{"id":"W4318830364","doi":"10.2139/ssrn.4293702","title":"The Role of Macro–Finance Factors in Predicting Market Volatility: A Latent Threshold Dynamic Model","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Fredericton; University of New Brunswick; McMaster University","funders":"","keywords":"Volatility (finance); Macro; Econometrics; Economics; Financial economics; Computer science","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":[0.002122408,0.0007289585,0.001378573,0.00124719,0.0005785837,0.00358354,0.001820245,0.002354867,0.004210111],"category_scores_gemma":[0.007416881,0.0006796158,0.001151451,0.001106305,0.001153929,0.003340487,0.001431081,0.002460332,0.0007488147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008549209,"about_ca_system_score_gemma":0.001102559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009460782,"about_ca_topic_score_gemma":0.005865753,"domain_scores_codex":[0.999375,0.0001749103,0.00003949527,0.0001956595,0.00005373791,0.0001611794],"domain_scores_gemma":[0.9951421,0.003475592,0.0005690655,0.000168356,0.0002558781,0.0003889713],"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":[0.001032106,0.0008379642,0.1253577,0.0001684413,0.0007666252,0.0005969105,0.000499369,0.7689292,0.002654281,0.07430004,0.003384994,0.02147236],"study_design_scores_gemma":[0.0000305031,0.00004981786,0.005044673,0.0000102767,0.00005938266,0.00003062923,0.00003815667,0.9803227,0.00009179964,0.01418075,0.0001218259,0.00001948473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.904102,0.0006671218,0.08811822,0.002780582,0.0001195638,0.0000480955,0.0007565246,0.0002062782,0.003201784],"genre_scores_gemma":[0.995981,0.0002362117,0.00169825,0.00006396528,0.00004754711,0.00001765639,0.00022213,0.00001743551,0.001715916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009460782,"threshold_uncertainty_score":0.0188114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007825560624436697,"score_gpt":0.1924733012737021,"score_spread":0.1846477406492654,"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."}}