Issue
RAIRO-Oper. Res.
Volume 53, Number 5, November-December 2019
Fuzzy Data Envelopment Analysis: Recent Developments and Applications
Page(s) 1581 - 1600
DOI https://doi.org/10.1051/ro/2019071
Published online 08 October 2019
  • A. Basso and S. Funari, A data envelopment analysis approach to measure the mutual fund performance. Eur. J. Oper. Res. 135 (2001) 477–492. [Google Scholar]
  • M. Branda, Diversification-consistent data envelopment analysis with general deviation measures. Eur. J. Oper. Res. 226 (2013) 626–635. [Google Scholar]
  • M. Branda, Reformulations of input–output oriented DEA tests with diversification. Oper. Res. Lett. 41 (2013) 516–520. [CrossRef] [Google Scholar]
  • M. Branda, Diversification-consistent data envelopment analysis based on directional-distance measures. Omega 52 (2015) 65–76. [Google Scholar]
  • W. Briec and K. Kerstens, Multi-horizon Markowitz portfolio performance appraisals: a general approach. Omega 37 (2009) 50–62. [Google Scholar]
  • W. Briec, K. Kerstens and J.B. Lesourd, Single-period Markowitz portfolio selection, performance gauging, and duality: a variation on the Luenberger shortage function. J. Optim. Theor. App. 120 (2004) 1–27. [CrossRef] [Google Scholar]
  • W. Briec, K. Kerstens and O. Jokung, Mean-variance-skewness portfolio performance gauging: a general shortage function and dual approach. Manage. Sci. 53 (2007) 135–149. [Google Scholar]
  • E. Cao and M. Lai, A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands. J. Comput. Appl. Math. 231 (2009) 302–310. [Google Scholar]
  • J. Cao, G. Lian and T.R.N. Roslan, Pricing variance swaps under stochastic volatility and stochastic interest rate. Appl. Math. Comput. 277 (2016) 72–81. [Google Scholar]
  • M.M. Carhart, On persistence in mutual fund performance. J. Finance 52 (1997) 57–82. [Google Scholar]
  • C. Carlsson, R. Fullér and P. Majlender, A possibilistic approach to selecting portfolios with highest utility score. Fuzzy Sets Syst. 1 (2002) 13–21. [CrossRef] [Google Scholar]
  • Z. Chen and R. Lin, Mutual fund performance evaluation using data envelopment analysis with new risk measures. Or Spectr. 28 (2006) 375–398. [Google Scholar]
  • W. Chen, Y. Gai and P. Gupta, Efficiency evaluation of fuzzy portfolio in different risk measures via DEA. Ann. Oper. Res. 269 (2018) 103–127. [Google Scholar]
  • W. Chen, S. Li, J. Zhang and M.K. Mehlawat, A comprehensive model for fuzzy multi-objective portfolio selection based on DEA cross-efficiency model. To appear in Soft Comput. DOI: 10.1007/s00500-018-3595-x (2018). [Google Scholar]
  • H. Ding, Z. Zhou, H. Xiao, C. Ma and W. Liu, Performance evaluation of portfolios with margin requirements. Math. Prob. Eng. 2014 (2014) 1–8. [Google Scholar]
  • D. Dubois and H. Prade, Possibility Theory. Edited by Meyers, R.A. In Encyclopedia of Complexity and Systems Science. Springer, Heidelberg (2009) 6927–6939. [CrossRef] [Google Scholar]
  • E.F. Fama and K.R. French, Disagreements, tastes and asset prices. J. Financial Econ. 83 (1993) 667–689. [CrossRef] [Google Scholar]
  • X. Huang, Mean-entropy models for fuzzy portfolio selection. IEEE Trans. Fuzzy Syst. 16 (2008) 1096–1101. [Google Scholar]
  • Y. Huang, X. Yang and J. Zhou, Optimal investment and proportional reinsurance for a jump–diffusion risk model with constrained control variables. J. Comput. Appl. Math. 296 (2016) 443–461. [Google Scholar]
  • M.C. Jensen, The performance of mutual funds in the period 1945–1964. J. Finance 2 (1968) 389–416. [Google Scholar]
  • T. Joro and P. Na, Portfolio performance evaluation in a mean-variance-skewness framework. Eur. J. Oper. Res. 175 (2006) 446–461. [Google Scholar]
  • J.S. Kamdem, C.T. Deffo and L.A. Fono, Moments and semi-moments for fuzzy portfolio selection. Insurance Math. Econ. 51 (2012) 517–530. [CrossRef] [Google Scholar]
  • J.D. Lamb and K.H. Tee, Data envelopment analysis models of investment funds. Eur. J. Oper. Res. 216 (2012) 687–696. [Google Scholar]
  • B. Liu and Y.K. Liu, Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst. 10 (2002) 445–450. [Google Scholar]
  • Y. Liu and W. Zhang, A multi-period fuzzy portfolio optimization model with minimum transaction lots. Eur. J. Oper. Res. 242 (2015) 933–941. [Google Scholar]
  • Y. Liu, W. Zhang and W. Xu, Fuzzy multi-period portfolio selection optimization models using multiple criteria. Automatica 48 (2012) 3042–3053. [CrossRef] [Google Scholar]
  • W. Liu, Z. Zhou, D. Liu and H. Xiao, Estimation of portfolio efficiency via DEA. Omega 52 (2015) 107–118. [Google Scholar]
  • S. Lozano and E. Gutiérrez, Data envelopment analysis of mutual funds based on second-order stochastic dominance. Eur. J. Oper. Res. 189 (2008) 230–244. [Google Scholar]
  • H. Markowitz, Portfolio selection. J. Finance 7 (1952) 77–91. [Google Scholar]
  • Z. Mashayekhi and H. Omrani, An integrated multi-objective Markowitz–DEA cross-efficiency model with fuzzy returns for portfolio selection problem. Appl. Soft Comput. 38 (2016) 1–9. [Google Scholar]
  • M.K. Mehlawat, Credibilistic mean-entropy models for multi-period portfolio selection with multi-choice aspiration levels. Inf. Sci. 345 (2016) 9–26. [Google Scholar]
  • M.R. Morey and R.C. Morey, Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking. Omega 27 (1999) 241–258. [Google Scholar]
  • B.P.S. Murthi, Y.K. Choi and P. Desai, Efficiency of mutual funds and portfolio performance measurement: a non-parametric approach. Eur. J. Oper. Res. 98 (1997) 408–418. [Google Scholar]
  • Z. Qin, X. Li and X. Ji, Portfolio selection based on fuzzy cross-entropy. J. Comput. Appl. Math. 228 (2009) 139–149. [Google Scholar]
  • A. Saeidifar and E. Pasha, On the possibilistic moments of fuzzy numbers and their applications. J. Comput. Appl. Math. 223 (2009) 1028–1042. [Google Scholar]
  • W.F. Sharpe, Mutual fund performance. J. Bus. 1 (1966) 119–138. [Google Scholar]
  • M. Silva Portela, E. Thanassoulis and G. Simpson, Negative data in DEA: a directional distance approach applied to bank branches. J. Oper. Res. Soc. 55 (2004) 1111–1121. [Google Scholar]
  • J.L. Treynor, How to rate management of investment funds. Harvard Bus. Rev. 43 (1965) 63–75. [Google Scholar]
  • E. Vercher, J.D. Bermúdez and J.V. Segura, Fuzzy portfolio optimization under downside risk measures. Fuzzy Sets Syst. 158 (2007) 769–782. [CrossRef] [Google Scholar]
  • L.A. Zadeh, Fuzzy sets. Inf. Control 8 (1965) 338–353. [CrossRef] [MathSciNet] [Google Scholar]
  • P. Zhang and W. Zhang, Multiperiod mean absolute deviation fuzzy portfolio selection model with risk control and cardinality constraints. Fuzzy Sets Syst. 255 (2014) 74–91. [CrossRef] [Google Scholar]
  • W. Zhang, Y. Liu and W. Xu, A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs. Eur. J. Oper. Res. 222 (2012) 341–349. [Google Scholar]
  • X. Zhao, S. Wang and K.K. Lai, Mutual funds performance evaluation based on endogenous benchmarks. Expert Syst. App. 38 (2011) 3663–3670. [CrossRef] [Google Scholar]
  • Z. Zhou, L. Zhao, S. Lui and C. Ma, A generalized fuzzy DEA/AR performance assessment model. Math. Comput. Model. 55 (2012) 2117–2128. [Google Scholar]
  • Z. Zhou, H. Xiao, J. Yin, X. Zeng and L. Lin, Pre-commitment vs. time-consistent strategies for the generalized multi-period portfolio optimization with stochastic cash flows. Insurance: Math. Econ. 68 (2016) 187–202. [CrossRef] [Google Scholar]
  • Z. Zhou, Q. Jin, H. Xiao, Q. Wu and W. Liu, Estimation of cardinality constrained portfolio efficiency via segmented DEA. Omega 76 (2018) 28–37. [Google Scholar]
  • Z. Zhou, X. Liu, H. Xiao, T. Ren and W. Liu, Time-consistent strategies for multi-period portfolio optimization with/without the risk-free asset. Math. Prob. Eng. 2018 (2018) 20. [Google Scholar]
  • Z. Zhou, H. Xiao, Q. Jin, W. Liu, DEA frontier improvement and portfolio rebalancing: an application of China mutual funds on considering sustainability information disclosure. Eur. J. Oper. Res. 269 (2018) 111–131. [Google Scholar]
  • Z. Zhou, X. Zeng, H. Xiao, T. Ren and W. Liu, Multiperiod portfolio optimization for asset-liability management with quadratic transaction costs. J. Ind. Manage. Optim. 15 (2019) 1493–1515. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.