{"id":"W2027990387","doi":"10.5539/ijef.v3n1p283","title":"Inter-Bank Call Rate Volatility and the Global Financial Crisis: The Nigerian Case","year":2011,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock market crash; Volatility (finance); Financial crisis; Interbank lending market; Economics; Stock market; Autoregressive conditional heteroskedasticity; Volatility clustering; Crash; Monetary economics; Financial economics; Interest rate; Macroeconomics","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":[0.0006847969,0.0002582446,0.0003442014,0.0008634976,0.0005516254,0.001564719,0.0002149599,0.000824133,0.001020926],"category_scores_gemma":[0.002148318,0.0001966734,0.0002800932,0.00114558,0.000574566,0.001153533,0.0006031391,0.0007684946,0.0001033289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006786156,"about_ca_system_score_gemma":0.0003707375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01658761,"about_ca_topic_score_gemma":0.01712744,"domain_scores_codex":[0.9997923,0.00008176728,0.00001349965,0.00002609352,0.00002970599,0.00005673937],"domain_scores_gemma":[0.9989711,0.0006009262,0.0002488423,0.00004268699,0.00006825174,0.00006822714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000639373,0.000260489,0.894948,0.0001269936,0.000160311,0.01575528,0.002997495,0.03639909,0.0009012418,0.02552873,0.001405922,0.02087716],"study_design_scores_gemma":[0.00009162816,0.0003193321,0.7698424,0.0003022888,0.0002639371,0.007260737,0.01880775,0.1780744,0.001234471,0.01750577,0.006175024,0.0001222432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975362,0.000458909,0.0001746589,0.0002710707,0.000006696472,0.000003179448,0.00004148941,0.000001490527,0.001506269],"genre_scores_gemma":[0.9993507,0.0003879587,0.00005608554,0.00001290389,0.00000539328,0.000001326471,0.00002854139,8.817193e-7,0.0001562939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01658761,"threshold_uncertainty_score":0.03298211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03385194959667287,"score_gpt":0.2299680065823728,"score_spread":0.1961160569856999,"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."}}