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.
|Journal||Journal of Applied Business Research|
|Publication status||Published - Oct 2014|
- Forecasting crude oil prices' volaitlity
- performance evaluation
- orientation-free DEA
Ouenniche, J., Xu, B., & Tone, K. (2014). Forecasting models evaluation using a slacks-based context-dependent DEA framework. Journal of Applied Business Research, 30(5), 1477-1484. http://cluteinstitute.com/ojs/index.php/JABR/article/view/8800/8772