scholarly journals Further Study of the DEA-Based Framework for Performance Evaluation of Competing Crude Oil Prices’ Volatility Forecasting Models

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 827 ◽  
Author(s):  
Zhongbao Zhou ◽  
Qianying Jin ◽  
Jian Peng ◽  
Helu Xiao ◽  
Shijian Wu

The super-efficiency data envelopment analysis model is innovative in evaluating the performance of crude oil prices’ volatility forecasting models. This multidimensional ranking, which takes account of multiple criteria, gives rise to a unified decision as to which model performs best. However, the rankings are unreliable because some efficiency scores are infeasible solutions in nature. What’s more, the desirability of indexes is worth discussing so as to avoid incorrect rankings. Hence, herein we introduce four models, which address the issue of undesirable characteristics of indexes and infeasibility of the super efficiency models. The empirical results reveal that the new rankings are more robust and quite different from the existing results.

2014 ◽  
Vol 30 (5) ◽  
pp. 1477 ◽  
Author(s):  
Jamal Ouenniche ◽  
Bing Xu ◽  
Kaoru Tone

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.


2011 ◽  
Vol 38 (9) ◽  
pp. 10875-10881 ◽  
Author(s):  
S.J. Sadjadi ◽  
H. Omrani ◽  
S. Abdollahzadeh ◽  
M. Alinaghian ◽  
H. Mohammadi

Author(s):  
Nurull Qurraisya Nadiyya Md-Khair ◽  
Ruhaidah Samsudin

Crude oil is considered as a crucial energy source in modern days. Consequently, the fluctuation of crude oil prices can cause a significant impact on economic activities. Researchers have proposed many hybrid forecasting models on top of single forecasting methods which are utilized to predict crude oil prices movement more accurately. Nevertheless, many limitations still existed in hybrid forecasting models and models that can predict crude oil prices as accurate as possible is required. The motivations of this review paper are to identify and assess the mostly used crude oil prices forecasting methods and to analyse their current limitations. 12 studies that used “decomposition-and-ensemble” framework was selected for review. Wavelet transform is identified as the mostly used data decomposition method while some limitations have been recognized. Future researches should include more studies to further elucidate the limitations in existing forecasting method so that subsequent forecasting methods can be improved.


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