{"id":"W2096645669","doi":"10.2139/ssrn.1507090","title":"On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; HEC Montréal","funders":"","keywords":"Econometrics; Multivariate statistics; Ranking (information retrieval); Volatility (finance); Statistics; Proxy (statistics); Computer science; Mathematics; Machine learning","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":[0.00939016,0.00103628,0.001321731,0.002138441,0.0004838874,0.002009797,0.0008572008,0.001263661,0.001456218],"category_scores_gemma":[0.02616487,0.0002846463,0.000601189,0.001214235,0.0006219863,0.00255316,0.0008360772,0.001415021,0.0003562823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00063816,"about_ca_system_score_gemma":0.0006580524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003076712,"about_ca_topic_score_gemma":0.001565216,"domain_scores_codex":[0.9979385,0.001137707,0.0001337005,0.0001724802,0.0003933898,0.0002241769],"domain_scores_gemma":[0.9767828,0.01952439,0.001049421,0.001033989,0.001191557,0.0004179084],"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":[0.001134384,0.0003390102,0.01188122,0.0001617075,0.0001618954,0.00008670126,0.00009229566,0.80517,0.002332962,0.01031874,0.00260539,0.1657158],"study_design_scores_gemma":[0.00001018773,0.0001033069,0.001492703,0.00001205995,0.00002211606,0.00001976263,0.00002104808,0.994238,0.0006443057,0.00332727,0.00009619515,0.00001309945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7568508,0.002866872,0.2354031,0.0007868008,0.000152557,0.0000303153,0.0003489321,0.0006244351,0.002936156],"genre_scores_gemma":[0.9820092,0.0005526601,0.01568386,0.0000497101,0.00009581362,0.00001547565,0.0006245509,0.00006302479,0.0009058968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00939016,"threshold_uncertainty_score":0.0496605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03544337416692494,"score_gpt":0.2278483304832991,"score_spread":0.1924049563163741,"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."}}