{"id":"W2589594047","doi":"10.1111/irfi.12111","title":"A Multivariate Stochastic Volatility Model Applied to a Panel of S&P500 Stocks in Different Industries","year":2017,"lang":"en","type":"article","venue":"International Review of Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Univariate; Econometrics; Multivariate statistics; Portfolio; Volatility (finance); Economics; Stock (firearms); Panel data; Stochastic volatility; Statistics; Financial economics; Mathematics; Engineering","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":[0.003786229,0.0005028527,0.001001196,0.001141233,0.0003900524,0.001451289,0.0009477459,0.0009244838,0.001502535],"category_scores_gemma":[0.007241373,0.0004406035,0.001529174,0.001299619,0.0004164913,0.000898185,0.0007387058,0.001267908,0.0002320811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006793506,"about_ca_system_score_gemma":0.0005701377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02836585,"about_ca_topic_score_gemma":0.01704691,"domain_scores_codex":[0.9990585,0.0004868532,0.00004208325,0.0001839766,0.000116567,0.0001119889],"domain_scores_gemma":[0.9957783,0.002710063,0.0006596034,0.0003557712,0.0003159317,0.000180285],"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":[0.0001792046,0.0001615062,0.114648,0.00003279242,0.0004851523,0.0001824861,0.00009163034,0.8641673,0.001435,0.005981138,0.0007999603,0.01183579],"study_design_scores_gemma":[0.00001335861,0.00003871318,0.02034836,0.00000668663,0.00004259413,0.00001428271,0.00002474649,0.9772954,0.0003175724,0.001737475,0.0001430386,0.00001790297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9364472,0.0001431126,0.06146168,0.0003527837,0.00001934592,0.00004164313,0.0007424927,0.00008987637,0.0007019663],"genre_scores_gemma":[0.9936489,0.0001019035,0.004777275,0.00002904174,0.00002045736,0.00002272784,0.0009380049,0.000007959949,0.0004535335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02836585,"threshold_uncertainty_score":0.05640149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1314061026486669,"score_gpt":0.3234112625541042,"score_spread":0.1920051599054373,"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."}}