{"id":"W3123509965","doi":"10.1016/j.ijforecast.2014.01.001","title":"Correlation Dynamics and International Diversification Benefits","year":2014,"lang":"en","type":"article","venue":"Open Repository and Bibliography (University of Luxembourg)","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":211,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Toronto","funders":"HEC Montréal; McGill University","keywords":"Diversification (marketing strategy); Portfolio; Economics; Econometrics; Asset allocation; Capital asset pricing model; Financial economics; Portfolio allocation; Asset (computer security); Emerging markets; Business; Finance; Computer science","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":[0.0003164679,0.00006576165,0.0001618078,0.001766782,0.0002823695,0.00009245028,0.0002115184,0.00007552899,0.00001898012],"category_scores_gemma":[0.000002513153,0.00009094619,0.00005300217,0.001036948,0.00009042185,0.0006341062,0.0001554069,0.0000654445,0.000003028154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009276774,"about_ca_system_score_gemma":0.000003837758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001184432,"about_ca_topic_score_gemma":0.00004068435,"domain_scores_codex":[0.9994851,0.00001519187,0.0001471628,0.0002449141,0.00003031012,0.00007731253],"domain_scores_gemma":[0.9995251,0.00003057096,0.0002194454,0.0001193693,0.0000545968,0.00005096533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003967811,0.00002989344,0.8792451,0.00001331576,0.00002586919,3.980814e-7,0.0001635242,0.00005209331,0.000006363931,0.1161181,0.0001347562,0.004170914],"study_design_scores_gemma":[0.0005213612,0.00006228532,0.8938442,0.0000249637,0.00001530873,0.000003400845,0.0003471883,0.09297368,0.000005697261,0.009320659,0.002740188,0.0001410989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8985481,0.0007058946,0.06239263,0.000255144,0.0002459186,0.0001835242,0.00006191144,0.00001639255,0.03759053],"genre_scores_gemma":[0.9968176,0.001311317,0.001430996,0.00001451804,0.00002321574,3.284761e-7,0.00002140241,0.000003712299,0.0003769466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1067974,"threshold_uncertainty_score":0.3708678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02491735277724628,"score_gpt":0.2004099705380108,"score_spread":0.1754926177607645,"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."}}