{"id":"W2025586852","doi":"10.1007/s11227-013-0893-z","title":"Normalized particle swarm optimization for complex chooser option pricing on graphics processing unit","year":2013,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Computer science; Valuation of options; Particle swarm optimization; Exotic option; Mathematical optimization; Black–Scholes model; Binomial options pricing model; Profit (economics); Finance; Algorithm; Economics; Microeconomics; Volatility (finance); Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007319363,0.0000951306,0.0002193474,0.00009863642,0.0003632382,0.00008751988,0.000218726,0.00004267645,0.0000239568],"category_scores_gemma":[0.0001371822,0.00007755565,0.0000732578,0.0003151335,0.00003642639,0.000309251,0.00002666324,0.0001437483,0.00002011549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003509206,"about_ca_system_score_gemma":0.00002043982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006332896,"about_ca_topic_score_gemma":0.000001220761,"domain_scores_codex":[0.999003,0.000007621247,0.0006364274,0.0001029185,0.00005082892,0.0001992096],"domain_scores_gemma":[0.9989735,0.0001457652,0.0004892888,0.0001081162,0.0002341316,0.00004919717],"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":[0.0001233717,0.0003149506,0.003324959,0.000159204,0.00007482902,5.284924e-7,0.003896552,0.4522343,0.001349714,0.5122352,0.0002137861,0.02607263],"study_design_scores_gemma":[0.0007274981,0.0001436856,0.009392613,0.00006928899,0.00001882335,0.00001649654,0.0003425669,0.9393218,0.0002046457,0.04919223,0.0004315275,0.0001388787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2827179,0.0002431738,0.7157826,0.0008287561,0.0000671374,0.0002124209,0.000003379582,0.00001129593,0.0001332829],"genre_scores_gemma":[0.97179,0.00003517813,0.02754391,0.0003579878,0.0002329557,0.00001083733,0.000003828812,0.00001683325,0.000008465073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6890721,"threshold_uncertainty_score":0.3162628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06439300136935261,"score_gpt":0.2568065548535011,"score_spread":0.1924135534841485,"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."}}