Performance Evaluation of Prediction Models Under Multiple Criteria : An application on crude oil prices volatility forecasting models

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.