{"id":"W3015033710","doi":"10.20944/preprints202003.0465.v1","title":"Modeling the Co-Movement of Inflation and Exchange Rate","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Division of Mathematical Sciences","keywords":"Economics; Exchange rate; Autoregressive conditional heteroskedasticity; Econometrics; Stylized fact; Granger causality; Inflation (cosmology); Copula (linguistics); Volatility (finance); Monetary economics; Macroeconomics","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":[0.0008372355,0.0005314256,0.0006315798,0.000463124,0.0002223332,0.001720255,0.0007657197,0.00160366,0.002134515],"category_scores_gemma":[0.003226412,0.0005361588,0.0008028253,0.0007665539,0.0004228687,0.001037676,0.0008543456,0.0009943628,0.0003703769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006903201,"about_ca_system_score_gemma":0.0009199607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01348957,"about_ca_topic_score_gemma":0.007795094,"domain_scores_codex":[0.999662,0.0001275031,0.00001739871,0.0000919588,0.00003769518,0.00006339522],"domain_scores_gemma":[0.9988596,0.0007313473,0.0002550273,0.00004043184,0.00006319657,0.00005029186],"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":[0.0000618714,0.00006660515,0.009690604,0.00005086739,0.0001037796,0.0002452942,0.0001099615,0.9326637,0.0008910974,0.04555025,0.0009718887,0.009593979],"study_design_scores_gemma":[0.000005606677,0.00001088024,0.0009393762,0.000004226141,0.00001460243,0.00002292529,0.00001085761,0.9923699,0.00005759147,0.006145494,0.0004130535,0.000005507776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4823038,0.00169066,0.4955186,0.002646616,0.0001962275,0.00007309856,0.001030332,0.0005345244,0.01600621],"genre_scores_gemma":[0.9750275,0.000764875,0.01432758,0.00008087131,0.00008477917,0.00007171432,0.0003406784,0.0000650603,0.009236956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01348957,"threshold_uncertainty_score":0.02682209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1760594348114353,"score_gpt":0.3107950281775934,"score_spread":0.1347355933661581,"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."}}