{"id":"W3200991750","doi":"10.1109/compsac51774.2021.00260","title":"Novel Data-Driven Resilient Portfolio Risk Measures Using Sign and Volatility Correlations","year":2021,"lang":"en","type":"article","venue":"","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Manitoba","funders":"","keywords":"Kurtosis; Portfolio; Portfolio optimization; Skewness; Econometrics; Rate of return on a portfolio; Expected shortfall; Value at risk; Modern portfolio theory; Post-modern portfolio theory; Sharpe ratio; Computer science; Efficient frontier; Mathematics; Actuarial science; Statistics; Replicating portfolio; Economics; Risk management; Financial 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":[0.003679152,0.001289785,0.001119314,0.00195043,0.0002468537,0.00184131,0.0008555092,0.0007353247,0.0005770207],"category_scores_gemma":[0.01128248,0.0003297177,0.0007060401,0.001606649,0.0005742552,0.002773184,0.001478574,0.001201026,0.0001429088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007214748,"about_ca_system_score_gemma":0.0008191621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004335798,"about_ca_topic_score_gemma":0.0003701145,"domain_scores_codex":[0.9984393,0.000521873,0.0001625937,0.0002180091,0.0005778574,0.00008046313],"domain_scores_gemma":[0.9949284,0.002361208,0.001385307,0.0004553213,0.000688514,0.0001812945],"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":[0.0001565799,0.0001788794,0.008993445,0.0001212445,0.0002340919,0.000157642,0.00005043504,0.813817,0.006951965,0.03227942,0.000969083,0.1360902],"study_design_scores_gemma":[0.000006075206,0.0001041149,0.001110142,0.00001078664,0.00002139399,0.00004979278,0.000006068223,0.9904301,0.00180626,0.006177422,0.0002602802,0.00001771997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0849513,0.0009587244,0.9118151,0.0002025871,0.00005158367,0.00008037152,0.0001111303,0.0003395696,0.001489684],"genre_scores_gemma":[0.8384522,0.0006819815,0.1595801,0.00007983309,0.00007165207,0.0001080525,0.0002927698,0.00004959068,0.0006839084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003679152,"threshold_uncertainty_score":0.01945746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2106914384701972,"score_gpt":0.3907743720300457,"score_spread":0.1800829335598485,"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."}}