{"id":"W3049611042","doi":"10.3390/jrfm13080181","title":"Comparison of Financial Models for Stock Price Prediction","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive model; Stock price; Econometrics; Geometric Brownian motion; Artificial neural network; Stock (firearms); Computer science; Autoregressive integrated moving average; Time series; Autoregressive–moving-average model; Stochastic process; Economics; Series (stratigraphy); Mathematics; Artificial intelligence; Statistics; Machine learning; Diffusion process; Engineering","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":[0.002226559,0.0006840599,0.0006020258,0.001618498,0.0002555872,0.0007695818,0.0008589075,0.0006588572,0.00113453],"category_scores_gemma":[0.005503266,0.0001902667,0.0006645439,0.001170953,0.0001734856,0.001151847,0.0003868614,0.000489968,0.0002815102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007562073,"about_ca_system_score_gemma":0.0005771217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01178806,"about_ca_topic_score_gemma":0.00741432,"domain_scores_codex":[0.9990976,0.0003352526,0.00006707264,0.0000816508,0.0003757828,0.00004275212],"domain_scores_gemma":[0.9973364,0.00194188,0.0001080636,0.00012452,0.0004532439,0.00003579705],"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":[0.0002933963,0.0001646845,0.008982286,0.0001866054,0.0002932531,0.00007947841,0.00005557379,0.8205462,0.0006609241,0.007209032,0.001464058,0.1600645],"study_design_scores_gemma":[0.00001224604,0.00005053835,0.001993866,0.00001706186,0.00002880369,0.00001622521,0.00001686357,0.9953033,0.0002942639,0.001628411,0.000628229,0.0000102223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5366142,0.0117946,0.4231136,0.002089471,0.0004489503,0.0001404006,0.001147941,0.001704714,0.02294616],"genre_scores_gemma":[0.9461392,0.003753142,0.04715444,0.0000968685,0.0001078819,0.00009202182,0.0007395064,0.00006979585,0.001847224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01178806,"threshold_uncertainty_score":0.02343893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1317524425838538,"score_gpt":0.3864742933923031,"score_spread":0.2547218508084493,"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."}}