{"id":"W3125356077","doi":"10.3390/econometrics3040864","title":"Non-Parametric Estimation of Intraday Spot Volatility: Disentangling Instantaneous Trend and Seasonality","year":2015,"lang":"en","type":"article","venue":"Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Heteroscedasticity; Seasonality; Econometrics; Volatility (finance); Estimator; Parametric statistics; Spot contract; Economics; Mathematics; Statistics; Financial economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001421296,0.0002149312,0.000667577,0.0009192275,0.00008336402,0.00008047467,0.0001983962,0.0001550506,0.00004885047],"category_scores_gemma":[0.00152706,0.0002645037,0.0001099402,0.00200081,0.0001027026,0.0004477577,0.0001018867,0.0001966322,0.00003567601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002517369,"about_ca_system_score_gemma":0.00005952827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002985171,"about_ca_topic_score_gemma":0.00004507749,"domain_scores_codex":[0.9979925,0.00001630479,0.001059017,0.0005270668,0.00008562962,0.0003194896],"domain_scores_gemma":[0.9985339,0.0002175344,0.0005549849,0.0003819008,0.00006464004,0.0002470572],"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":[0.00008295312,0.0002266659,0.9419632,0.0001432142,0.00005206603,0.000006691921,0.001043029,0.003239697,0.000001345086,0.02339027,0.000140845,0.02971005],"study_design_scores_gemma":[0.0007781266,0.0001483497,0.09363128,0.00001676623,0.00001630934,0.000007767551,0.0001463316,0.8667173,0.00003497542,0.03661148,0.001567255,0.00032405],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705167,0.003877985,0.01989836,0.00008287851,0.0004045523,0.0002258687,0.0002918258,0.00003495977,0.004666898],"genre_scores_gemma":[0.9931657,0.0002407994,0.00633488,0.00003514025,0.00007069556,0.000007885851,0.00004272393,0.0000244677,0.00007776033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8634776,"threshold_uncertainty_score":0.9999807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07085584415197826,"score_gpt":0.2444144918895224,"score_spread":0.1735586477375441,"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."}}