{"id":"W2026793228","doi":"10.1080/02664763.2010.545374","title":"A segmented regime-switching model with its application to stock market indices","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Otago","keywords":"Econometrics; Stock market; Stock market index; Volatility (finance); Stock (firearms); Markov chain; Index (typography); Economics; Computer science; Mathematics; Statistics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002461679,0.0005581203,0.0008834149,0.0008053055,0.0004276661,0.0009237856,0.001051974,0.00106793,0.001976445],"category_scores_gemma":[0.008405033,0.0003023231,0.0009817914,0.0007773197,0.0008351273,0.001145094,0.000680747,0.0009591298,0.0002382369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007378297,"about_ca_system_score_gemma":0.0006609959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006712019,"about_ca_topic_score_gemma":0.003125854,"domain_scores_codex":[0.9994656,0.0002403885,0.00002576763,0.0001086707,0.00008569622,0.00007391754],"domain_scores_gemma":[0.9963683,0.00274804,0.0003379924,0.0001940996,0.000234375,0.0001171995],"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":[0.0001398501,0.00009736767,0.005076899,0.00005948572,0.00008893388,0.0001518769,0.0001858292,0.9227999,0.001315104,0.0510871,0.0007289675,0.0182688],"study_design_scores_gemma":[0.000004154107,0.00001594862,0.0002682758,0.000002085017,0.000005124478,0.00001353158,0.000004921024,0.9939839,0.00005664878,0.005520737,0.000119955,0.0000047822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1777484,0.0004224375,0.8170574,0.0003867858,0.00007589043,0.00007493621,0.0002066893,0.0004471223,0.003580414],"genre_scores_gemma":[0.9534805,0.0002993492,0.04356051,0.00006452456,0.00006118928,0.0001127342,0.0002399817,0.00004059807,0.002140661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006712019,"threshold_uncertainty_score":0.0133459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894789656705783,"score_gpt":0.2264263973357313,"score_spread":0.1974785007686735,"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."}}