{"id":"W3122800062","doi":"10.2139/ssrn.3192216","title":"Derivatives Trading for Insurers","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Business; High-frequency trading; Pairs trade; Actuarial science; Financial economics; Algorithmic trading; Finance; Economics; Alternative trading system","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":[0.001284359,0.0002494738,0.0003746445,0.000538211,0.0008547218,0.002890619,0.0004602585,0.001644077,0.01327138],"category_scores_gemma":[0.01011192,0.0001757101,0.000419847,0.0003792074,0.0004802592,0.001577136,0.0007194548,0.00110165,0.0007800463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437154,"about_ca_system_score_gemma":0.001286183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006194886,"about_ca_topic_score_gemma":0.006702689,"domain_scores_codex":[0.9994259,0.0001452947,0.00002970762,0.0001016217,0.0001666381,0.0001308964],"domain_scores_gemma":[0.9970232,0.001278052,0.0005693381,0.0003998202,0.0003317308,0.0003979392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00370019,0.001782027,0.2556672,0.0003368134,0.0003914489,0.003545379,0.001681285,0.04140604,0.008430799,0.3541879,0.06583921,0.2630318],"study_design_scores_gemma":[0.0005496572,0.001493984,0.2586904,0.0003740709,0.0007882168,0.003003124,0.002735799,0.3655888,0.009139245,0.2885804,0.06889934,0.0001570806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9273149,0.004385524,0.007380827,0.007669095,0.0001826811,0.00005067966,0.0008561925,0.0002569963,0.05190298],"genre_scores_gemma":[0.9944734,0.0002357682,0.0003679658,0.0000610759,0.00004020545,0.000002619615,0.0001040864,0.000006657232,0.004708222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01327138,"threshold_uncertainty_score":0.04439723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02397112344684517,"score_gpt":0.2412103397976518,"score_spread":0.2172392163508066,"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."}}