{"id":"W1574862869","doi":"","title":"The Long and the Short of It: Long Memory Regressors and Predictive Regressions","year":2005,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Predictability; Predictive power; Econometrics; Statistics; Statistic; Mathematics; Regression; Set (abstract data type); Distortion (music); Computer science","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":[0.01354865,0.0007401987,0.001063837,0.001308729,0.0006425284,0.00196253,0.00158956,0.001404639,0.00350982],"category_scores_gemma":[0.1103869,0.0004422551,0.0007000303,0.001415118,0.002624927,0.004957065,0.002447662,0.002891829,0.0004857974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005721617,"about_ca_system_score_gemma":0.001139061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001525872,"about_ca_topic_score_gemma":0.001136797,"domain_scores_codex":[0.9950918,0.002627215,0.0003055723,0.000645498,0.00101755,0.0003123799],"domain_scores_gemma":[0.9160017,0.06818602,0.005530556,0.007889592,0.001737335,0.0006548734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001124437,0.0002556139,0.07103495,0.0002336997,0.0004972887,0.001291715,0.0006476509,0.08922902,0.009871893,0.3879704,0.002984885,0.4348585],"study_design_scores_gemma":[0.0001129845,0.000324289,0.02430006,0.00007154061,0.0001706373,0.000365595,0.0001500581,0.4452738,0.01323707,0.5132358,0.002669153,0.00008905547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2109883,0.0006944965,0.7821049,0.00129008,0.0001033189,0.00007124052,0.000127957,0.000361164,0.004258475],"genre_scores_gemma":[0.9182895,0.0003103175,0.07775276,0.0002722873,0.0003051446,0.0001114496,0.0002062222,0.0001680259,0.00258424],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01354865,"threshold_uncertainty_score":0.07165301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04777458436591326,"score_gpt":0.3064270785904392,"score_spread":0.258652494224526,"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."}}