{"id":"W2107781784","doi":"10.1016/j.jeconom.2014.08.002","title":"Multi-scale tests for serial correlation","year":2014,"lang":"en","type":"article","venue":"Journal of Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Autocorrelation; Mathematics; Monte Carlo method; Wavelet; Correlation; Statistics; Variance (accounting); Scale (ratio); Statistical hypothesis testing; Multivariate statistics; Algorithm; Computer science; Artificial intelligence","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":[0.03019574,0.001263136,0.002141193,0.005142084,0.002118663,0.003249682,0.002613713,0.002778579,0.01990066],"category_scores_gemma":[0.1731105,0.0008100851,0.004031074,0.005613046,0.003204877,0.006591589,0.003513384,0.00277705,0.002095558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004861353,"about_ca_system_score_gemma":0.0008375488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009012273,"about_ca_topic_score_gemma":0.000932864,"domain_scores_codex":[0.9566145,0.0254257,0.003574065,0.008074591,0.004639614,0.00167153],"domain_scores_gemma":[0.4678002,0.4698125,0.01914434,0.03425357,0.005860174,0.003129199],"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":[0.005046214,0.001325688,0.8044935,0.0005660888,0.01357695,0.003401479,0.001731573,0.01756996,0.00584987,0.04114628,0.008895874,0.0963965],"study_design_scores_gemma":[0.001177256,0.003387925,0.7707824,0.0001870663,0.002062648,0.002191414,0.002152063,0.1519584,0.003118533,0.05741907,0.005237788,0.0003255818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.922431,0.0005727785,0.0631009,0.000564156,0.000430842,0.0001616877,0.002163244,0.0004461969,0.01012922],"genre_scores_gemma":[0.989213,0.00005929798,0.007509479,0.0000974643,0.0001842892,0.0001617649,0.001222894,0.0001094937,0.001442167],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03019574,"threshold_uncertainty_score":0.1596923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1638472878356485,"score_gpt":0.2617431466855746,"score_spread":0.09789585884992605,"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."}}