{"id":"W4220730889","doi":"10.3390/jrfm15030126","title":"The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Volatility (finance); Stock market index; Index (typography); Econometrics; Stock market; Logistic regression; Equity (law); Financial economics; Statistics; Mathematics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002485048,0.0001015011,0.0002367243,0.0000883365,0.0006195755,0.00005925423,0.0004870291,0.00002427254,0.0001594954],"category_scores_gemma":[0.000113153,0.00005471119,0.0002605153,0.0001779305,0.00007632509,0.00004984139,0.0002792102,0.0003488212,0.00000159624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001322074,"about_ca_system_score_gemma":0.00002873358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002377861,"about_ca_topic_score_gemma":0.00002661672,"domain_scores_codex":[0.9989923,0.00006939586,0.0005866273,0.0001232629,0.00006650185,0.0001619647],"domain_scores_gemma":[0.9984999,0.000185826,0.0009598884,0.0003041527,0.00002146964,0.00002880751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003561039,0.0001580468,0.5917203,0.00001506754,0.0001584672,0.000003797822,0.00036033,0.002854719,7.852797e-7,0.3644796,0.005447545,0.03444524],"study_design_scores_gemma":[0.0003979144,0.000158539,0.7552617,0.000007797488,0.00001529879,0.000004213606,0.0001361796,0.008139028,6.425341e-7,0.1481974,0.08760481,0.00007649634],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988184,0.0009797105,0.001230065,0.0006463757,0.0006801778,0.0002333925,0.0001633578,0.000001894159,0.007881031],"genre_scores_gemma":[0.9977515,0.001764887,0.0000221855,0.0001000254,0.00007111221,0.000008396234,3.728707e-7,0.000007437467,0.0002740707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2162822,"threshold_uncertainty_score":0.4765336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008045762657948275,"score_gpt":0.1988617722364666,"score_spread":0.1908160095785183,"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."}}