{"id":"W2950831182","doi":"10.2139/ssrn.3075819","title":"Time-Consistent Mean-Variance Portfolio Optimization: A Numerical 2 Impulse Control Approach","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Portfolio optimization; Impulse control; Portfolio; Variance (accounting); Impulse (physics); Mathematics; Econometrics; Computer science; Economics; Financial economics; Physics; Medicine","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":[0.003088155,0.00117623,0.002268356,0.001146779,0.0007210459,0.00236848,0.001826277,0.004694548,0.005436876],"category_scores_gemma":[0.01315289,0.001321552,0.001377691,0.001086286,0.002060889,0.001937808,0.002136036,0.002631973,0.0004791538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120367,"about_ca_system_score_gemma":0.001971556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008432994,"about_ca_topic_score_gemma":0.004860793,"domain_scores_codex":[0.9991774,0.0004981413,0.00002941279,0.00009567042,0.0001208235,0.00007855446],"domain_scores_gemma":[0.9941769,0.004703355,0.0003372584,0.0001938238,0.0004225607,0.0001661391],"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":[0.00003692244,0.00002988628,0.000179026,0.00002919185,0.00003685975,0.00004077512,0.00001920593,0.9769001,0.0001547976,0.01952498,0.0003534394,0.002694825],"study_design_scores_gemma":[0.000006367878,0.000003545458,0.00001492664,0.000002504949,0.000003122372,0.000002544283,0.000001670232,0.9973149,0.00002154932,0.002570272,0.00005587891,0.000002721471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01881315,0.0004800251,0.9696347,0.0009010507,0.0001677818,0.00005127784,0.00008682551,0.0002163734,0.009648844],"genre_scores_gemma":[0.7824928,0.0005693306,0.1975283,0.0006116583,0.0004040906,0.0003934847,0.0002684942,0.0002770498,0.01745475],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008432994,"threshold_uncertainty_score":0.01818812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382436360335744,"score_gpt":0.2065625316690816,"score_spread":0.1927381680657241,"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."}}