{"id":"W2209948770","doi":"10.1016/j.jedc.2015.10.001","title":"Estimation of correlations in portfolio credit risk models based on noisy security prices","year":2015,"lang":"en","type":"article","venue":"Journal of Economic Dynamics and Control","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal; Université du Québec à Montréal","funders":"","keywords":"Econometrics; Estimator; Economics; Credit risk; Portfolio; Bond; Credit default swap; Equity (law); Correlation; Estimation; Credit derivative; Financial economics; Actuarial science; Statistics; Mathematics; 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":[0.000920585,0.0001072867,0.0004662777,0.0004442113,0.00003979191,0.00003608384,0.0001126448,0.00009544246,0.00001562668],"category_scores_gemma":[0.0001590511,0.0001174324,0.0001142895,0.00008896334,0.00004590046,0.0003635177,0.00001111426,0.0001864272,0.000006335973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002444481,"about_ca_system_score_gemma":0.0001254909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002667625,"about_ca_topic_score_gemma":0.0002108692,"domain_scores_codex":[0.9986706,0.0000151296,0.001004654,0.0001419945,0.00003977267,0.000127832],"domain_scores_gemma":[0.9981593,0.0001341605,0.001402655,0.00014218,0.00005848879,0.0001031896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001029797,0.00008602008,0.09218848,0.000004739297,0.00002143868,0.000001549829,0.0001480784,0.7323594,1.433002e-7,0.1724679,0.00009793065,0.002521352],"study_design_scores_gemma":[0.001858574,0.000166629,0.056846,0.0000172516,0.00001616046,0.000003314144,0.0000490046,0.8114808,4.516941e-7,0.1293135,0.0001614298,0.00008693616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8363017,0.0005240379,0.157326,0.0003147875,0.0005692681,0.0001493471,0.0003951885,0.000004041847,0.004415577],"genre_scores_gemma":[0.9990507,0.0001612093,0.000572165,0.0000169157,0.0001431492,0.000003819289,0.0000108666,0.0000104265,0.0000307655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1627489,"threshold_uncertainty_score":0.4788755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406171320515669,"score_gpt":0.2167948781190093,"score_spread":0.2027331649138526,"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."}}