{"id":"W2894595594","doi":"10.2139/ssrn.2966352","title":"Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement","year":2017,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"Leonard N. Stern School of Business, New York University","keywords":"Autoregressive conditional heteroskedasticity; Autoregressive model; Mathematics; Econometrics; Volatility (finance); Economics; Humanities; Philosophy","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":[0.003650717,0.001025973,0.001678646,0.001288556,0.0005513653,0.001723819,0.001709834,0.001578732,0.002743631],"category_scores_gemma":[0.01807784,0.0008278831,0.001407757,0.00132694,0.0009703255,0.002136582,0.001586543,0.002012476,0.0003012792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006823279,"about_ca_system_score_gemma":0.001128514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001858042,"about_ca_topic_score_gemma":0.001256741,"domain_scores_codex":[0.9988766,0.0005956165,0.0000550428,0.0001448715,0.0002276586,0.0001002122],"domain_scores_gemma":[0.9927586,0.00525744,0.0008151537,0.0004741066,0.0004987246,0.0001959057],"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":[0.0000908582,0.00008461125,0.003171543,0.0001157141,0.0001591737,0.0002206961,0.0001349114,0.6511998,0.002007992,0.30945,0.001468003,0.03189676],"study_design_scores_gemma":[0.000004313516,0.000008793724,0.0002324118,0.000005387726,0.00000961343,0.0000182266,0.000006812082,0.9564276,0.0002101436,0.04287189,0.0001971947,0.000007559858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07362747,0.0009816784,0.9219076,0.0007081889,0.00007538107,0.00002594038,0.0001184615,0.0002485504,0.002306714],"genre_scores_gemma":[0.9351644,0.001067323,0.05848975,0.000103446,0.0003531293,0.00006928969,0.0003005814,0.0001764656,0.004275559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003650717,"threshold_uncertainty_score":0.01930702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04890154915592922,"score_gpt":0.2624627391495572,"score_spread":0.213561189993628,"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."}}