{"id":"W2600532481","doi":"10.5539/ijsp.v6n3p43","title":"Dependence Modeling in Energy Markets using Sibuya-type Copulas","year":2017,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copula (linguistics); Autoregressive model; Econometrics; Mathematics; Futures contract; Marginal distribution; Joint probability distribution; Tail dependence; Statistics; Economics; Random variable","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":[0.004804086,0.001144363,0.001450873,0.001608734,0.000543623,0.001859873,0.001777342,0.0009632151,0.001847367],"category_scores_gemma":[0.01185987,0.0007390016,0.002161877,0.001457183,0.001152586,0.002479506,0.001490181,0.00178013,0.0003573804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007639203,"about_ca_system_score_gemma":0.0009025671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006852567,"about_ca_topic_score_gemma":0.004166749,"domain_scores_codex":[0.9986157,0.000795537,0.00006656795,0.0002122635,0.0001853013,0.0001245338],"domain_scores_gemma":[0.9957606,0.002893277,0.0006159033,0.000281585,0.0002991465,0.0001494042],"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":[0.00005497432,0.00007367211,0.005229384,0.0000641431,0.0002585526,0.0002280207,0.0001850344,0.811939,0.00108133,0.1652342,0.0009380098,0.01471365],"study_design_scores_gemma":[0.000002828377,0.000007562043,0.0005707072,0.000005042151,0.00001134533,0.00001601291,0.00001214692,0.9821004,0.00008220119,0.01701157,0.0001726578,0.000007479819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08649641,0.0004093098,0.9109321,0.000188993,0.00002739405,0.00003908562,0.0001883462,0.0001643013,0.001554036],"genre_scores_gemma":[0.9192086,0.0007713611,0.07566552,0.00007755895,0.00007278031,0.0001552577,0.0004795676,0.0001803327,0.003388883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006852567,"threshold_uncertainty_score":0.02540678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06292783704527594,"score_gpt":0.287234219986728,"score_spread":0.2243063829414521,"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."}}