{"id":"W1841135789","doi":"","title":"Dynamic Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns: The Implications for Optimal Portfolio Construction","year":2014,"lang":"en","type":"article","venue":"DergiPark (Istanbul University)","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volatility (finance); Econometrics; Economics; Portfolio; Stock (firearms); Financial economics; Crude oil; Stock market index; Index (typography); Stock market; Computer science; Petroleum engineering; Biology; Geology; Engineering","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":[0.0008327457,0.0002317629,0.0003029746,0.0004870475,0.0002530804,0.001041188,0.0002146232,0.0004027963,0.00111202],"category_scores_gemma":[0.004838126,0.0002095266,0.0004187255,0.0004441769,0.0004522895,0.001331351,0.0006232062,0.0004488345,0.0000578519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000774782,"about_ca_system_score_gemma":0.0009536657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003251646,"about_ca_topic_score_gemma":0.00304623,"domain_scores_codex":[0.9996929,0.00009704891,0.00002263782,0.00006967807,0.00006194531,0.00005577643],"domain_scores_gemma":[0.9981195,0.0009408159,0.0005659543,0.0001167679,0.0001507398,0.0001061006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004161884,0.0004902534,0.501058,0.0002007383,0.0006513514,0.001160158,0.0004662162,0.3162298,0.009820604,0.09120712,0.001163843,0.07713579],"study_design_scores_gemma":[0.00005059914,0.0003293131,0.2919624,0.0000646387,0.0002899704,0.0003692831,0.0008465906,0.6211361,0.00599129,0.0777288,0.001164734,0.00006627836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858665,0.0003234276,0.01092075,0.0002939688,0.000007874345,0.00001300044,0.00005119731,0.00001097252,0.002512318],"genre_scores_gemma":[0.9989581,0.00008402352,0.0007571639,0.000007666084,0.000003236201,0.000002638946,0.00002068903,9.12962e-7,0.0001655575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003251646,"threshold_uncertainty_score":0.006465435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01474269216626876,"score_gpt":0.2053983645780363,"score_spread":0.1906556724117675,"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."}}