{"id":"W4386417658","doi":"10.3390/jrfm16090392","title":"Simulation Framework to Determine Suitable Innovations for Volatility Persistence Estimation: The GARCH Approach","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Heteroscedasticity; Econometrics; Volatility (finance); Estimator; Computer science; Autoregressive model; Monte Carlo method; Consistency (knowledge bases); SABR volatility model; Stochastic volatility; Statistics; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001994904,0.0001087688,0.000271094,0.0003301645,0.0004041282,0.0000835227,0.0001946529,0.00007441393,0.000005026961],"category_scores_gemma":[0.001675315,0.00009642234,0.0001083705,0.0008508579,0.00003368347,0.0002054382,0.00008225628,0.0002006896,0.00001113526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005220605,"about_ca_system_score_gemma":0.00001720796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002243739,"about_ca_topic_score_gemma":0.000006374197,"domain_scores_codex":[0.9987691,0.00001605476,0.0007012797,0.0002118675,0.00008089921,0.0002208099],"domain_scores_gemma":[0.9988711,0.0003563238,0.0003733424,0.0002000319,0.0001477362,0.00005145244],"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":[0.0002552309,0.0001516792,0.0563113,0.0001823614,0.00004334143,0.00000325979,0.005808603,0.4672477,0.000001187808,0.2528731,0.001363768,0.2157584],"study_design_scores_gemma":[0.0003010013,0.0001075751,0.1274755,0.00002883421,0.00002282728,7.41529e-7,0.000241736,0.7161076,0.00000111433,0.1264321,0.02916331,0.000117615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2403801,0.0003180605,0.7581794,0.0002733358,0.0002521311,0.0003441369,0.00004696005,0.00001135104,0.0001945887],"genre_scores_gemma":[0.9477596,0.0002012639,0.05155687,0.0001115549,0.0001875007,0.00002948732,0.000005679252,0.00001011242,0.0001379215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7073796,"threshold_uncertainty_score":0.3931989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07201260259964296,"score_gpt":0.2752417597114739,"score_spread":0.2032291571118309,"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."}}