{"id":"W4399616218","doi":"10.54097/x8rztp48","title":"Personal Wealth, Risk Tolerance, and Stock Allocation: A Markov Chain Approach","year":2024,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Asset allocation; Equity (law); Economics; Markov chain; Stock market; Order (exchange); Stock (firearms); Financial economics; Business; Actuarial science; Finance; Portfolio; Computer science","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":[0.0005545699,0.000151626,0.0001789905,0.001595858,0.0002024585,0.0002556363,0.0001999075,0.00009261623,0.000007440676],"category_scores_gemma":[0.0001078288,0.0001299423,0.00001911166,0.003056148,0.0002674144,0.0006618834,0.0001526079,0.0002043688,0.00002669405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000383504,"about_ca_system_score_gemma":0.00002922179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001057105,"about_ca_topic_score_gemma":0.00002560876,"domain_scores_codex":[0.9987706,0.000003014083,0.0001928351,0.0005055732,0.0002154065,0.0003125953],"domain_scores_gemma":[0.9996928,0.00002386262,0.00004464552,0.0001552579,0.00006777677,0.00001564621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001252796,0.00006519318,0.1404725,0.0005381773,0.00001090292,0.00004737731,0.0004991412,0.000622657,0.00278557,0.838927,0.0004601901,0.01555882],"study_design_scores_gemma":[0.000205489,0.00001515028,0.03800691,0.0001627802,0.00002669224,0.00001441606,0.00008917991,0.9109762,0.00009689322,0.001139652,0.04897191,0.0002947708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954264,0.001566782,0.000571507,0.001040476,0.000305671,0.000152333,0.000001484336,0.000334152,0.0006012648],"genre_scores_gemma":[0.997223,0.000200634,0.00216325,0.00003892869,0.0002094087,0.00003082846,0.000002876452,0.00001204605,0.0001190807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9103535,"threshold_uncertainty_score":0.5298895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005475772728333906,"score_gpt":0.2010646556279022,"score_spread":0.1955888828995683,"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."}}