{"id":"W3125487332","doi":"10.2139/ssrn.3352688","title":"Derivatives Pricing via Machine Learning","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Business; Economics","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":[0.001772447,0.0004438034,0.001075988,0.001115226,0.0005027818,0.00201316,0.0007594643,0.001320908,0.004354476],"category_scores_gemma":[0.01181246,0.0005270999,0.0006756581,0.0009716992,0.0009477301,0.002602421,0.0009899744,0.002146777,0.0007480505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007750815,"about_ca_system_score_gemma":0.0006756922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001771053,"about_ca_topic_score_gemma":0.001364307,"domain_scores_codex":[0.9992874,0.0003633678,0.000037281,0.0001193826,0.0001510079,0.00004155507],"domain_scores_gemma":[0.9941927,0.004413129,0.0003542076,0.0004602271,0.0004618865,0.0001178662],"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":[0.0001279575,0.0002073709,0.002032692,0.0001100727,0.0001011357,0.000112721,0.00007387195,0.6243704,0.001199257,0.2015471,0.004644522,0.1654729],"study_design_scores_gemma":[0.000003444847,0.000004022026,0.00008604072,0.000003119502,0.000002227317,0.000006884948,9.407598e-7,0.9675601,0.00008772191,0.032082,0.0001608911,0.000002558748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04913305,0.001165655,0.9415249,0.001145367,0.0001905636,0.0000392117,0.0001090218,0.0007374374,0.005954908],"genre_scores_gemma":[0.8779613,0.0008323165,0.1102825,0.0001889404,0.0004150528,0.00006071567,0.0002104864,0.0001234279,0.009925277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004354476,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009042172783850366,"score_gpt":0.2037850843401319,"score_spread":0.1947429115562815,"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."}}