{"id":"W3024006442","doi":"10.1002/ijfe.2006","title":"A study on volatility spurious almost integration effect: A threshold realized <scp>GARCH</scp> approach","year":2020,"lang":"en","type":"article","venue":"International Journal of Finance & Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spurious relationship; Volatility (finance); Econometrics; Economics; Autoregressive conditional heteroskedasticity; Monte Carlo method; Forward volatility; Stochastic volatility; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001304202,0.0003039988,0.000846915,0.0002965538,0.0001004869,0.0001964154,0.0008942772,0.0001513144,0.00001686713],"category_scores_gemma":[0.001042025,0.0003300828,0.0003687669,0.0001765967,0.00006416046,0.0006170091,0.0001170968,0.0006395372,0.00008700645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000348787,"about_ca_system_score_gemma":0.00009792992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008954184,"about_ca_topic_score_gemma":0.00002517769,"domain_scores_codex":[0.9972587,0.00004668339,0.001710433,0.0005493815,0.0001343652,0.0003003914],"domain_scores_gemma":[0.9976256,0.0002143489,0.001489,0.0003019694,0.0002289932,0.0001400193],"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":[0.002937244,0.004031739,0.6465154,0.00008754674,0.001320853,0.0002522786,0.03090267,0.04892377,0.0001542021,0.2185945,0.007015368,0.03926449],"study_design_scores_gemma":[0.01440894,0.007054273,0.222517,0.0002288868,0.0001027923,0.0001427075,0.00183053,0.6277303,0.001179428,0.0648609,0.05906963,0.0008746437],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759115,0.0004808512,0.01401387,0.0008157887,0.001065859,0.0004417146,0.0001569502,0.0000242944,0.007089186],"genre_scores_gemma":[0.9970468,0.0003735137,0.001152668,0.0005425024,0.0007168788,0.00001972882,0.0000221726,0.00003828816,0.00008750623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5788065,"threshold_uncertainty_score":0.9999151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05603211644359377,"score_gpt":0.2691529275338282,"score_spread":0.2131208110902344,"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."}}