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Performance Evaluation of Prediction Models Under Multiple Criteria : An application on crude oil prices volatility forecasting models OUENNICHE, Jamal XU, Bing TONE, Kaoru Forecasting crude oil prices’ volatility performance evaluation data envelopment analysis (DEA) commodity and energy markets The workshop is supported by JSPS (Japan Society for the Promotion of Science), Grant-in-Aid for Scientific Research (B), #25282090, titled “Studies in Theory and Applications of DEA for Forecasting Purpose. 本研究はJSPS科研費 基盤研究(B) 25282090の助成を受けたものです。 With the increasing number of quantitative models available to forecast the crude oil prices and its volatility, the assessment of the relative performance of competing models becomes a critical task. So far, competing forecasting models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria – a situation where one cannot make an informed decision as to which model performs best when taking all criteria into account. In order to overcome this methodological problem, we proposed a multidimensional framework based on Data Envelopment Analysis models to rank order competing forecasting models. Workshop 2015 -Advances in DEA Theory and Applications (December 1-2, 2015) conference paper 出版社不明 2015-12-02 AM application/pdf 71 80 https://grips.repo.nii.ac.jp/record/1408/files/71-80_Quenniche,Xu,Tone.pdf https://doi.org/10.24545/00001405 https://grips.repo.nii.ac.jp/records/1408 eng http://www.grips.ac.jp/jp/oldseminars/20151105-3601/ http://www.grips.ac.jp/jp/oldseminars/20151105-3601/