{"id":"W100222566","doi":"10.21314/jcf.2010.212","title":"Generalized control variate methods for pricing Asian options","year":2010,"lang":"en","type":"article","venue":"The Journal of Computational Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Control variates; Monte Carlo methods for option pricing; Martingale (probability theory); Monte Carlo method; Variance reduction; Quasi-Monte Carlo method; Mathematics; Stochastic volatility; Random variate; Applied mathematics; Mathematical optimization; Volatility (finance); Computer science; Econometrics; Hybrid Monte Carlo; Statistics; Markov chain Monte Carlo; Random variable","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":[0.001463371,0.00009267734,0.0002841715,0.00009998491,0.0002482135,0.00003466687,0.0003269819,0.00005221302,0.00001891016],"category_scores_gemma":[0.0003468466,0.00007836493,0.0001267783,0.0002198512,0.00006285739,0.0001316337,0.00001674409,0.0002222067,0.00001851878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002188972,"about_ca_system_score_gemma":0.00007891214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000011938,"about_ca_topic_score_gemma":0.000002594727,"domain_scores_codex":[0.9990212,0.00001230314,0.0006678959,0.0001077832,0.00003952091,0.0001513127],"domain_scores_gemma":[0.9981807,0.0005138344,0.0008654214,0.0001339706,0.0002698533,0.0000362521],"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":[0.00004311342,0.0000386394,0.00003580305,0.000005584959,0.00002859995,1.552065e-7,0.0001565077,0.01973574,0.0001877306,0.973717,0.000136476,0.005914631],"study_design_scores_gemma":[0.0008457899,0.00006309192,0.0100216,0.000007312919,0.00002013315,0.00004251762,0.0000081288,0.06258763,0.00002893611,0.9044912,0.0217893,0.00009433153],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007526977,0.0008800005,0.9864296,0.003928993,0.0005596036,0.0002232823,0.00006507373,0.000007603641,0.0003788466],"genre_scores_gemma":[0.5300444,0.00003094368,0.4692463,0.0002929943,0.0002922201,0.00002232136,0.000002958926,0.00001101661,0.00005685093],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5225174,"threshold_uncertainty_score":0.3195629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263451902862075,"score_gpt":0.3032715868717833,"score_spread":0.2769263965855758,"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."}}