{"id":"W3180981544","doi":"10.3390/jrfm14070322","title":"A Neural Network Monte Carlo Approximation for Expected Utility Theory","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stylized fact; Computer science; Portfolio; Mathematical optimization; Monte Carlo method; Artificial neural network; Expected utility hypothesis; Portfolio optimization; Bellman equation; Mathematical economics; Mathematics; Artificial intelligence; Economics","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":[0.001684416,0.0006995781,0.0009918299,0.000826794,0.0004945669,0.001011028,0.001522261,0.001629749,0.003684956],"category_scores_gemma":[0.006748185,0.0005665784,0.0007217495,0.000897003,0.0009918942,0.001472011,0.0009590033,0.001911556,0.0004894538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514912,"about_ca_system_score_gemma":0.001238957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007915743,"about_ca_topic_score_gemma":0.005578002,"domain_scores_codex":[0.999401,0.0002855011,0.00002207068,0.0000818661,0.0001590551,0.0000505617],"domain_scores_gemma":[0.9982486,0.001346964,0.00009000345,0.00007817391,0.0001758101,0.00006056322],"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":[0.00002015472,0.00001968408,0.0002820033,0.00003335369,0.00002399326,0.00003262679,0.0000216093,0.9355471,0.0003584969,0.04928688,0.0005160804,0.0138581],"study_design_scores_gemma":[0.000001631787,0.000002614416,0.00001782417,0.000003508104,0.000001414067,0.000004761127,8.109564e-7,0.9952218,0.00004441866,0.004510821,0.0001885101,0.000001898851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003696252,0.000286986,0.993218,0.0001579924,0.00003743526,0.00002103082,0.00002546793,0.0000780307,0.002478776],"genre_scores_gemma":[0.4737647,0.0007744784,0.51577,0.0002941174,0.0002002941,0.0003703614,0.0001907625,0.0001730413,0.008462297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007915743,"threshold_uncertainty_score":0.01573932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01647651454842002,"score_gpt":0.2117525799767987,"score_spread":0.1952760654283787,"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."}}