{"id":"W1585146667","doi":"10.1007/978-1-4614-3433-7_5","title":"American Option Pricing Using Simulation and Regression: Numerical Convergence Results","year":2012,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Convergence (economics); Valuation of options; Stochastic game; Rate of convergence; Monte Carlo method; Regression; Econometrics; Mathematics; Applied mathematics; Function (biology); Economics; Computer science; Mathematical economics; Statistics; Key (lock)","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":[0.008712912,0.001487574,0.002270197,0.00352442,0.001170977,0.003149575,0.002361278,0.003315866,0.005398173],"category_scores_gemma":[0.0540542,0.001057191,0.001938332,0.003626715,0.003130985,0.004879549,0.002638508,0.004772084,0.0008209899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001386263,"about_ca_system_score_gemma":0.001801926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006169731,"about_ca_topic_score_gemma":0.003325782,"domain_scores_codex":[0.9979213,0.001291651,0.0001003774,0.0001788192,0.0004083189,0.00009960337],"domain_scores_gemma":[0.9512676,0.04016868,0.00141853,0.002217517,0.004139777,0.0007878733],"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":[0.0001549148,0.0001736918,0.001622836,0.0001551478,0.0001371052,0.00009262998,0.0001495792,0.672364,0.0008066955,0.292441,0.003094039,0.02880842],"study_design_scores_gemma":[0.000007172773,0.00000552236,0.00006545621,0.00001692758,0.000007066791,0.00001414864,0.000006116386,0.9740615,0.0001065557,0.02546172,0.0002416911,0.000006107649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03264626,0.003426789,0.9460658,0.00129418,0.0003004784,0.00006934745,0.0001318376,0.0003992204,0.01566608],"genre_scores_gemma":[0.6343741,0.005257984,0.3400399,0.0005594325,0.0006900919,0.000490608,0.0007389039,0.0008036238,0.01704543],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008712912,"threshold_uncertainty_score":0.04607886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05623301805113582,"score_gpt":0.2843038837225916,"score_spread":0.2280708656714558,"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."}}