{"id":"W2273727572","doi":"10.5539/ijef.v8n2p179","title":"Co-Movement in Stock Markets Based on Directed Complex Network","year":2016,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Degree distribution; Stock (firearms); Clustering coefficient; Stock exchange; Stock market; Average path length; Cluster analysis; Complex network; Econometrics; Computer science; Economics; Mathematics; Statistics; Combinatorics; Graph; Geography; Shortest path problem; Finance","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":[0.0006232499,0.0002934531,0.000389069,0.002465405,0.0006177874,0.001370074,0.0005976124,0.0006354226,0.002059899],"category_scores_gemma":[0.004807875,0.0002620104,0.0004994465,0.001581442,0.0007628295,0.002267884,0.0007709817,0.0004928114,0.0001722779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021399,"about_ca_system_score_gemma":0.0003254029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005903576,"about_ca_topic_score_gemma":0.004700168,"domain_scores_codex":[0.9995463,0.0001698788,0.00001929963,0.0001430356,0.00007679678,0.00004454391],"domain_scores_gemma":[0.9978794,0.001144049,0.000468501,0.000101263,0.0002470081,0.0001599011],"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":[0.0002110567,0.0001144239,0.06252372,0.0002774355,0.0003540497,0.001216555,0.001174046,0.5970175,0.005880251,0.2811731,0.005686996,0.0443709],"study_design_scores_gemma":[0.00001459672,0.00002861769,0.01019791,0.000019833,0.00004301149,0.0001781878,0.0001950254,0.9284152,0.0003508602,0.05859802,0.001931856,0.00002698836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6661022,0.001408044,0.3201207,0.001558121,0.00008111669,0.00009083642,0.0008819193,0.0002212053,0.009535913],"genre_scores_gemma":[0.9867547,0.0004586389,0.01045425,0.00007245391,0.00003294627,0.00005918401,0.000269371,0.00001884123,0.001879648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005903576,"threshold_uncertainty_score":0.01173842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347107511342247,"score_gpt":0.2558183218204301,"score_spread":0.2423472467070076,"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."}}