{"id":"W4389125182","doi":"10.2139/ssrn.4628457","title":"A Variational Autoencoder Approach to Conditional Generation of Possible Future Volatility Surfaces","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Autoencoder; Volatility (finance); SABR volatility model; Econometrics; Economics; Volatility smile; Computer science; Financial economics; Artificial intelligence; Artificial neural network","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":[0.002831549,0.0001151306,0.0002492101,0.0002685407,0.0002046088,0.00005086447,0.0001725852,0.0001139707,0.00004884777],"category_scores_gemma":[0.0001207119,0.0001263283,0.0001165084,0.0004867385,0.00002514912,0.000263883,0.00002945876,0.0005891262,0.00006759704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003056693,"about_ca_system_score_gemma":0.0006221553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009347136,"about_ca_topic_score_gemma":0.00009330064,"domain_scores_codex":[0.9982541,0.00003726529,0.0005653069,0.0002626008,0.0001031635,0.0007775722],"domain_scores_gemma":[0.9994186,0.00003774245,0.0002462292,0.0001333914,0.0001021727,0.0000618517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002157078,0.0000787134,0.02409863,0.000008654111,0.00005643862,1.974604e-7,0.0004456587,0.04497847,0.00004606858,0.9288327,0.0003962378,0.001036671],"study_design_scores_gemma":[0.0002406773,0.00005328187,0.06820016,0.000002598211,0.000003979566,0.00001126761,0.0001364949,0.5013798,0.00000657567,0.4287653,0.001094412,0.0001054555],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5593057,0.0009579249,0.4363481,0.0005938112,0.0002686589,0.0001300582,0.0001227846,0.00003096966,0.002241995],"genre_scores_gemma":[0.9949256,0.0004632468,0.003347098,0.00004137491,0.0005141756,0.000009903072,0.0001008352,0.00001477458,0.0005829811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5000674,"threshold_uncertainty_score":0.5151518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04087812628469947,"score_gpt":0.241894805498708,"score_spread":0.2010166792140086,"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."}}