{"id":"W2073543145","doi":"10.1080/09603107.2012.727972","title":"Setting the optimal make-whole call premium","year":2012,"lang":"en","type":"article","venue":"Applied Financial Economics","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Rule of thumb; Economics; Ex-ante; Value (mathematics); Risk premium; Investment (military); Call option; Microeconomics; Econometrics; Actuarial science; Financial economics; Computer science","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":[0.002494738,0.0006648024,0.0008589984,0.0005604014,0.0005457753,0.002966481,0.00122523,0.002300616,0.004869099],"category_scores_gemma":[0.01646947,0.0005895554,0.0004860703,0.0002861524,0.0009318845,0.002675578,0.001774323,0.001853722,0.0007255393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052662,"about_ca_system_score_gemma":0.001485549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001236615,"about_ca_topic_score_gemma":0.0012234,"domain_scores_codex":[0.9984988,0.0003724787,0.00005267622,0.0002625936,0.0004675,0.0003458072],"domain_scores_gemma":[0.9959299,0.002468875,0.0004172274,0.0005235042,0.0003140074,0.0003464834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003589102,0.000297088,0.003679607,0.0001116966,0.0000640261,0.000274097,0.0002275812,0.6756523,0.01426934,0.2676382,0.006328349,0.03109881],"study_design_scores_gemma":[0.00007581992,0.0001402024,0.002823269,0.00004661606,0.00004181328,0.0001643553,0.000178655,0.8519958,0.007511045,0.1339416,0.00299805,0.00008277142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5025036,0.0005370167,0.4271752,0.002400846,0.0003055648,0.0001612706,0.0004244301,0.001165822,0.06532624],"genre_scores_gemma":[0.9799943,0.00007426675,0.01726542,0.0001697045,0.00003003987,0.00004170078,0.00004482236,0.00008259463,0.002297221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004869099,"threshold_uncertainty_score":0.01628876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589785064353616,"score_gpt":0.1963374114289245,"score_spread":0.1804395607853884,"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."}}