{"id":"W2811388006","doi":"10.5539/ijef.v10n8p36","title":"Multi Factor Stock Selection Model Based on LSTM","year":2018,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profitability index; Stock (firearms); Computer science; Portfolio; Profit (economics); Artificial intelligence; Model selection; Selection (genetic algorithm); Factor analysis; Econometrics; Machine learning; Economics; Financial economics; Finance; Engineering; Microeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005173386,0.0006981153,0.0006478374,0.000602894,0.0003109598,0.0007085959,0.0008120156,0.0005933914,0.002056206],"category_scores_gemma":[0.001032603,0.000267193,0.0006384754,0.0008352984,0.0002067981,0.001112823,0.0003625871,0.000746094,0.0004376812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006027665,"about_ca_system_score_gemma":0.0006677827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052646,"about_ca_topic_score_gemma":0.008036776,"domain_scores_codex":[0.9997349,0.00003966561,0.00002239161,0.0000894633,0.00006807567,0.00004548886],"domain_scores_gemma":[0.9997349,0.0001027907,0.00003500271,0.00001297283,0.00009837614,0.00001587554],"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":[0.0003075933,0.0001474899,0.007101277,0.0001072476,0.0002268591,0.0002999021,0.0001152149,0.6880924,0.008619987,0.005949297,0.003294734,0.285738],"study_design_scores_gemma":[0.000004907804,0.00002041279,0.000398429,0.000002813556,0.00001328038,0.0000189804,0.000003072579,0.9979022,0.0005280523,0.0009275068,0.0001756553,0.000004650943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1662593,0.001418228,0.822933,0.0008122435,0.0002859377,0.0000921163,0.00051603,0.002128143,0.005555019],"genre_scores_gemma":[0.9555089,0.0004897774,0.03852624,0.0001569705,0.00009757641,0.00009407972,0.0004053294,0.00004032519,0.004680683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01052646,"threshold_uncertainty_score":0.02093041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1441558598242856,"score_gpt":0.3957467843747123,"score_spread":0.2515909245504268,"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."}}