{"id":"W4283371147","doi":"10.3390/jrfm15070279","title":"Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volatility (finance); Autoregressive conditional heteroskedasticity; Economics; Econometrics; Tourism; Conditional variance; Financial economics; Composite index; Index (typography); Computer science","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":[0.001001093,0.0005494229,0.0004568704,0.0005873011,0.0002313674,0.001045677,0.0003842307,0.0005842733,0.0008295576],"category_scores_gemma":[0.003012323,0.0002905941,0.0008661853,0.0005013625,0.0002632599,0.0009503098,0.0005552719,0.0007153193,0.0001148002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004548153,"about_ca_system_score_gemma":0.0004433674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01570036,"about_ca_topic_score_gemma":0.009491741,"domain_scores_codex":[0.9996151,0.00009374897,0.00003686732,0.00008840309,0.00009153337,0.00007438659],"domain_scores_gemma":[0.998765,0.000742254,0.0001992738,0.00008765123,0.0001410356,0.00006468756],"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":[0.0003580961,0.0001277735,0.08974521,0.00006745898,0.0001932668,0.0004139694,0.0001062934,0.8690791,0.003978357,0.001698788,0.0004786348,0.03375315],"study_design_scores_gemma":[0.000003239148,0.00003142167,0.009338833,0.000004129904,0.00002049142,0.00001778797,0.00002317947,0.9894829,0.0007569102,0.0002289059,0.00008289583,0.00000918556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801283,0.000268689,0.01744806,0.0002185213,0.00004863401,0.00001611587,0.0002426407,0.00008279688,0.001546248],"genre_scores_gemma":[0.9984739,0.00009819838,0.001018526,0.000008283682,0.00001344349,0.000003342113,0.0001121215,0.000004151552,0.0002679225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01570036,"threshold_uncertainty_score":0.03121799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508743916898395,"score_gpt":0.1892314222751095,"score_spread":0.1741439831061256,"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."}}