{"id":"W3123568641","doi":"","title":"Is Volatility Clustering of Asset Returns Asymmetric","year":2014,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Toronto Metropolitan University","funders":"","keywords":"Volatility clustering; Stylized fact; Volatility (finance); Econometrics; Cluster analysis; Forward volatility; Volatility swap; Economics; Foreign exchange; Financial economics; Univariate; Implied volatility; Stock (firearms); Monetary economics; Autoregressive conditional heteroskedasticity; Mathematics; Statistics; Multivariate statistics; Geography","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":[0.001641982,0.0002298676,0.000925142,0.002110489,0.00053016,0.002110807,0.001058346,0.001185632,0.001932916],"category_scores_gemma":[0.02066601,0.0005704506,0.0006275076,0.001588228,0.001249634,0.003033412,0.001061344,0.0005874814,0.0005156703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008346289,"about_ca_system_score_gemma":0.0003783462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002326794,"about_ca_topic_score_gemma":0.001177485,"domain_scores_codex":[0.9980986,0.0004351029,0.0001313538,0.0006294816,0.0003879846,0.0003174928],"domain_scores_gemma":[0.9865768,0.003491238,0.005771708,0.002557848,0.001040834,0.0005616366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00134738,0.000391307,0.5426793,0.0003826976,0.001374961,0.00162106,0.002797144,0.1309223,0.02036407,0.1390461,0.007728342,0.1513454],"study_design_scores_gemma":[0.0001301671,0.0001435353,0.4661501,0.00009300697,0.0002095954,0.001503599,0.001092767,0.3419932,0.004980118,0.1801217,0.003403886,0.0001782572],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809038,0.0002606688,0.0151278,0.0004665025,0.00002129696,0.00001724835,0.0002670174,0.00009125796,0.002844346],"genre_scores_gemma":[0.9990317,0.00007520021,0.0005340848,0.00003054711,0.00002885393,0.000004414079,0.0001455019,0.00001512669,0.0001346481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002326794,"threshold_uncertainty_score":0.008683741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06015897997833092,"score_gpt":0.3002151179772685,"score_spread":0.2400561379989376,"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."}}