{"id":"W1605241249","doi":"10.1080/00949655.2015.1060235","title":"Bayesian inference of asymmetric stochastic conditional duration models","year":2015,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Markov chain Monte Carlo; Inference; Particle filter; Bayesian inference; Econometrics; Bayesian probability; Statistics; Computer science; Artificial intelligence; Kalman filter","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":[0.0005950031,0.00006949651,0.0002601713,0.0002914733,0.00003981639,0.00003179923,0.00003808998,0.00005404097,0.00001220223],"category_scores_gemma":[0.001086405,0.00007415857,0.00003241449,0.0001818139,0.00004292416,0.0003999046,0.00001083011,0.0001007759,0.000003756868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000486356,"about_ca_system_score_gemma":0.00005466271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000205938,"about_ca_topic_score_gemma":0.000001538267,"domain_scores_codex":[0.9987844,0.00002682428,0.0009012753,0.0001012175,0.0001094082,0.00007693331],"domain_scores_gemma":[0.9983902,0.0004408308,0.0006377919,0.00003672868,0.0003966259,0.00009780146],"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":[0.00005160266,0.00003604823,0.001224632,0.00001171683,0.00000794813,6.581441e-7,0.000270505,0.8115149,0.000001259414,0.183993,0.00001995544,0.002867799],"study_design_scores_gemma":[0.0004066842,0.0001150481,0.006881221,0.000008728563,0.000005127967,0.000001788549,0.00002589847,0.5825002,0.000001021423,0.4100054,0.00000755109,0.00004135952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06742273,0.0001904005,0.9318401,0.00006023442,0.000108974,0.00006496481,0.00006545705,0.000004121031,0.0002430394],"genre_scores_gemma":[0.9731707,0.000007588993,0.02670677,0.00002422881,0.00004974637,5.07307e-7,0.00003070868,0.000005244854,0.000004499813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.905748,"threshold_uncertainty_score":0.3024099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08635199570709687,"score_gpt":0.3130797651868325,"score_spread":0.2267277694797356,"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."}}