{"id":"W1979818263","doi":"10.1111/1467-9892.00227","title":"On the Distributional Properties of GARCH Processes","year":2001,"lang":"en","type":"article","venue":"Journal of Time Series Analysis","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Mathematics; Econometrics; Heteroscedasticity; Autoregressive model; Series (stratigraphy); Class (philosophy); Statistics; Volatility (finance); Computer science; Artificial intelligence","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":[0.0006446301,0.00007702075,0.0004050086,0.0002272693,0.0001013197,0.00003357134,0.0002033029,0.00003663601,0.0005929146],"category_scores_gemma":[0.0006314933,0.00005210846,0.0002818431,0.0008201232,0.0000742329,0.0002031915,0.00002281532,0.0001176392,0.00002965815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003720073,"about_ca_system_score_gemma":0.00004855119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006546271,"about_ca_topic_score_gemma":0.00002014671,"domain_scores_codex":[0.9990105,0.00001487341,0.0006798065,0.00009496037,0.00008407535,0.0001157608],"domain_scores_gemma":[0.9988874,0.00005995656,0.0006170649,0.0001425671,0.0002632292,0.00002973672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00280329,0.00137506,0.6628935,0.0003287263,0.007790429,0.00002859137,0.003459949,0.07798675,0.001182591,0.2348737,0.005182019,0.00209533],"study_design_scores_gemma":[0.002800363,0.003708366,0.2464111,0.0008102101,0.003127764,0.0001550849,0.002673433,0.1886644,0.01675174,0.4045818,0.1281277,0.002187965],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884273,0.002129536,0.00621917,0.00196872,0.00003599937,0.00003893749,0.00005276842,0.000003044562,0.001124517],"genre_scores_gemma":[0.9983079,0.0006206671,0.0001443578,0.00003456384,0.00006465739,0.000001250785,0.000003018935,0.000004598539,0.000819026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4164824,"threshold_uncertainty_score":0.6492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287885981900563,"score_gpt":0.2080422961522004,"score_spread":0.1751634363331948,"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."}}