{"id":"W2296746376","doi":"","title":"Price Impact of Aggressive Liquidity Provision","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Market liquidity; Market microstructure; Equity (law); Market maker; Order (exchange); Adverse selection; Market impact; Market depth; Information asymmetry; Financial economics; Economics; Population; Business; Monetary economics; Microeconomics; Finance; Stock market; Geography","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":[0.0003220067,0.000148469,0.0001678973,0.0004584755,0.0002105676,0.001148155,0.0002409572,0.000437754,0.002356618],"category_scores_gemma":[0.004867778,0.0001077902,0.0001019364,0.0003433159,0.0002641404,0.0008444444,0.0005787522,0.0006366941,0.0002698689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003008474,"about_ca_system_score_gemma":0.0001309526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005445116,"about_ca_topic_score_gemma":0.000708528,"domain_scores_codex":[0.9997492,0.00004756061,0.00001540411,0.00002897236,0.0001127388,0.00004606564],"domain_scores_gemma":[0.9973483,0.001069086,0.001000496,0.0001315973,0.0002109546,0.0002395304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004761623,0.0007781051,0.6406347,0.0003916283,0.0003356586,0.00585493,0.002330679,0.02059447,0.14125,0.02148524,0.006816104,0.1547668],"study_design_scores_gemma":[0.0000612255,0.0007550834,0.9521425,0.00003381997,0.0001041003,0.001103828,0.00110711,0.02512486,0.009932154,0.006027543,0.003556263,0.00005141922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974799,0.0001465679,0.000357772,0.00009928189,0.00001079107,0.000002907934,0.00004904729,0.0000335568,0.001820236],"genre_scores_gemma":[0.9997546,0.0000244238,0.00004701475,0.00001311688,0.00001533985,5.931789e-7,0.00002593525,0.000002625027,0.0001162719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002356618,"threshold_uncertainty_score":0.007883668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476452569939481,"score_gpt":0.2333009466947603,"score_spread":0.2185364209953655,"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."}}