{"id":"W1634749637","doi":"10.1007/s11579-008-0012-8","title":"Risk minimization and optimal derivative design in a principal agent game","year":2008,"lang":"en","type":"article","venue":"Mathematics and Financial Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Principal (computer security); Mathematical finance; Risk aversion (psychology); Derivative (finance); Adverse selection; Econometrics; Mathematical economics; Economics; Private information retrieval; Principal–agent problem; Variance (accounting); Spectral risk measure; Mathematics; Actuarial science; Expected utility hypothesis; Computer science; Risk management; Statistics; Financial economics; Expected shortfall; Finance; Accounting","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":[0.0004872213,0.0002003489,0.0005296661,0.0001624749,0.0001320535,0.00005302424,0.0001079241,0.0001369285,0.00003481319],"category_scores_gemma":[0.0001714341,0.0002438794,0.00005316393,0.00006821523,0.0001445098,0.0002225361,0.0001015714,0.0001358992,0.00003008696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008782114,"about_ca_system_score_gemma":0.00003926638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007473546,"about_ca_topic_score_gemma":0.00003295855,"domain_scores_codex":[0.9985487,0.00001123489,0.000754155,0.0003988009,0.00001135274,0.000275683],"domain_scores_gemma":[0.9991633,0.0001091816,0.0004220608,0.0001999978,0.00001357764,0.00009183689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005118033,0.0001457757,0.01211684,0.00004874331,0.00002802564,0.000007518279,0.0142452,0.009182299,0.000002307911,0.9626392,0.00006321516,0.001469765],"study_design_scores_gemma":[0.002628007,0.0002744406,0.03295168,0.00004248296,0.00001701391,0.00007546601,0.0005804242,0.4712368,0.00008669805,0.4777684,0.01336718,0.0009714087],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9051718,0.000476586,0.0919653,0.00006842976,0.0001160195,0.0003087352,0.00009416623,0.00001576699,0.001783163],"genre_scores_gemma":[0.9508333,0.004748745,0.04397644,0.0001017539,0.00006832906,0.00004333321,0.000006582186,0.00003183365,0.0001897477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4848707,"threshold_uncertainty_score":0.9945114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0385290781013499,"score_gpt":0.1997500001092976,"score_spread":0.1612209220079477,"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."}}