0.003065713,0.2799678,0.4408562],"study_design_scores_gemma":[0.00109081,0.000392163,0.360403,0.00004084739,0.00007489755,0.0002255842,0.005561458,0.004168868,0.006483966,0.02934161,0.5919268,0.0002900872],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358918,0.00142585,0.04526863,0.01297425,0.0002145764,0.00004893951,0.000001351236,0.000005255869,0.004169368],"genre_scores_gemma":[0.9928861,0.0007013255,0.00399476,0.00113429,0.0003932666,3.944808e-7,6.275808e-8,0.000004650972,0.0008851334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4405662,"threshold_uncertainty_score":0.6983575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05866248080212996,"score_gpt":0.3579669452314382,"score_spread":0.2993044644293082,"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."}}