{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005803321,0.0009872768,0.002120454,0.0009601603,0.0004616582,0.002158737,0.001424797,0.001727447,0.001075734],"category_scores_gemma":[0.03625341,0.001909536,0.001052437,0.001012655,0.001417343,0.003115956,0.001393167,0.00224602,0.0001471357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037645,"about_ca_system_score_gemma":0.001429816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008134213,"about_ca_topic_score_gemma":0.006113108,"domain_scores_codex":[0.9987065,0.0007344062,0.00007267274,0.0002415437,0.0001349629,0.0001099344],"domain_scores_gemma":[0.9662879,0.02861844,0.002993557,0.0009095705,0.0006869099,0.000503597],"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":[0.000091918,0.00004237963,0.004978541,0.00001967551,0.00009906153,0.0000765397,0.0000398201,0.9796798,0.000230457,0.01139784,0.0002194628,0.003124622],"study_design_scores_gemma":[0.00000693012,0.000005432105,0.0003286175,0.000002621334,0.000005474867,0.000004576665,0.000002187902,0.997136,0.00004174892,0.002448901,0.00001314576,0.000004373661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6419542,0.0005344115,0.3550446,0.0008020784,0.0000568621,0.00004210688,0.0002051852,0.0002272153,0.001133282],"genre_scores_gemma":[0.9895458,0.0002424305,0.009270393,0.00003997214,0.00005101892,0.00002783382,0.0001648418,0.00002765657,0.0006301706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008134213,"threshold_uncertainty_score":0.03069127,"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."}}