{"id":"W2003517149","doi":"10.1016/j.eneco.2014.02.014","title":"Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat","year":2014,"lang":"en","type":"article","venue":"Energy Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":319,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Economics; Volatility (finance); Econometrics; Conditional variance; Stock (firearms); Portfolio; Financial economics; Emerging markets; Stock market; Hedge; Financialization; Autoregressive conditional heteroskedasticity; Monetary economics; Finance","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":[0.001594463,0.0004565167,0.0004907708,0.0005678147,0.000304717,0.001325225,0.0007442849,0.001139369,0.000764974],"category_scores_gemma":[0.00975463,0.000546036,0.0007133026,0.0006586234,0.0004735042,0.00174661,0.0004591177,0.001254408,0.00007130584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008401081,"about_ca_system_score_gemma":0.000718863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01869095,"about_ca_topic_score_gemma":0.01591328,"domain_scores_codex":[0.9997584,0.00009363437,0.00001463773,0.00004961581,0.0000303147,0.00005338434],"domain_scores_gemma":[0.9954172,0.003557617,0.0005862709,0.0001287243,0.000172546,0.0001376213],"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":[0.00009131603,0.00008959109,0.03351013,0.00001601877,0.0001174168,0.0001074798,0.00005242573,0.9498383,0.000393743,0.01248629,0.0003130599,0.002984214],"study_design_scores_gemma":[0.000007647714,0.00001088377,0.002070567,0.00000130477,0.000009321127,0.00000765498,0.00001247095,0.9950308,0.00007495407,0.002725936,0.00004494721,0.000003610358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822056,0.0002002444,0.01588628,0.0004748786,0.00002868982,0.000007799026,0.0001281201,0.00003151814,0.001036955],"genre_scores_gemma":[0.9981295,0.0001249045,0.001034302,0.00001609,0.00002163276,0.000005394205,0.00008670624,0.000007081061,0.000574289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01869095,"threshold_uncertainty_score":0.03716427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161626872465371,"score_gpt":0.200473458615092,"score_spread":0.1843107713685549,"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."}}