{"id":"W1444142499","doi":"10.2139/ssrn.2614828","title":"Equity Investing with Targeted Constant Volatility Exposure","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Volatility (finance); Econometrics; Volatility smile; Economics; Implied volatility; Univariate; Forward volatility; Volatility risk premium; Financial economics; Equity (law); Transaction cost; Volatility swap; Multivariate statistics; Finance; Statistics; Mathematics","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":[0.0008317251,0.0004830968,0.000751572,0.0002991497,0.0002092894,0.001626264,0.0006396924,0.00153888,0.003956713],"category_scores_gemma":[0.004125124,0.0002327955,0.0003366104,0.0002494163,0.0006738629,0.001307663,0.0007708163,0.0006747307,0.0003449232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005328201,"about_ca_system_score_gemma":0.0003834884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001358249,"about_ca_topic_score_gemma":0.001248571,"domain_scores_codex":[0.999686,0.00004590735,0.00001386968,0.00006418565,0.00003855316,0.0001514865],"domain_scores_gemma":[0.9983501,0.0006248959,0.0004839434,0.0001534809,0.0000921864,0.0002953717],"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":[0.0104571,0.004176087,0.1664599,0.0005709703,0.0007254586,0.01386505,0.0008469587,0.3042912,0.06991897,0.2928091,0.01046498,0.1254141],"study_design_scores_gemma":[0.0005931891,0.003744974,0.07470551,0.00004337566,0.0005652212,0.001956014,0.0004956592,0.7570335,0.0169527,0.1414344,0.002373272,0.0001021675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988654,0.00009775793,0.005941361,0.0003144087,0.00002602842,0.00001716817,0.00007381197,0.00006706666,0.004808477],"genre_scores_gemma":[0.9974557,0.00002395144,0.0001910309,0.00001947339,0.000009060433,0.000002123789,0.00001522211,0.000002413141,0.002281144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003956713,"threshold_uncertainty_score":0.01323652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0434012201439794,"score_gpt":0.2341581304677911,"score_spread":0.1907569103238117,"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."}}