{"id":"W4309044538","doi":"10.37256/aie.3220221722","title":"Multi-Timeframe Algorithmic Trading Bots Using Thick Data Heuristics with Deep Reinforcement Learning","year":2022,"lang":"en","type":"article","venue":"Artificial Intelligence Evolution","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Heuristics; Computer science; Reinforcement learning; Algorithmic trading; Trading strategy; Benchmark (surveying); Artificial intelligence; Heuristic; Order (exchange); Intuition; Machine learning; High-frequency trading; Econometrics; Economics; Financial economics; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009027242,0.0001962724,0.0002776393,0.0002166164,0.0009448174,0.0001312305,0.0004770022,0.0000631019,0.0005869308],"category_scores_gemma":[0.0001711894,0.0002293268,0.0000506822,0.0004408199,0.0001277188,0.000561057,0.0002748597,0.0004376456,0.0001008529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004537968,"about_ca_system_score_gemma":0.00007576608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001503249,"about_ca_topic_score_gemma":0.00006597038,"domain_scores_codex":[0.9980891,0.00005347061,0.0007170677,0.0005911008,0.000125559,0.0004237144],"domain_scores_gemma":[0.9989517,0.00005030758,0.0004220888,0.0004685002,0.00003876335,0.0000686786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001061384,0.0002083977,0.003726224,0.00002849014,0.00005805995,0.0000149429,0.001028352,0.485751,0.0002593094,0.5050367,0.000125509,0.003656886],"study_design_scores_gemma":[0.00006061051,0.0002621857,0.000688686,0.00001459862,0.00001378552,0.00000989466,0.0014234,0.962599,0.00008295849,0.03093508,0.003600249,0.0003095009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0439738,0.0009346246,0.9519757,0.0001551844,0.0007360415,0.0003801349,0.00004689367,0.00008507794,0.001712545],"genre_scores_gemma":[0.9895645,0.00004447006,0.009801351,0.0001171966,0.0001609803,0.00002949363,0.0001002782,0.00003061471,0.0001511149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9455907,"threshold_uncertainty_score":0.9351677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1352135594923659,"score_gpt":0.2804784550600712,"score_spread":0.1452648955677053,"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."}}