{"id":"W3021305677","doi":"10.1017/s174849952000010x","title":"Asymmetry in mortality volatility and its implications on index-based longevity hedging","year":2020,"lang":"en","type":"article","venue":"Annals of Actuarial Science","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Actua; University of Waterloo","funders":"","keywords":"Longevity; Volatility (finance); Hedge; Heteroscedasticity; Econometrics; Longevity risk; Autoregressive conditional heteroskedasticity; Economics; Index (typography); Financial economics; Biology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003579939,0.0001333801,0.0002436002,0.000204586,0.0005171339,0.0001134715,0.0006674292,0.00007492192,0.00003329437],"category_scores_gemma":[0.001757726,0.0001347258,0.00007681811,0.002203329,0.001106441,0.0005974105,0.000124413,0.0001864123,0.000005073895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004262347,"about_ca_system_score_gemma":0.0003400513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002974786,"about_ca_topic_score_gemma":0.001892734,"domain_scores_codex":[0.9975173,0.00020935,0.0003650652,0.0005621262,0.000870536,0.0004756126],"domain_scores_gemma":[0.9987761,0.0001830258,0.0002042079,0.0003050946,0.0002492228,0.0002823577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005854553,0.0001921494,0.946937,0.00003934903,0.00001164582,0.000002093156,0.00247928,0.0001710776,0.0005002876,0.04077408,0.0001432199,0.008691261],"study_design_scores_gemma":[0.0001919681,0.00006422972,0.9926597,0.00001886347,0.000006477179,2.718821e-8,0.0002501729,0.002353069,0.001223324,0.002464002,0.0006267767,0.0001413487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804855,0.00005940247,0.0002578804,0.009770327,0.0001664666,0.0004877252,0.0000235592,0.00004582079,0.008703347],"genre_scores_gemma":[0.9980006,0.00006169857,0.00006469103,0.001745993,0.0001053086,0.00001245096,0.000001456857,0.000004760374,0.000003103105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04572273,"threshold_uncertainty_score":0.5493957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1721684167972752,"score_gpt":0.4195325013111974,"score_spread":0.2473640845139222,"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."}}