{"id":"W3193155117","doi":"10.1002/for.993","title":"Forecasting volatility","year":2006,"lang":"en","type":"article","venue":"Journal of Forecasting","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Volatility (finance); Econometrics; Forward volatility; Implied volatility; Stochastic volatility; Volatility smile; Economics; Realized variance; Volatility swap; Volatility risk premium","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00165588,0.0001345805,0.0004443607,0.0002305579,0.0001593273,0.00006717134,0.0001883847,0.00008786804,0.00007291303],"category_scores_gemma":[0.0007494918,0.0001418767,0.0002432995,0.0002404066,0.00003486768,0.0004518168,0.00003912798,0.0003048107,0.00001257965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001059127,"about_ca_system_score_gemma":0.00003382385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002418892,"about_ca_topic_score_gemma":0.00003482886,"domain_scores_codex":[0.9979655,0.00001303549,0.001464379,0.0001784946,0.00007230659,0.0003063161],"domain_scores_gemma":[0.9981949,0.0001214694,0.001324164,0.0001394822,0.0001562819,0.00006372095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000118218,0.0002095301,0.9117231,0.0001105218,0.00005399071,0.00007713697,0.0006796826,0.006962231,0.0000956947,0.03683462,0.001603404,0.04153183],"study_design_scores_gemma":[0.0006473268,0.0001375286,0.02166963,0.0001072062,0.00001143578,0.0001500789,0.00005644805,0.8113256,0.0001322541,0.1551959,0.01032437,0.0002422065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386166,0.002010122,0.04349183,0.0001082225,0.0005466116,0.00006272214,0.00001491678,0.00001334465,0.01513563],"genre_scores_gemma":[0.9854399,0.00001129006,0.01354546,0.00002765739,0.0007891805,8.720726e-7,0.000001719006,0.00001882778,0.0001651036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8900535,"threshold_uncertainty_score":0.5785563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08245622204750369,"score_gpt":0.2241866021693835,"score_spread":0.1417303801218798,"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."}}