{"id":"W2788150211","doi":"10.1080/07350015.2017.1415910","title":"A New Approach to Volatility Modeling: The Factorial Hidden Markov Volatility Model","year":2018,"lang":"en","type":"article","venue":"Journal of Business and Economic Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Montréal","funders":"","keywords":"Volatility (finance); Econometrics; Stochastic volatility; Markov chain; Forward volatility; Leverage (statistics); Implied volatility; Computer science; Economics; Mathematics; Statistics","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":[0.002074268,0.000925403,0.001236331,0.0010278,0.0004614301,0.001745352,0.002209954,0.001433282,0.002093174],"category_scores_gemma":[0.006118277,0.0005070746,0.001470527,0.001329338,0.0007276776,0.002629163,0.001093041,0.002215258,0.0004188676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091806,"about_ca_system_score_gemma":0.001313066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005455369,"about_ca_topic_score_gemma":0.003894129,"domain_scores_codex":[0.9988788,0.0004681634,0.00006123155,0.0002463932,0.0002432801,0.0001021766],"domain_scores_gemma":[0.9984924,0.001030833,0.0001808215,0.0001187067,0.0001231984,0.00005408729],"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":[0.00008122439,0.00006740414,0.0047213,0.0001579251,0.0002612849,0.0002581238,0.0001464681,0.5960565,0.002471691,0.3372052,0.003718479,0.05485445],"study_design_scores_gemma":[0.000009121246,0.0000181796,0.0003747646,0.00001434609,0.00002587698,0.00004456978,0.000006724239,0.9232063,0.0002177501,0.07427487,0.001787019,0.00002058565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006650887,0.001132282,0.9894699,0.0005024269,0.0001538953,0.00002356869,0.0002786187,0.0002417055,0.001546746],"genre_scores_gemma":[0.7131696,0.0046855,0.2711392,0.0005987952,0.001181018,0.0003133895,0.001309376,0.0001996569,0.007403356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005455369,"threshold_uncertainty_score":0.01096994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06373866333266008,"score_gpt":0.2541139867581603,"score_spread":0.1903753234255002,"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."}}