{"id":"W2076237346","doi":"10.1155/2010/537571","title":"Modeling and Pricing of Variance and Volatility Swaps for Local Semi‐Markov Volatilities in Financial Engineering","year":2010,"lang":"en","type":"article","venue":"Mathematical Problems in Engineering","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov chain; Econometrics; Martingale (probability theory); Volatility (finance); Stochastic volatility; Markov process; Variance swap; Mathematics; Economics; Financial economics; Forward volatility; Applied mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001185177,0.0005508759,0.0007981927,0.0005127317,0.0003463116,0.001393441,0.0008933154,0.001335535,0.001288171],"category_scores_gemma":[0.003067903,0.0004405176,0.0008691541,0.0003557088,0.001452229,0.001748004,0.0007388471,0.0009136599,0.0001330329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001074112,"about_ca_system_score_gemma":0.0008624372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002530014,"about_ca_topic_score_gemma":0.00208276,"domain_scores_codex":[0.9996634,0.0001244204,0.00001528417,0.00006073188,0.00007641743,0.00005981987],"domain_scores_gemma":[0.9989519,0.0006281019,0.0002247646,0.0000424716,0.00007897025,0.00007380729],"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":[0.00005167647,0.00005989964,0.00171005,0.00004939673,0.00005176664,0.0002125959,0.0001029251,0.6759594,0.003895841,0.313338,0.0002684329,0.00429995],"study_design_scores_gemma":[0.000006328833,0.00001680564,0.0002652909,0.000003964012,0.000007051979,0.00002090341,0.00001182605,0.9481756,0.0002558111,0.05110735,0.0001203701,0.000008661204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3554032,0.0007063973,0.6387538,0.0008286351,0.00004087419,0.00002673306,0.00006041055,0.0000633622,0.0041167],"genre_scores_gemma":[0.9863165,0.0003220554,0.01016037,0.00003147049,0.00003534053,0.00003885339,0.00002912722,0.00001197783,0.00305419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002530014,"threshold_uncertainty_score":0.007793188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185031984503833,"score_gpt":0.1934389070333124,"score_spread":0.1815885871882741,"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."}}