{"id":"W2992741516","doi":"","title":"QUANTIFYING THE RISK ON BANKSâ RETURNS ARISING FROM FINANCIAL TECHNOLOGY ADOPTION: AN ASYMMETRIC GARCH APPROACH TO VALUE-AT-RISK","year":2019,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Value at risk; Economics; Profitability index; Actuarial science; Financial economics; Risk–return spectrum; Econometrics; Business; Finance; Risk management; Volatility (finance)","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":[0.003704081,0.0005673979,0.0004726857,0.001363037,0.0002500258,0.001917604,0.0006383689,0.001042057,0.001141754],"category_scores_gemma":[0.01282875,0.0002696889,0.0007811446,0.001454942,0.000781011,0.002153295,0.001142558,0.001328065,0.0001704707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183818,"about_ca_system_score_gemma":0.0006039076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003138635,"about_ca_topic_score_gemma":0.001914531,"domain_scores_codex":[0.9984375,0.00058611,0.0001042616,0.0002299402,0.0004304856,0.0002117014],"domain_scores_gemma":[0.991376,0.00513499,0.002224366,0.0006121612,0.0005305564,0.0001219384],"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":[0.0003027183,0.0002009499,0.4532933,0.0002252247,0.0006690425,0.001196636,0.0008331651,0.3536773,0.004802423,0.0844398,0.00146268,0.09889682],"study_design_scores_gemma":[0.00001696181,0.0003736671,0.2058755,0.0001029905,0.0003167119,0.0005563767,0.0006639705,0.7249269,0.004429357,0.06000139,0.002616158,0.0001199843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.92133,0.001172853,0.06999297,0.0007871884,0.00003756004,0.00005298993,0.000332029,0.0001018688,0.006192578],"genre_scores_gemma":[0.9971118,0.0002756576,0.001862967,0.00002247955,0.00001835306,0.000009984318,0.00009282649,0.000005596146,0.0006003571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003704081,"threshold_uncertainty_score":0.0195893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03289740977604685,"score_gpt":0.2492914714004853,"score_spread":0.2163940616244385,"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."}}