@inproceedings{oai:grips.repo.nii.ac.jp:00001408,
 author = {OUENNICHE, Jamal and XU, Bing and TONE, Kaoru},
 month = {Dec},
 note = {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)},
 pages = {71--80},
 publisher = {出版社不明},
 title = {Performance Evaluation of Prediction Models Under Multiple Criteria : An application on crude oil prices volatility forecasting models},
 year = {2015}
}