{"id":"W2526125297","doi":"10.2139/ssrn.2975355","title":"Extracting Latent States from High Frequency Option Prices","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Simon Fraser University; Wilfrid Laurier University","funders":"","keywords":"Econometrics; Economics; Financial economics","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":[0.0009626123,0.0006477673,0.0005921199,0.002153752,0.0003467131,0.001365168,0.0005772309,0.001281985,0.003254992],"category_scores_gemma":[0.005263758,0.0005368725,0.0009515986,0.001484781,0.0003944007,0.001957933,0.0009647401,0.001528783,0.001273736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002753293,"about_ca_system_score_gemma":0.0004022501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001194681,"about_ca_topic_score_gemma":0.001563763,"domain_scores_codex":[0.999621,0.0001181854,0.00002955026,0.00008834673,0.0000835009,0.0000593802],"domain_scores_gemma":[0.9961358,0.002964195,0.0003197636,0.0003133955,0.0001700859,0.00009678901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001569243,0.0009508149,0.04587939,0.0004747797,0.0004936999,0.001902397,0.0007264022,0.2491128,0.05599601,0.0736113,0.005276986,0.5640061],"study_design_scores_gemma":[0.00002433839,0.00005711017,0.008142438,0.00001966657,0.00004566182,0.0001559221,0.00006687389,0.9493483,0.002193318,0.03928908,0.0006326902,0.00002451791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3273583,0.0005094663,0.6678929,0.0003732986,0.00006373721,0.00003806997,0.001113151,0.0009430913,0.001707956],"genre_scores_gemma":[0.9405482,0.0003209386,0.05550258,0.00003140569,0.000104133,0.00003891726,0.001740277,0.00008682005,0.001626798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003254992,"threshold_uncertainty_score":0.01088899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000598329806389,"score_gpt":0.2339603715309173,"score_spread":0.2139543882328534,"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."}}