{"id":"W1972603500","doi":"10.4018/ijsds.2014040104","title":"Multi-Scaling Analysis of the S&P500 under Different Regimes in Wavelet Domain","year":2014,"lang":"en","type":"article","venue":"International Journal of Strategic Decision Sciences","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Hurst exponent; Series (stratigraphy); Wavelet; Scaling; Statistical physics; Econometrics; Exponent; Rescaled range; Range (aeronautics); Mathematics; Power law; Detrended fluctuation analysis; Time series; Statistics; Computer science; Physics; Artificial intelligence; Materials science; Geology","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":[0.0004046393,0.0001916696,0.0001783934,0.0008904159,0.0001622561,0.0005135782,0.000157919,0.0002827211,0.0005323671],"category_scores_gemma":[0.001934578,0.0000817786,0.0002295875,0.0008596695,0.0003032098,0.0007531669,0.000250967,0.0004247763,0.0001057353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001537345,"about_ca_system_score_gemma":0.0001014025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006944524,"about_ca_topic_score_gemma":0.000420134,"domain_scores_codex":[0.9998536,0.0000220768,0.000008919205,0.00002851702,0.00006238066,0.00002451999],"domain_scores_gemma":[0.9994889,0.0001972254,0.0001258576,0.00004406443,0.0001066209,0.00003729869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009742519,0.0003002211,0.1067752,0.0004825832,0.0003114585,0.003473541,0.001803535,0.1577655,0.2562718,0.07405676,0.004186162,0.3935991],"study_design_scores_gemma":[0.00001019857,0.000153751,0.2093562,0.00003297424,0.00005497014,0.000434003,0.0004540804,0.7628946,0.01330531,0.01071187,0.002543645,0.0000483283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9256693,0.0005359353,0.07064368,0.0002379362,0.00005348745,0.0000149087,0.0001140335,0.00006503604,0.002665713],"genre_scores_gemma":[0.9949691,0.0002307808,0.004345794,0.00001338526,0.00002823135,0.000004743115,0.00006297461,0.000008062141,0.0003369214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008904159,"threshold_uncertainty_score":0.002139986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1357463457463038,"score_gpt":0.3232047901803813,"score_spread":0.1874584444340776,"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."}}