{"id":"W2107680452","doi":"10.2139/ssrn.2321522","title":"Monthly Beta Forecasting with Low, Medium and High Frequency Stock Returns","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"BETA (programming language); Estimator; Econometrics; Portfolio; Stock (firearms); Economics; Expected return; Statistics; Mathematics; Actuarial science; Finance; Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001376093,0.0004373688,0.0004409603,0.0009326729,0.0001754093,0.0007014521,0.0003471098,0.00071584,0.002026169],"category_scores_gemma":[0.006665149,0.0002286187,0.0004819108,0.0008768143,0.0001252317,0.0008376828,0.0002671968,0.0006419598,0.0004624956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001898435,"about_ca_system_score_gemma":0.0001770457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003038364,"about_ca_topic_score_gemma":0.003097938,"domain_scores_codex":[0.9997355,0.0000923965,0.00001580564,0.00005184194,0.00005827868,0.00004607208],"domain_scores_gemma":[0.9972386,0.001870453,0.0002323018,0.0002232393,0.0002947804,0.0001405978],"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":[0.002400638,0.000561642,0.177986,0.0001368069,0.0003574354,0.0003989003,0.0001867615,0.557488,0.01215694,0.002688177,0.006146032,0.2394928],"study_design_scores_gemma":[0.00001635731,0.00008397177,0.02685825,0.00000573368,0.0000302872,0.00003331589,0.00001359523,0.9707836,0.001379993,0.0006347293,0.0001495047,0.0000107172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805828,0.0002184428,0.01722416,0.0001263266,0.00006046669,0.000006694077,0.0003048838,0.0002133793,0.00126297],"genre_scores_gemma":[0.9958243,0.00007120486,0.003216248,0.000009538715,0.00004389374,0.000003395261,0.0003482535,0.0000165126,0.0004665198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003038364,"threshold_uncertainty_score":0.007277548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01575630514734925,"score_gpt":0.1895104911052784,"score_spread":0.1737541859579292,"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."}}