{"id":"W4366307218","doi":"10.2139/ssrn.4410089","title":"Optimal Trading in Automatic Market Makers with Deep Learning","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Algorithmic trading; Pairs trade; Deep learning; High-frequency trading; Artificial intelligence; Computer science; Business; Financial economics; Industrial organization; Economics; Data science; Alternative trading system","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":[0.002112158,0.0005806191,0.001465806,0.0007041462,0.0005336885,0.002007421,0.001306225,0.001876936,0.004053322],"category_scores_gemma":[0.01208455,0.001094734,0.0004785624,0.0004836454,0.001320535,0.003392097,0.001777467,0.001817539,0.0003458965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009057507,"about_ca_system_score_gemma":0.001439701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00357038,"about_ca_topic_score_gemma":0.004666469,"domain_scores_codex":[0.9994279,0.0001927544,0.0000353859,0.0001451119,0.00007006241,0.0001287674],"domain_scores_gemma":[0.9932529,0.005298581,0.0004736366,0.000280386,0.0003246034,0.0003699194],"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":[0.0007402259,0.0003476052,0.004664952,0.0001155717,0.0001064621,0.0002039677,0.0001356174,0.8773254,0.002069221,0.04665082,0.002711655,0.06492858],"study_design_scores_gemma":[0.00001154921,0.000009290766,0.00009051806,0.000002294992,0.000002892729,0.000004925929,0.000005029958,0.9893014,0.0001140339,0.01042006,0.00003498813,0.000003000041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4147907,0.0006795386,0.5756524,0.001846475,0.0001957702,0.00005367241,0.0001849359,0.0008367261,0.00575984],"genre_scores_gemma":[0.982582,0.00005527586,0.01456042,0.00008505029,0.00004433707,0.00001829012,0.00007430602,0.00004241132,0.002537915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004053322,"threshold_uncertainty_score":0.0135597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066384445725249,"score_gpt":0.2019101896004336,"score_spread":0.1912463451431811,"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."}}