{"id":"W2999793792","doi":"10.1002/for.2650","title":"Short‐run wavelet‐based covariance regimes for applied portfolio management","year":2020,"lang":"en","type":"article","venue":"Journal of Forecasting","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Covariance; Portfolio; Wavelet; Econometrics; Computer science; Project portfolio management; Portfolio optimization; Economics; Financial economics; Mathematics; Statistics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009967348,0.0001280951,0.0004192301,0.0001213703,0.00008556288,0.00006166918,0.000227142,0.00005618425,0.00009227186],"category_scores_gemma":[0.0001634993,0.0001361339,0.0002036616,0.0001875335,0.00002040484,0.0001133523,0.00003716711,0.0001611413,0.000003440579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006114533,"about_ca_system_score_gemma":0.000019072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001921147,"about_ca_topic_score_gemma":5.944275e-7,"domain_scores_codex":[0.9985626,0.000006143136,0.0009227194,0.0002180554,0.00005825102,0.0002321774],"domain_scores_gemma":[0.9988084,0.0000883802,0.0007731994,0.0001360652,0.0000678999,0.0001260315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002279291,0.0004829343,0.08022045,0.002094136,0.00116672,0.0002321973,0.0009047213,0.005726609,0.00009874848,0.5832317,0.01946528,0.3040972],"study_design_scores_gemma":[0.001377431,0.00018938,0.007048227,0.00006072173,0.00003521956,0.00001372474,0.00007982529,0.9209533,0.00003424433,0.01927693,0.05064863,0.0002823483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0902849,0.0006362705,0.8239509,0.002105967,0.0005737519,0.0005695702,0.0001028343,0.00002641186,0.08174942],"genre_scores_gemma":[0.9415105,0.00002286226,0.05756857,0.0004059557,0.0002697996,0.000007574282,0.000005362683,0.00002115105,0.0001882148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9152267,"threshold_uncertainty_score":0.5551379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08140277547360625,"score_gpt":0.2344701920577541,"score_spread":0.1530674165841479,"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."}}