{"id":"W2950632727","doi":"10.82308/13883","title":"Modeling commodity prices for valuation and hedging of mining projects subjected to volatile markets","year":2017,"lang":"fr","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Speculation; Valuation (finance); Commodity; Commodity swap; Price discovery; Economics; Business; Financial economics; Commodity market; Stock (firearms); Finance; Commerce; Futures contract; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00167393,0.000891128,0.0008347653,0.000678322,0.0004219139,0.00315418,0.001488682,0.002970181,0.004057873],"category_scores_gemma":[0.00504365,0.0007803519,0.001173071,0.0006888263,0.0009010684,0.002060212,0.001156867,0.001959129,0.0003251508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001303178,"about_ca_system_score_gemma":0.001179113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01111202,"about_ca_topic_score_gemma":0.005237103,"domain_scores_codex":[0.999584,0.0001478325,0.00002626566,0.0000953523,0.00005956192,0.00008700517],"domain_scores_gemma":[0.9983497,0.001161397,0.000216477,0.00005338696,0.0001170117,0.0001021107],"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":[0.00005536841,0.00003943778,0.002367769,0.0000447132,0.00002914809,0.0002075604,0.0000567221,0.9800375,0.0005580871,0.01385554,0.0003859573,0.002362363],"study_design_scores_gemma":[0.000005403396,0.00001262514,0.000378484,0.000005127957,0.000006015107,0.00001743944,0.00002173212,0.9956304,0.00006623774,0.003630201,0.0002202255,0.000006205159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6532688,0.002316426,0.3084811,0.002553732,0.000280155,0.0002484493,0.001503926,0.00029458,0.0310528],"genre_scores_gemma":[0.9819427,0.000522479,0.01116875,0.00006682639,0.00005160281,0.00008899617,0.0002919347,0.00003996209,0.005826784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01111202,"threshold_uncertainty_score":0.02209473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07443753382851052,"score_gpt":0.2637151658726256,"score_spread":0.1892776320441151,"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."}}