{"id":"W1545991674","doi":"10.1002/ijfe.1458","title":"Examining realized volatility regimes under a threshold stochastic volatility model","year":2012,"lang":"en","type":"article","venue":"International Journal of Finance & Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Stochastic volatility; Econometrics; Threshold model; Volatility (finance); Threshold limit value; Economics; Realized variance; Implied volatility; Leverage (statistics); Leverage effect; Markov chain Monte Carlo; Forward volatility; Bayesian probability; Mathematics; Statistics; Autoregressive conditional heteroskedasticity","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":[0.001877816,0.0002672982,0.0007170098,0.0003348893,0.0001074399,0.0001074897,0.000727157,0.0001926699,0.00008979861],"category_scores_gemma":[0.0003528674,0.0003184904,0.0003034889,0.0001083022,0.000107583,0.001631098,0.0001362544,0.0004505236,0.00004559271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005514844,"about_ca_system_score_gemma":0.000155355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008872067,"about_ca_topic_score_gemma":0.00002280845,"domain_scores_codex":[0.9972164,0.00001960918,0.001834024,0.000358015,0.0001062347,0.0004657292],"domain_scores_gemma":[0.9973559,0.0001280216,0.001685794,0.0003900028,0.0002881772,0.0001520814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007268746,0.0005781521,0.2618165,0.00002302915,0.0003309561,0.000005276284,0.002411155,0.2373883,0.000034358,0.4902461,0.0009245004,0.005514801],"study_design_scores_gemma":[0.001147193,0.00005786736,0.04419816,0.00006033902,0.00001767721,0.00003479741,0.00008772031,0.7805403,0.00003511132,0.170899,0.002568351,0.0003534766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.815522,0.002006282,0.1773948,0.0004009967,0.001810864,0.0001132997,0.0001416664,0.00001709761,0.002593041],"genre_scores_gemma":[0.9918522,0.0005319311,0.006246102,0.0002961351,0.0007145302,0.000007087994,0.00001165869,0.00003627714,0.0003041323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.543152,"threshold_uncertainty_score":0.9999267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09157239541207723,"score_gpt":0.2766962494437558,"score_spread":0.1851238540316786,"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."}}