{"id":"W2612233487","doi":"","title":"Credit Migration and Derivatives Pricing Using Copulas","year":2005,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Copula (linguistics); Credit risk; Univariate; Credit derivative; Econometrics; Portfolio; Markov chain; Credit spread (options); Actuarial science; Economics; Multivariate statistics; Financial economics; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001400882,0.0001036443,0.0001882108,0.000152394,0.0003074852,0.00006675725,0.00005912426,0.0001032159,0.00004694723],"category_scores_gemma":[0.00010122,0.0001238882,0.00004646974,0.0001645973,0.0001135519,0.0002842079,0.00001737001,0.0001112794,0.0000260259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244861,"about_ca_system_score_gemma":0.00001090675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00039427,"about_ca_topic_score_gemma":0.0001948509,"domain_scores_codex":[0.9992715,0.000007388643,0.0003004585,0.0002272894,0.00002685521,0.0001665538],"domain_scores_gemma":[0.99961,0.00003691747,0.0001589127,0.0001210849,0.0000203298,0.0000527303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001115481,0.00004004134,0.3671006,0.0000137797,0.00002293503,0.000002013511,0.004439229,0.0006063607,0.0004099648,0.6142213,0.0004920157,0.01264059],"study_design_scores_gemma":[0.0005495608,0.0000437063,0.7600388,0.00001744204,0.00001202293,0.00001500262,0.0002448184,0.03501417,0.0003628768,0.0299397,0.173378,0.0003839288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497315,0.001413009,0.0459778,0.0009321126,0.0001886274,0.0001008301,0.00002662422,0.00003393282,0.001595581],"genre_scores_gemma":[0.981464,0.0002794944,0.01724693,0.00006091942,0.0005796906,0.000005558052,0.0000136482,0.00001508793,0.0003346299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5842816,"threshold_uncertainty_score":0.5052015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357263630233594,"score_gpt":0.2172848257134393,"score_spread":0.1937121894111033,"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."}}