{"id":"W1944708231","doi":"10.1002/cpe.1784","title":"An efficient graphics processing unit‐based parallel algorithm for pricing multi‐asset American options","year":2011,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Graphics processing unit; Graphics; Complementarity (molecular biology); Parallel computing; Mathematical optimization; Linear complementarity problem; Valuation of options; Algorithm; Mathematics; Computer graphics (images)","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":[0.0002173343,0.0001201295,0.0001782524,0.0001072983,0.0004526152,0.00009753012,0.00009817215,0.00003937347,0.000002874654],"category_scores_gemma":[0.0001313414,0.0001355705,0.00002388572,0.0003387472,0.0002119197,0.0004413592,0.00001900579,0.00008787206,0.000003152276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009609733,"about_ca_system_score_gemma":0.00004062758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001756655,"about_ca_topic_score_gemma":0.000004109888,"domain_scores_codex":[0.9990638,0.000008530968,0.0003245907,0.0003901327,0.00003376712,0.0001791903],"domain_scores_gemma":[0.9991479,0.0001227947,0.0003813056,0.000102784,0.0001476902,0.00009751155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004722527,0.0007003323,0.001677934,0.00006971384,0.00001528545,0.000001529253,0.02063337,0.0006228148,0.00001584851,0.6498613,0.000006513479,0.3263482],"study_design_scores_gemma":[0.0005550489,0.0002399836,0.00763139,0.00001945543,0.00001607517,0.000007949911,0.00372654,0.9736021,0.00001411766,0.0124904,0.001435923,0.0002609853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02106705,0.001459488,0.9767628,0.0001263763,0.00007943209,0.0002817305,0.00004713209,0.00004010963,0.0001358337],"genre_scores_gemma":[0.7727019,0.00009826785,0.2266558,0.0002778177,0.0000236118,0.0002102509,0.00002194133,0.000008255606,0.000002189455],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9729793,"threshold_uncertainty_score":0.5528406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08426280087602969,"score_gpt":0.3369720426031249,"score_spread":0.2527092417270952,"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."}}