{"id":"W2979356072","doi":"10.1109/fuzz-ieee.2019.8858826","title":"Fuzzy Option Pricing Using a Novel Data-Driven Feed Forward Neural Network Volatility Model","year":2019,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Valuation of options; Autoregressive conditional heteroskedasticity; Econometrics; Volatility (finance); Fuzzy logic; Implied volatility; Computer science; Black–Scholes model; Artificial neural network; Stochastic volatility; Autoregressive model; Volatility smile; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009471302,0.0002467355,0.0005047631,0.0001919419,0.0002376694,0.0003410584,0.001687043,0.0001337063,0.0002362676],"category_scores_gemma":[0.004340205,0.0001854175,0.000133028,0.001176082,0.00006249446,0.001259879,0.001425827,0.0002740982,0.0000789569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001124078,"about_ca_system_score_gemma":0.000150411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001255776,"about_ca_topic_score_gemma":0.00005347292,"domain_scores_codex":[0.9955047,0.0003743784,0.00092964,0.001157236,0.001454258,0.0005797663],"domain_scores_gemma":[0.9942129,0.002551955,0.000439964,0.002285343,0.000350055,0.0001597327],"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":[0.0001013015,0.00003103163,0.04073597,0.000006173905,0.00001575929,5.08099e-7,0.0001280487,0.9214159,0.002468624,0.0009012274,0.0008395548,0.03335586],"study_design_scores_gemma":[0.0003818733,0.00002606087,0.01225813,0.00002027286,0.00002214587,0.00001254941,0.00008264633,0.969522,0.00001559046,0.01724123,0.0002006469,0.0002168784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4622275,0.00001004726,0.5279552,0.00006656417,0.0005707141,0.0003123354,0.00001308645,0.00007616707,0.008768401],"genre_scores_gemma":[0.5625393,2.572243e-7,0.4361166,0.0001329948,0.0001306295,0.000001924812,0.000008019243,0.00001655003,0.001053768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1003118,"threshold_uncertainty_score":0.7561105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2890495851539418,"score_gpt":0.4300383694543919,"score_spread":0.1409887843004501,"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."}}