{"id":"W1995905272","doi":"10.1007/s10690-011-9142-8","title":"The Minimal Entropy Martingale Measure (MEMM) for a Markov-Modulated Exponential Lévy Model","year":2011,"lang":"en","type":"article","venue":"Asia-Pacific Financial Markets","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Exponential function; Martingale (probability theory); Mathematics; Applied mathematics; Markov process; Entropy (arrow of time); Local martingale; Martingale pricing; Measure (data warehouse); Markov chain; Econometrics; Mathematical economics; Statistical physics; Computer science; Statistics; Mathematical analysis; 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":[0.001646792,0.000590173,0.001022378,0.001124276,0.0007796628,0.001890013,0.001197841,0.001423354,0.002870532],"category_scores_gemma":[0.005413422,0.0003502577,0.0009692767,0.0004342824,0.00214786,0.00251437,0.001482713,0.001263754,0.0002233201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221487,"about_ca_system_score_gemma":0.001325518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000900409,"about_ca_topic_score_gemma":0.0006662796,"domain_scores_codex":[0.9995229,0.0001706096,0.00002703192,0.00009909256,0.00009120046,0.00008919985],"domain_scores_gemma":[0.997665,0.001232729,0.0003356273,0.0001243992,0.000250967,0.000391274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005978691,0.00003458232,0.0009223676,0.00006136094,0.00003390063,0.0001116469,0.00008219777,0.01614138,0.002331952,0.9768399,0.0005092814,0.002871637],"study_design_scores_gemma":[0.00002011651,0.00005459293,0.0009198967,0.00002269212,0.00001841205,0.0001240007,0.00003674831,0.2340954,0.0005836016,0.7635145,0.0005729718,0.00003700059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4440615,0.001141279,0.5370811,0.002034774,0.0002082025,0.00007084825,0.0003508953,0.0001480105,0.01490341],"genre_scores_gemma":[0.9760236,0.0003519736,0.01829312,0.0001768505,0.0001751689,0.00007804322,0.0001562897,0.00003917925,0.004705698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002870532,"threshold_uncertainty_score":0.009602904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03125348555926807,"score_gpt":0.2068795337764702,"score_spread":0.1756260482172022,"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."}}