{"id":"W4299402568","doi":"10.2139/ssrn.241349","title":"A Nonlinear Structural Model for Volatility Clustering","year":2000,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"","keywords":"Volatility clustering; Cluster analysis; Volatility (finance); Econometrics; Nonlinear system; Economics; Mathematics; Computer science; Autoregressive conditional heteroskedasticity; Statistics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002878629,0.0008959408,0.001914456,0.001871024,0.001142988,0.001976685,0.004202597,0.003190711,0.005148081],"category_scores_gemma":[0.0132142,0.001192646,0.001780494,0.002100081,0.001847095,0.003722957,0.00235311,0.002803509,0.001462604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002074961,"about_ca_system_score_gemma":0.001772613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01193674,"about_ca_topic_score_gemma":0.01271176,"domain_scores_codex":[0.9988549,0.0004478038,0.00004941408,0.0003501014,0.0001546694,0.0001431096],"domain_scores_gemma":[0.9946471,0.003327995,0.0006584273,0.0005191393,0.0006201113,0.00022724],"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":[0.00009141582,0.00007144855,0.0018651,0.0000648268,0.00009006251,0.00008641673,0.0001523617,0.8433959,0.0007289107,0.1385875,0.001417084,0.01344881],"study_design_scores_gemma":[0.000007696535,0.000008771957,0.0001718106,0.000003660977,0.00001022665,0.00001027375,0.000007618222,0.9805516,0.0000450936,0.01902823,0.0001474789,0.00000760538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0678669,0.0003174874,0.927254,0.0009949693,0.00009753448,0.00007758867,0.0005000661,0.0002895728,0.002601934],"genre_scores_gemma":[0.8901526,0.0007950802,0.09008965,0.0002331231,0.0002556711,0.0003774842,0.001266221,0.0002384121,0.01659171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01193674,"threshold_uncertainty_score":0.02373457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07833498739325026,"score_gpt":0.3981519333854531,"score_spread":0.3198169459922029,"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."}}