{"id":"W4311974316","doi":"10.3390/jrfm15120592","title":"Stock Market Volatility Response to COVID-19: Evidence from Thailand","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volatility (finance); Economics; Stock market; Recession; Financial economics; Stock (firearms); Coronavirus disease 2019 (COVID-19); Monetary economics; Spillover effect; Volatility swap; Volatility smile; Econometrics; Implied volatility; Macroeconomics; Internal medicine","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":[0.0005118948,0.0001668864,0.0001770376,0.0005341318,0.0002041878,0.0008976315,0.0001983178,0.0003059145,0.001026833],"category_scores_gemma":[0.002562851,0.0001075735,0.0002497549,0.0008358565,0.0003063894,0.000620726,0.000467298,0.0004899757,0.0001609109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002549345,"about_ca_system_score_gemma":0.0003364713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008534476,"about_ca_topic_score_gemma":0.006309854,"domain_scores_codex":[0.9997634,0.00006330106,0.00002451301,0.00003542753,0.00007183075,0.00004147942],"domain_scores_gemma":[0.9978687,0.0005675417,0.001021902,0.00009651697,0.0002850334,0.0001603486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004022526,0.0001351302,0.9733225,0.0001630975,0.0002145769,0.001642282,0.001749497,0.002450487,0.001991947,0.0008969577,0.0008202153,0.01621108],"study_design_scores_gemma":[0.00001754871,0.0002440128,0.9869179,0.00005625218,0.0001037561,0.0007263731,0.00249911,0.005722348,0.001161594,0.0006731613,0.00184715,0.00003080814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971209,0.0004253576,0.0002414735,0.0002065521,0.000006846555,0.000007544021,0.000359351,0.000003895347,0.001627951],"genre_scores_gemma":[0.9990916,0.0003982657,0.00006029347,0.00003321707,0.00001476262,0.000002229949,0.0002408841,0.000001309536,0.0001572926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008534476,"threshold_uncertainty_score":0.01696962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03893226156109447,"score_gpt":0.2709900359352987,"score_spread":0.2320577743742042,"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."}}