{"id":"W2003689225","doi":"10.1142/s0219024905003177","title":"LOCALIZED MONTE CARLO ALGORITHM TO COMPUTE PRICES OF PATH DEPENDENT OPTIONS ON TREES","year":2005,"lang":"en","type":"article","venue":"International Journal of Theoretical and Applied Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Monte Carlo method; Probabilistic logic; Algorithm; Path (computing); Monte Carlo algorithm; Computer science; Tree (set theory); Probabilistic analysis of algorithms; Mathematical optimization; Mathematics; Artificial intelligence; Statistics; Combinatorics","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":[0.001532851,0.0005025577,0.000834743,0.0008575039,0.0005004847,0.0008644068,0.001166546,0.001017518,0.004002874],"category_scores_gemma":[0.00699819,0.0004891682,0.0005340905,0.001197022,0.0008569493,0.00125826,0.00117539,0.001661366,0.0008764535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008970457,"about_ca_system_score_gemma":0.001485337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003885303,"about_ca_topic_score_gemma":0.00397393,"domain_scores_codex":[0.9993969,0.0002878741,0.00003076866,0.00006769844,0.0001668101,0.00004996295],"domain_scores_gemma":[0.9971688,0.002002596,0.0001420895,0.0002268097,0.0003510579,0.0001087409],"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":[0.0001093158,0.00005647097,0.0007716087,0.00004793502,0.00005479339,0.00007637811,0.00005962839,0.8735493,0.001714293,0.05810638,0.001327105,0.06412682],"study_design_scores_gemma":[0.00001217457,0.000008088665,0.00004102333,0.000002863364,0.000003252399,0.00001076473,0.00000181918,0.9903067,0.0002431821,0.008933677,0.0004329936,0.000003502771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003176523,0.0000591002,0.9960316,0.00003460701,0.0000127081,0.00001859337,0.00001541336,0.0002503187,0.0004011029],"genre_scores_gemma":[0.1685883,0.0002109031,0.8279363,0.00009677764,0.00004718581,0.0003662552,0.0001994418,0.0001627261,0.002392144],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004002874,"threshold_uncertainty_score":0.01339096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009233659103891805,"score_gpt":0.2298067867360742,"score_spread":0.2205731276321824,"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."}}