{"id":"W2165124641","doi":"10.1016/j.csda.2013.06.023","title":"Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models","year":2014,"lang":"en","type":"article","venue":"CBS Research Portal (Copenhagen Business School)","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"Danmarks Grundforskningsfond","keywords":"Heteroscedasticity; Econometrics; Bayesian inference; Inference; Valuation of options; Bayesian probability; Model selection; Bayes factor; Economics; Mathematics; Statistics; Computer science; Artificial intelligence","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":[0.008062919,0.00124256,0.002053477,0.001343898,0.0006284281,0.004276888,0.002385072,0.002267511,0.006603559],"category_scores_gemma":[0.02610364,0.001376014,0.002302632,0.002017234,0.001404907,0.005551102,0.001828588,0.002956647,0.001192521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597633,"about_ca_system_score_gemma":0.00153536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004757317,"about_ca_topic_score_gemma":0.003929705,"domain_scores_codex":[0.9950617,0.002937834,0.0002068454,0.0005081611,0.001019792,0.0002656044],"domain_scores_gemma":[0.9886284,0.008905994,0.0007699015,0.0006604508,0.000825627,0.00020956],"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":[0.00009478258,0.00006576131,0.0009483136,0.000101156,0.0001319401,0.0001986568,0.0001031977,0.5354277,0.0008433993,0.4357089,0.00132572,0.02505045],"study_design_scores_gemma":[0.00001186939,0.00001452321,0.0001999092,0.00001365826,0.00001658312,0.00003642562,0.000008176789,0.8707823,0.000198226,0.1280033,0.0006927709,0.00002229279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006900203,0.0003539029,0.9898584,0.0003107786,0.00003932235,0.00003001707,0.00009963629,0.0001666129,0.002241115],"genre_scores_gemma":[0.6255748,0.002317237,0.3515333,0.0003180295,0.0004304067,0.0004133828,0.0009721851,0.0004196052,0.01802106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008062919,"threshold_uncertainty_score":0.04264128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1128235891398483,"score_gpt":0.3116570106390796,"score_spread":0.1988334214992314,"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."}}