{"id":"W2497975354","doi":"10.21314/jcf.2016.310","title":"Numerical solution of the Hamilton–Jacobi–Bellman formulation for continuous-time mean–variance asset allocation under stochastic volatility","year":2016,"lang":"en","type":"article","venue":"The Journal of Computational Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hamilton–Jacobi–Bellman equation; Viscosity solution; Stochastic volatility; Mathematics; Mathematical optimization; Applied mathematics; Partial differential equation; Efficient frontier; Volatility (finance); Portfolio; Bellman equation; Mathematical analysis; Econometrics; Economics; Finance","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":[0.001108118,0.0005822529,0.0007667972,0.0003552,0.0004437829,0.0009889271,0.0008106947,0.001727224,0.00239757],"category_scores_gemma":[0.002492693,0.0003353047,0.0006036895,0.0004835111,0.001145999,0.0008996941,0.001117538,0.001177815,0.0002052158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007778317,"about_ca_system_score_gemma":0.001562191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003667916,"about_ca_topic_score_gemma":0.002481577,"domain_scores_codex":[0.9997548,0.0001044448,0.0000134779,0.00003008388,0.00006777076,0.00002934929],"domain_scores_gemma":[0.999351,0.000404771,0.0000740994,0.0000384934,0.00008561189,0.00004598519],"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":[0.00002132953,0.00001979096,0.0002810531,0.00005467703,0.00001158614,0.00007067963,0.00004778243,0.9262584,0.001358265,0.0659674,0.0004640695,0.005444906],"study_design_scores_gemma":[0.000003951442,0.000004242486,0.00001883264,0.000002921142,0.000001088663,0.00000462799,0.000002734566,0.9965672,0.0001162705,0.003088213,0.0001876675,0.000002142982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02670718,0.0005705733,0.9649597,0.0006651084,0.00009754203,0.00004760024,0.00006232083,0.00007196071,0.006818069],"genre_scores_gemma":[0.6698987,0.0007905391,0.3191009,0.0001936967,0.00008765533,0.0003131155,0.0001452032,0.00008702961,0.009383213],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003667916,"threshold_uncertainty_score":0.008020639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168680055504135,"score_gpt":0.2366306246014543,"score_spread":0.2149438240464129,"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."}}