{"id":"W2910860963","doi":"10.1111/fire.12171","title":"Higher Moments and Exchange Rate Behavior","year":2019,"lang":"en","type":"article","venue":"Financial Review","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Liberian dollar; Exchange rate; Econometrics; Economics; Pound (networking); Us dollar; Variance (accounting); Financial economics; Monetary economics; Volatility (finance); Computer science; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001688196,0.0002055783,0.0003925599,0.0009919453,0.00009006027,0.0009695011,0.0002150821,0.0004278761,0.002113826],"category_scores_gemma":[0.01142921,0.0001251892,0.0003030583,0.0008622668,0.0002635085,0.0005482979,0.0002689096,0.0004337055,0.0002724163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003459416,"about_ca_system_score_gemma":0.0001511405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001424048,"about_ca_topic_score_gemma":0.0005161011,"domain_scores_codex":[0.9996024,0.0001725362,0.00003292339,0.00005086699,0.0001031119,0.00003829877],"domain_scores_gemma":[0.9921724,0.004520104,0.002318191,0.0004614733,0.000380985,0.0001469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001270161,0.0002468003,0.5834086,0.0003459917,0.0007257738,0.001285168,0.0007084659,0.2024916,0.008920767,0.0810141,0.003930504,0.1156521],"study_design_scores_gemma":[0.00007274132,0.0003112152,0.6801545,0.0001177675,0.0002035145,0.0008156487,0.0002229757,0.2512678,0.003187794,0.05818202,0.005387923,0.00007610927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844571,0.001628771,0.007836729,0.0004149844,0.0000257612,0.000008169567,0.0002860081,0.00009800514,0.005244477],"genre_scores_gemma":[0.999009,0.0002749705,0.0003091831,0.00001372368,0.00002049629,0.000001471911,0.0001056362,0.000004395651,0.0002611127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002113826,"threshold_uncertainty_score":0.00892812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0329075863504723,"score_gpt":0.2555528142586113,"score_spread":0.222645227908139,"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."}}