{"id":"W2911649252","doi":"10.3390/jrfm11030052","title":"Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis","year":2018,"lang":"en","type":"preprint","venue":"Journal of risk and financial management","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Volatility (finance); Econometrics; Conditional variance; Realized variance; Conditional expectation; Nonparametric statistics; Mathematics; Conditional probability distribution; Bayesian probability; Stochastic volatility; Parametric statistics; Forward volatility; Statistics; Economics; Autoregressive conditional heteroskedasticity","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.009533132,0.0007701226,0.001496523,0.001987301,0.0007070485,0.002464874,0.002166548,0.002050876,0.002055992],"category_scores_gemma":[0.03337757,0.001015223,0.001571418,0.001361793,0.002520982,0.00367156,0.001814423,0.002709147,0.0003424751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001492753,"about_ca_system_score_gemma":0.001319022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01013561,"about_ca_topic_score_gemma":0.00620982,"domain_scores_codex":[0.9965383,0.002086117,0.0001024054,0.0005077966,0.0005607532,0.0002046394],"domain_scores_gemma":[0.986101,0.01161712,0.0008096424,0.0007500597,0.000539599,0.0001826194],"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":[0.0001690833,0.0001604015,0.008269101,0.0001269487,0.0002492066,0.0002688724,0.0003233813,0.5986626,0.001384487,0.3362977,0.002249549,0.05183866],"study_design_scores_gemma":[0.00001384297,0.00001676449,0.001082632,0.0000172726,0.00001843607,0.00004620364,0.0000214185,0.9046434,0.00009969599,0.09342753,0.0005908575,0.00002201417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05127211,0.0005197159,0.9442373,0.001210461,0.00003495887,0.00006377947,0.0002664968,0.0002153172,0.002179812],"genre_scores_gemma":[0.8770713,0.0009331935,0.1152042,0.0004349253,0.0002692181,0.0002472304,0.0004989498,0.0001031554,0.005237885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01013561,"threshold_uncertainty_score":0.05041665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01552852047851566,"score_gpt":0.2247014100459537,"score_spread":0.209172889567438,"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."}}