Forecasting Models Evaluation Using A Slacks-Based Context-Dependent DEA Framework

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Jamal Ouenniche
Bing Xu
Kaoru Tone

Keywords

Forecasting Crude Oil Prices’ Volatility, Performance Evaluation, Orientation-Free DEA

Abstract

Xu and Ouenniche (2012a) proposed an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) based model to address a common methodological issue in the evaluation of competing forecasting models; namely, ranking models based on a single performance measure at a time, which typically leads to conflicting ranks. However, their approach suffers from a number of issues. In this paper, we overcome these issues by proposing a slacks-based context-dependent DEA framework and use it to rank forecasting models of oil prices’ volatility.

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