{"id":"W2898042373","doi":"10.3390/jrfm11040066","title":"Are There Any Volatility Spill-Over Effects among Cryptocurrencies and Widely Traded Asset Classes?","year":2018,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cryptocurrency; Social connectedness; Volatility (finance); Spillover effect; Index (typography); Asset (computer security); Variance decomposition of forecast errors; Financial market; Stock market; Financial economics; Business; Economics; Monetary economics; Econometrics; Finance; Computer science; Microeconomics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001165813,0.0001895674,0.0005105126,0.0002020405,0.0001931893,0.0001229747,0.0001547684,0.0001058138,0.00006144873],"category_scores_gemma":[0.0002907054,0.0001764859,0.0001199347,0.0001828069,0.0001790327,0.0002640232,0.0001061139,0.0002625542,0.000002956547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005362463,"about_ca_system_score_gemma":0.000009479667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000840018,"about_ca_topic_score_gemma":0.0002046069,"domain_scores_codex":[0.9986733,0.00004407498,0.0006672325,0.0002881302,0.00008156041,0.0002457456],"domain_scores_gemma":[0.9983926,0.00009397419,0.001117674,0.0002046883,0.00006840373,0.0001226794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009207807,0.00006843927,0.9687895,0.0001390434,0.00004256576,0.00002319555,0.0001811137,5.430589e-7,8.487107e-7,0.01171474,0.0007927221,0.01815521],"study_design_scores_gemma":[0.0008078522,0.0001711858,0.9152428,0.00007761682,0.00003863552,0.000002805974,0.00006661742,0.005540213,0.000002167825,0.05751907,0.0203571,0.0001739248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790126,0.002092466,0.01592494,0.00006616303,0.0005828523,0.0002201286,0.0000742159,0.000008393667,0.002018245],"genre_scores_gemma":[0.9969603,0.001943904,0.000690932,0.00008869381,0.000236279,0.000004013147,0.000001090782,0.00001177312,0.00006294446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0535467,"threshold_uncertainty_score":0.7196888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283077235964154,"score_gpt":0.2155577461990815,"score_spread":0.2027269738394399,"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."}}