{"id":"W4295868022","doi":"10.2139/ssrn.4212377","title":"Technical Trading Rules, Loss Avoidance, and the Business Cycle","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Business; Industrial organization","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":[0.001980327,0.0001991763,0.0003727443,0.0005881363,0.0004234124,0.003376863,0.0004262971,0.0007965838,0.003011116],"category_scores_gemma":[0.01405587,0.0001741382,0.0003001396,0.0005870095,0.001502265,0.001905215,0.0006904828,0.0008454573,0.000312418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004955513,"about_ca_system_score_gemma":0.000442708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004275813,"about_ca_topic_score_gemma":0.0004619879,"domain_scores_codex":[0.9995273,0.0001590447,0.00005039905,0.00007340736,0.0001227333,0.00006706976],"domain_scores_gemma":[0.9911966,0.003959158,0.003400968,0.000649438,0.0004145897,0.0003792263],"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":[0.001523205,0.0006213284,0.06967179,0.0002929243,0.0002998637,0.0009805417,0.0005293709,0.1466253,0.007816569,0.6390504,0.004636938,0.1279517],"study_design_scores_gemma":[0.0001071516,0.0002871565,0.03919742,0.00006624615,0.00009070989,0.0005330651,0.0002521676,0.07105959,0.001321147,0.8828758,0.00415487,0.0000547257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9158179,0.00265607,0.03277064,0.001431976,0.00008433199,0.00002698473,0.0001295041,0.000104368,0.04697835],"genre_scores_gemma":[0.9974063,0.000353934,0.0006989273,0.00004014913,0.0000257188,0.000002914629,0.00002487599,0.000009584403,0.001437636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003376863,"threshold_uncertainty_score":0.01047313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830133720328193,"score_gpt":0.1989845897552588,"score_spread":0.1806832525519769,"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."}}