{"id":"W4353000572","doi":"10.54691/bcpbm.v35i.3302","title":"Stock price prediction based on SVM, LSTM, ARIMA","year":2022,"lang":"en","type":"article","venue":"BCP Business & Management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Autoregressive integrated moving average; Econometrics; Computer science; Stock (firearms); Stock market prediction; Stock market; Stock price; Financial economics; Equity (law); Economics; Artificial intelligence; Machine learning; Time series; Series (stratigraphy); Engineering","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":[0.0005810872,0.00044826,0.0005805998,0.000739033,0.0002333843,0.0006702901,0.0004762507,0.0004049228,0.001169337],"category_scores_gemma":[0.001354358,0.0001546396,0.0003966977,0.0008290779,0.0001370447,0.0008424047,0.0002711138,0.0007091032,0.0004020321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003046923,"about_ca_system_score_gemma":0.0004416666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007235411,"about_ca_topic_score_gemma":0.00572831,"domain_scores_codex":[0.9998268,0.00002713427,0.00001686043,0.00005273135,0.00004846544,0.00002794628],"domain_scores_gemma":[0.9996485,0.0001793181,0.00004137096,0.00001986915,0.0000917965,0.00001925497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002958461,0.000240154,0.01011106,0.0001803229,0.0001702116,0.0001155201,0.00008190958,0.212974,0.01003174,0.003121199,0.003955299,0.7587228],"study_design_scores_gemma":[0.000003388336,0.00003712761,0.001519305,0.0000063958,0.00001607921,0.00002160061,0.000009344715,0.9962225,0.0008323563,0.001023859,0.0003015578,0.000006451283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3497815,0.008915984,0.6269351,0.001238215,0.0005608028,0.00008389141,0.0007202076,0.003050913,0.008713446],"genre_scores_gemma":[0.9423833,0.001677892,0.05170374,0.0001207538,0.0001936354,0.00003612208,0.0003602903,0.00002828597,0.003495903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007235411,"threshold_uncertainty_score":0.01438659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09974785452163878,"score_gpt":0.3629668361643734,"score_spread":0.2632189816427346,"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."}}