{"id":"W2944433903","doi":"10.1111/mafi.12384","title":"Noncausal affine processes with applications to derivative pricing","year":2023,"lang":"en","type":"article","venue":"Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Affine transformation; Term (time); Derivative (finance); Computer science; Valuation of options; Mathematical economics; Affine term structure model; Econometrics; Applied mathematics; Mathematics; Economics; Pure mathematics; Financial economics; Yield curve; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001424832,0.0006818761,0.0005942553,0.0008342385,0.0004046817,0.001435268,0.0005909289,0.001045811,0.003634061],"category_scores_gemma":[0.005438961,0.0003754674,0.000897681,0.0009727228,0.001780613,0.001860577,0.0009985346,0.001839728,0.0002040122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057674,"about_ca_system_score_gemma":0.0007112469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002919629,"about_ca_topic_score_gemma":0.001676368,"domain_scores_codex":[0.9994784,0.0002035725,0.00003143732,0.00006878176,0.0001734852,0.00004429738],"domain_scores_gemma":[0.9974865,0.001577697,0.0003865513,0.0001649965,0.0002462808,0.0001380231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006998933,0.00001905543,0.0002627884,0.00001981622,0.000009603044,0.000123189,0.00006641189,0.06109322,0.0005304959,0.9335634,0.0003282756,0.003976672],"study_design_scores_gemma":[0.000007248124,0.00001529682,0.000165795,0.000006961412,0.000005980572,0.00005137448,0.00001765156,0.4032345,0.000173989,0.5948949,0.001415296,0.00001081132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05296993,0.001797399,0.9334674,0.001420084,0.0001976776,0.00002131641,0.00009133701,0.0001018969,0.009932876],"genre_scores_gemma":[0.9351258,0.001776635,0.05255042,0.0001442014,0.0004935162,0.00004619853,0.00006357244,0.00005008824,0.009749546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003634061,"threshold_uncertainty_score":0.01215714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03561337852069545,"score_gpt":0.2560671552338029,"score_spread":0.2204537767131074,"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."}}