{"id":"W4407738797","doi":"10.1016/j.frl.2025.106940","title":"Putting VAR forecasts of the real price of crude oil to the test","year":2025,"lang":"en","type":"article","venue":"Finance research letters","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Bank of Canada","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Crude oil; Economics; Oil price; Econometrics; Vector autoregression; Test (biology); Financial economics; Monetary economics; Petroleum engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004830045,0.0004884963,0.0008425311,0.001032647,0.0002894527,0.002305889,0.0008945594,0.0007967474,0.003695844],"category_scores_gemma":[0.03517781,0.0002792123,0.0006083606,0.0005792088,0.0004499056,0.00267047,0.0008053063,0.001549991,0.001047352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008052284,"about_ca_system_score_gemma":0.001250095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006794442,"about_ca_topic_score_gemma":0.005407746,"domain_scores_codex":[0.9977533,0.0007758998,0.0001404408,0.0004081053,0.0007688323,0.0001534271],"domain_scores_gemma":[0.9844572,0.009814624,0.0009261763,0.002157951,0.002445179,0.0001989185],"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":[0.001756191,0.000260568,0.105903,0.0003703407,0.001166707,0.0004935308,0.0002814946,0.4997369,0.01252756,0.08107038,0.01426283,0.2821705],"study_design_scores_gemma":[0.0001047537,0.0006799577,0.04515743,0.0001513021,0.000249997,0.0001764101,0.00028164,0.8791084,0.01959845,0.04524079,0.009087984,0.0001629257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7430964,0.001243764,0.2107982,0.002991268,0.001052165,0.0000518378,0.002940874,0.002472995,0.03535261],"genre_scores_gemma":[0.9801834,0.0001513035,0.01692907,0.0001798358,0.0001017325,0.000009916573,0.001123115,0.0001120424,0.001209614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006794442,"threshold_uncertainty_score":0.02554405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04263595106867825,"score_gpt":0.2938243872174368,"score_spread":0.2511884361487586,"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."}}