{"id":"W3123342669","doi":"10.1016/j.ejor.2006.09.002","title":"Calculating risk neutral probabilities and optimal portfolio policies in a dynamic investment model with downside risk control","year":2006,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Nanyang Technological University","keywords":"Downside risk; Portfolio; Economics; Investment (military); Control (management); Portfolio optimization; Econometrics; Computer science; Financial economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002515613,0.00009951775,0.0002253124,0.0003349203,0.000245627,0.0001445405,0.0001514851,0.00002064692,0.000009525513],"category_scores_gemma":[0.0003299453,0.00008675155,0.00004009546,0.0002491187,0.0001821273,0.0002284106,0.00004173861,0.0004223889,0.00000953905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110326,"about_ca_system_score_gemma":0.0001483364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005653717,"about_ca_topic_score_gemma":0.0001255512,"domain_scores_codex":[0.9986737,0.00006923998,0.0006794587,0.0001971267,0.0001251345,0.0002553664],"domain_scores_gemma":[0.999118,0.0001372381,0.0003075845,0.0001067768,0.0002520639,0.00007836879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001030512,0.0001127223,0.02777411,0.00001166518,0.00002268128,0.00001962019,0.0005058982,0.338054,0.00004276517,0.633026,0.00007547707,0.0002519885],"study_design_scores_gemma":[0.002126045,0.0005126926,0.4458615,0.00005626734,0.000009827191,0.00007592441,0.0002469807,0.3854643,0.00001182954,0.1650444,0.0003794306,0.0002107753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7755439,0.0008536406,0.2183288,0.0005735248,0.00001193179,0.0002059263,0.0001125471,0.000003772162,0.004365965],"genre_scores_gemma":[0.9870244,0.00009459024,0.01253962,0.00006155993,0.0001020616,0.00001452396,0.000004471049,0.00001750819,0.0001412375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4679816,"threshold_uncertainty_score":0.3537625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03392933721540386,"score_gpt":0.2730314284169379,"score_spread":0.2391020912015341,"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."}}