{"id":"W2735805631","doi":"10.2139/ssrn.891127","title":"An Empirical Comparison of Affine and Non-Affine Models for Equity Index Options","year":2006,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Affine transformation; Affine shape adaptation; Econometrics; Affine combination; Computer science; Affine hull; Mathematics; Stochastic volatility; Applied mathematics; Volatility (finance); Affine space; Pure mathematics","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":[0.006527368,0.000620737,0.0009274145,0.00100905,0.0004485787,0.003697779,0.002131014,0.00138286,0.006835243],"category_scores_gemma":[0.02795865,0.0003409144,0.001141006,0.001355695,0.0008433179,0.003638812,0.001192263,0.001436414,0.0007268507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052081,"about_ca_system_score_gemma":0.0003885918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002627967,"about_ca_topic_score_gemma":0.002347567,"domain_scores_codex":[0.9989178,0.0005655736,0.00009093896,0.00017127,0.0001587159,0.00009563698],"domain_scores_gemma":[0.9654136,0.02830345,0.002879443,0.001826468,0.0008115912,0.0007654775],"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":[0.00463432,0.001330042,0.1811948,0.0005661614,0.0007775842,0.001122301,0.001411855,0.488708,0.004114164,0.2490358,0.00658125,0.0605238],"study_design_scores_gemma":[0.0001537635,0.0003809448,0.0402114,0.00003771831,0.0002043475,0.0002716662,0.0005453725,0.8800067,0.0008226719,0.07580257,0.001494663,0.00006817501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819494,0.0008924057,0.01307942,0.0004520875,0.0000372139,0.0000251534,0.0002947403,0.00009497593,0.00317461],"genre_scores_gemma":[0.9973027,0.0002088026,0.0009595269,0.0000247912,0.00003855842,0.000007175135,0.0004015294,0.00002344318,0.001033619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006835243,"threshold_uncertainty_score":0.03452039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548300217348807,"score_gpt":0.3245629641328188,"score_spread":0.2790799619593307,"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."}}