{"id":"W3182352630","doi":"10.2139/ssrn.3430276","title":"Behavioral Portfolio Insurance Strategies","year":2019,"lang":"de","type":"article","venue":"SSRN Electronic Journal","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Actuarial science; Portfolio; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005545497,0.0004566246,0.0002239833,0.0003410865,0.0002526647,0.001449554,0.0003918299,0.0008583483,0.01171201],"category_scores_gemma":[0.002656979,0.0001194713,0.0002746431,0.0002739815,0.0004125088,0.000903418,0.0006385752,0.0009486601,0.001440618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004327041,"about_ca_system_score_gemma":0.0004946787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004120203,"about_ca_topic_score_gemma":0.0004765236,"domain_scores_codex":[0.9997568,0.00008427606,0.000009098733,0.00003112617,0.0000712655,0.00004748357],"domain_scores_gemma":[0.9994562,0.0001925022,0.00009168761,0.00006984457,0.00007977681,0.0001098379],"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":[0.0001299318,0.0004840983,0.007156622,0.00007532445,0.00008379298,0.0001503757,0.0002829964,0.01746006,0.008544537,0.8593436,0.005599806,0.1006888],"study_design_scores_gemma":[0.0000807937,0.0005498286,0.0100462,0.00006161896,0.00008663924,0.0003653551,0.0004604642,0.1280838,0.002765107,0.8434163,0.01405569,0.00002812099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4765247,0.0007032963,0.1958645,0.005720662,0.0001828356,0.0001525449,0.0002634651,0.0002484037,0.3203396],"genre_scores_gemma":[0.9577699,0.0003261518,0.006488992,0.000348839,0.00003314971,0.00005880009,0.00006694572,0.00001107441,0.03489628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01171201,"threshold_uncertainty_score":0.03918058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02205760054607721,"score_gpt":0.3264588306550018,"score_spread":0.3044012301089246,"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."}}