{"id":"W2240565397","doi":"10.35536/lje.2013.v18.i1.a1","title":"One-Step-Ahead Forecastability of GARCH (1,1):A Comparative Analysis of USD- and PKR-Based ExchangeRate Volatilities","year":2013,"lang":"en","type":"article","venue":"The Lahore journal of economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rupee; Liberian dollar; Autoregressive conditional heteroskedasticity; Currency; Economics; Volatility (finance); Exchange rate; Us dollar; Context (archaeology); Robustness (evolution); Econometrics; U.S. Dollar Index; International economics; Monetary economics; Finance; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00600809,0.0005566265,0.0005931394,0.001647127,0.0002516557,0.001295201,0.0005448564,0.00062564,0.0007134155],"category_scores_gemma":[0.01693583,0.0002398185,0.0007835836,0.0009612724,0.0002886202,0.002181622,0.0004882332,0.0007489235,0.0001919526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003585633,"about_ca_system_score_gemma":0.0004483216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006101089,"about_ca_topic_score_gemma":0.003768264,"domain_scores_codex":[0.9991022,0.0003574143,0.0000594183,0.0001485368,0.0002520527,0.0000803764],"domain_scores_gemma":[0.9898248,0.007879876,0.000731328,0.0008463824,0.0005589369,0.0001586176],"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":[0.001154127,0.000164197,0.1329855,0.0002028193,0.0006805771,0.0004641172,0.0005211427,0.7319337,0.004659509,0.01034785,0.001072679,0.1158138],"study_design_scores_gemma":[0.0000170587,0.0002383323,0.05902728,0.00002348026,0.00009116485,0.0001451287,0.0001046316,0.9355821,0.001387668,0.002952336,0.0003742499,0.00005658994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9531105,0.0008595468,0.04233136,0.0002230132,0.00003810073,0.00002599047,0.0004751366,0.0003235453,0.002612789],"genre_scores_gemma":[0.996173,0.0001839417,0.003007939,0.00001171206,0.00001640443,0.000004224121,0.0003840603,0.00002288736,0.0001958964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006101089,"threshold_uncertainty_score":0.03177416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07533280719109103,"score_gpt":0.2517586558472207,"score_spread":0.1764258486561296,"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."}}