{"id":"W3125290053","doi":"","title":"Stock Market Efficiency Analysis using Long Spans of Data: A Multifractal Detrended Fluctuation Approach","year":2018,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multifractal system; Detrended fluctuation analysis; Econometrics; Stock (firearms); Stock market; Economics; Efficient-market hypothesis; Term (time); Financial economics; Geography; Mathematics; Fractal; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005030358,0.0004408727,0.001898958,0.003200257,0.0002223094,0.0002579216,0.001822738,0.0004940212,0.001089893],"category_scores_gemma":[0.0005314701,0.0005412048,0.0006138834,0.001430776,0.0004009053,0.0003727123,0.002612032,0.0008996741,0.00001631118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000920167,"about_ca_system_score_gemma":0.0002624885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003345556,"about_ca_topic_score_gemma":0.001982255,"domain_scores_codex":[0.9944302,0.0002134084,0.002241573,0.002091198,0.0001934313,0.0008301169],"domain_scores_gemma":[0.9945745,0.0002984209,0.001460267,0.003281182,0.0002039264,0.0001816712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005762728,0.00255736,0.5187926,0.002291956,0.01486658,0.00003912149,0.003318419,0.3036431,0.00007688425,0.003035866,0.0002732997,0.1505284],"study_design_scores_gemma":[0.0004157795,0.00004864513,0.02688159,0.00005179576,0.0001600535,0.000003383297,0.0003761215,0.969673,0.000007209939,0.000730745,0.001150578,0.0005010419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9080158,0.0009784381,0.008529346,0.00004535401,0.0003939855,0.001140216,0.002383989,0.00003852946,0.07847429],"genre_scores_gemma":[0.9893026,0.001189084,0.007000992,0.000006310955,0.0002716538,0.00005515945,0.0009067853,0.00007133657,0.001196049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6660299,"threshold_uncertainty_score":0.9998233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1101559184833663,"score_gpt":0.3297277808209528,"score_spread":0.2195718623375865,"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."}}