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

Zhongbao Zhou, Qianying Jin, Jian Peng, Helu Xiao and Shijian Wu
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Zhongbao Zhou: School of Business Administration, Hunan University, Changsha 410082, China
Qianying Jin: School of Business Administration, Hunan University, Changsha 410082, China
Jian Peng: School of Business Administration, Hunan University, Changsha 410082, China
Helu Xiao: School of Business, Hunan Normal University, Changsha 410081, China
Shijian Wu: College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China

Mathematics, 2019, vol. 7, issue 9, 1-10

Abstract: 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.

Keywords: forecasting models; super-efficiency data envelopment analysis; undesirable factors; infeasibility (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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