{"id":"W3187081192","doi":"10.3390/jrfm14080369","title":"Transfer Entropy Approach for Portfolio Optimization: An Empirical Approach for CESEE Markets","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Portfolio; Portfolio optimization; Post-modern portfolio theory; Rate of return on a portfolio; Econometrics; Stock market; Computer science; Economics; Transfer entropy; Benchmark (surveying); Entropy (arrow of time); Replicating portfolio; Financial economics; Principle of maximum entropy; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002379605,0.0007680126,0.000773323,0.001392966,0.0003938462,0.001415995,0.0009793526,0.001276458,0.003185847],"category_scores_gemma":[0.009286921,0.0002758074,0.0008465548,0.001047535,0.0008716472,0.002337514,0.001293705,0.001552388,0.0002094609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007804244,"about_ca_system_score_gemma":0.0005763977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001294347,"about_ca_topic_score_gemma":0.0007028125,"domain_scores_codex":[0.9994292,0.0003356553,0.0000260069,0.00006439077,0.0001116506,0.0000331664],"domain_scores_gemma":[0.9977211,0.001763368,0.0001575896,0.0001408044,0.000146188,0.00007093398],"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":[0.00004455063,0.0001571004,0.002804531,0.0001129505,0.0001283781,0.0001290776,0.0001112625,0.6648771,0.00138708,0.2940111,0.000770162,0.03546669],"study_design_scores_gemma":[0.000003161455,0.00001636499,0.0003605715,0.000006717495,0.000006165219,0.00001460368,0.000009396768,0.9622329,0.0001596301,0.03677112,0.000413124,0.000006198275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04791988,0.0007857997,0.9442471,0.0004966179,0.00004952983,0.00006917513,0.00006525031,0.00007790374,0.00628867],"genre_scores_gemma":[0.8826942,0.001591659,0.108448,0.0001505159,0.0002638635,0.000275251,0.0002110236,0.00007785633,0.006287537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003185847,"threshold_uncertainty_score":0.01258475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.022666801421002,"score_gpt":0.2349887761002701,"score_spread":0.2123219746792681,"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."}}