{"id":"W4238913342","doi":"10.32920/ryerson.14653152","title":"Pricing spread options under Levy jump-diffusion models","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Stochastic volatility; Jump diffusion; Jump; Valuation of options; Lévy process; Monte Carlo method; Exotic option; Volatility (finance); Econometrics; Poisson distribution; Jump process; Computer science; Economics; Mathematics; Applied mathematics; Statistics; Physics","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":[0.002446725,0.0007535891,0.001342364,0.000942638,0.0004889894,0.002296551,0.0009171601,0.002585685,0.001683254],"category_scores_gemma":[0.01054672,0.0005977483,0.0009195677,0.00080913,0.001299104,0.004000128,0.001398448,0.001650572,0.0001845368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008345136,"about_ca_system_score_gemma":0.0008682399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002725209,"about_ca_topic_score_gemma":0.001045326,"domain_scores_codex":[0.9993094,0.000345574,0.00002917551,0.00007448606,0.0001716127,0.00006967247],"domain_scores_gemma":[0.9966577,0.002676559,0.0002663259,0.00008773916,0.0001566133,0.0001549915],"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":[0.0000902365,0.00005286796,0.00144397,0.00005455002,0.00004852964,0.0003630612,0.00009545164,0.804397,0.003182084,0.1851875,0.0003205232,0.00476421],"study_design_scores_gemma":[0.0000138816,0.00001241083,0.0001034398,0.000003728364,0.000004572267,0.00002839626,0.000007866593,0.9646119,0.0001874232,0.03495887,0.00006020961,0.000007198113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4510578,0.001227961,0.5414863,0.001131774,0.00008498626,0.00004653701,0.00007098111,0.0001934087,0.004700095],"genre_scores_gemma":[0.9756582,0.0007358318,0.02006193,0.0000778895,0.00009548473,0.00003823597,0.00007613775,0.00004134988,0.003214862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002725209,"threshold_uncertainty_score":0.01293969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06889396788401494,"score_gpt":0.2489872676109988,"score_spread":0.1800932997269839,"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."}}