{"id":"W4389194366","doi":"10.1142/s0218348x24500026","title":"STATISTICAL ANALYSIS BY WAVELET LEADERS REVEALS DIFFERENCES IN MULTI-FRACTAL CHARACTERISTICS OF STOCK PRICE AND RETURN SERIES IN TURKISH HIGH FREQUENCY DATA","year":2023,"lang":"en","type":"article","venue":"Fractals","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fractal; Econometrics; Wavelet; Series (stratigraphy); Time series; Turkish; Computer science; Stock (firearms); Economics; Mathematics; Statistics; Artificial intelligence; Geography","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":[0.0005855927,0.0002177141,0.0002557264,0.001704837,0.0001741723,0.0005219292,0.0001762732,0.0002183476,0.0008749035],"category_scores_gemma":[0.002965966,0.00008639727,0.0004087852,0.0009636534,0.0003148273,0.0005876723,0.0002821543,0.000363133,0.0001816923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002086576,"about_ca_system_score_gemma":0.0001955257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002177852,"about_ca_topic_score_gemma":0.001253422,"domain_scores_codex":[0.9998015,0.00003060513,0.00002038364,0.0000474942,0.00006510448,0.00003498544],"domain_scores_gemma":[0.9989079,0.0003787776,0.0002732038,0.0001234885,0.0002545959,0.00006202808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001088857,0.0002992868,0.4675039,0.0004353065,0.0003805195,0.002664542,0.002604382,0.07922778,0.1316129,0.01411309,0.005613996,0.2944555],"study_design_scores_gemma":[0.00001886503,0.0002152586,0.6495505,0.00002873854,0.0000957868,0.0006335588,0.0007249984,0.3321694,0.01067944,0.004039141,0.001764876,0.00007952949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870143,0.0001113621,0.01182363,0.00006460975,0.00001566019,0.000008091327,0.0002188496,0.00006010174,0.0006833392],"genre_scores_gemma":[0.9968956,0.00005645942,0.002560889,0.000006752781,0.000008817186,0.000006636085,0.0002669149,0.000008732758,0.0001893204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002177852,"threshold_uncertainty_score":0.004330337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07821573458404146,"score_gpt":0.267402844048254,"score_spread":0.1891871094642125,"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."}}