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Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale

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  • Xiao, Helu
  • Zhou, Zhongbao
  • Ren, Teng
  • Liu, Wenbin

Abstract

Traditional data envelopment analysis (DEA) for estimating the portfolio efficiency requires that the portfolio frontier (theoretical frontier) is concave to ensure that the DEA efficiency in probability converges to the portfolio efficiency as the portfolio sample increases. However, in practice, the DEA efficiency is likely to overestimate the portfolio efficiency because some nonconvex settings may cause the portfolio frontier to be nonconcave. In this paper, we employ a free disposal hull (FDH) estimator by combining the free disposability and non-increasing returns to scale (NIRS) assumptions, namely FDH-NIRS estimator, to explore its theoretical nature and applications in the estimation of portfolio efficiency. First, we apply the directional distance function (DDF) to develop the portfolio frontier-, DEA-, FDH-, and FDH-NIRS-based models in the mean and value-at-risk (VaR) framework, and also show the differences between these models. Second, we transform the FDH-NIRS model into a linear equivalence model and further demonstrate that the FDH-NIRS efficiency in probability converges to the portfolio efficiency. Third, we extend the FDH-NIRS estimator to the framework of multiple return and risk measures with the purpose of showing its generalizability. Finally, we verify the validity of the proposed model and estimator by simulations.

Suggested Citation

  • Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
  • Handle: RePEc:eee:jomega:v:111:y:2022:i:c:s0305048322000792
    DOI: 10.1016/j.omega.2022.102672
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    1. Basso, Antonella & Funari, Stefania, 2001. "A data envelopment analysis approach to measure the mutual fund performance," European Journal of Operational Research, Elsevier, vol. 135(3), pages 477-492, December.
    2. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    3. Walter Briec & Kristiaan Kerstens & Octave Jokung, 2007. "Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach," Management Science, INFORMS, vol. 53(1), pages 135-149, January.
    4. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    5. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    6. Babat, Onur & Vera, Juan C. & Zuluaga, Luis F., 2018. "Computing near-optimal Value-at-Risk portfolios using integer programming techniques," European Journal of Operational Research, Elsevier, vol. 266(1), pages 304-315.
    7. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    8. Kerstens, Kristiaan & O’Donnell, Christopher & Van de Woestyne, Ignace, 2019. "Metatechnology frontier and convexity: A restatement," European Journal of Operational Research, Elsevier, vol. 275(2), pages 780-792.
    9. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.
    10. Leleu, Herve, 2006. "A linear programming framework for free disposal hull technologies and cost functions: Primal and dual models," European Journal of Operational Research, Elsevier, vol. 168(2), pages 340-344, January.
    11. W. Briec & K. Kerstens & J. B. Lesourd, 2004. "Single-Period Markowitz Portfolio Selection, Performance Gauging, and Duality: A Variation on the Luenberger Shortage Function," Journal of Optimization Theory and Applications, Springer, vol. 120(1), pages 1-27, January.
    12. Branda, Martin, 2015. "Diversification-consistent data envelopment analysis based on directional-distance measures," Omega, Elsevier, vol. 52(C), pages 65-76.
    13. Robert Thrall, 1999. "What Is the Economic Meaning of FDH?," Journal of Productivity Analysis, Springer, vol. 11(3), pages 243-250, June.
    14. Martin Branda, 2016. "Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour," 4OR, Springer, vol. 14(1), pages 77-99, March.
    15. Brandouy, Olivier & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2015. "Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis," European Journal of Operational Research, Elsevier, vol. 242(1), pages 332-342.
    16. Per Agrell & Jørgen Tind, 2001. "A Dual Approach to Nonconvex Frontier Models," Journal of Productivity Analysis, Springer, vol. 16(2), pages 129-147, September.
    17. Alois Kneip & Léopold Simar & Paul W. Wilson, 2016. "Testing Hypotheses in Nonparametric Models of Production," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 435-456, July.
    18. Podinovski, V. V., 2004. "On the linearisation of reference technologies for testing returns to scale in FDH models," European Journal of Operational Research, Elsevier, vol. 152(3), pages 800-802, February.
    19. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    20. Xiangyu Cui & Li Duan & Jiaan Yan, 2015. "Classical mean-variance model revisited: pseudo efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(10), pages 1646-1655, October.
    21. Lin, Ruiyue & Li, Zongxin, 2020. "Directional distance based diversification super-efficiency DEA models for mutual funds," Omega, Elsevier, vol. 97(C).
    22. Soleimani-damaneh, M. & Jahanshahloo, G.R. & Reshadi, M., 2006. "On the estimation of returns-to-scale in FDH models," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1055-1059, October.
    23. Brandouy, Olivier & Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2010. "Portfolio performance gauging in discrete time using a Luenberger productivity indicator," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1899-1910, August.
    24. Basso, Antonella & Funari, Stefania, 2014. "Constant and variable returns to scale DEA models for socially responsible investment funds," European Journal of Operational Research, Elsevier, vol. 235(3), pages 775-783.
    25. Kneip, Alois & Park, Byeong U. & Simar, Léopold, 1998. "A Note On The Convergence Of Nonparametric Dea Estimators For Production Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 14(6), pages 783-793, December.
    26. Ruiyue Lin & Zhiping Chen & Qianhui Hu & Zongxin Li, 2017. "Dynamic network DEA approach with diversification to multi-period performance evaluation of funds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 821-860, July.
    27. Kerstens, Kristiaan & Mounir, Amine & Van de Woestyne, Ignace, 2011. "Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function," European Journal of Operational Research, Elsevier, vol. 210(1), pages 81-94, April.
    28. Xiao, Helu & Ren, Tiantian & Zhou, Zhongbao & Liu, Wenbin, 2021. "Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach," Omega, Elsevier, vol. 103(C).
    29. Dimitris N. Politis, 2004. "A Heavy-Tailed Distribution for ARCH Residuals with Application to Volatility Prediction," Annals of Economics and Finance, Society for AEF, vol. 5(2), pages 283-298, November.
    30. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2017. "Global and local scale characteristics in convex and nonconvex nonparametric technologies: A first empirical exploration," European Journal of Operational Research, Elsevier, vol. 259(2), pages 576-586.
    31. Park, B.U. & Simar, L. & Weiner, Ch., 2000. "The Fdh Estimator For Productivity Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 16(6), pages 855-877, December.
    32. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2015. "When Bias Kills The Variance: Central Limit Theorems For Dea And Fdh Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 31(2), pages 394-422, April.
    33. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    34. Zhou, Zhongbao & Xiao, Helu & Jin, Qianying & Liu, Wenbin, 2018. "DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure," European Journal of Operational Research, Elsevier, vol. 269(1), pages 111-131.
    35. Dekker, David & Post, Thierry, 2001. "A quasi-concave DEA model with an application for bank branch performance evaluation," European Journal of Operational Research, Elsevier, vol. 132(2), pages 296-311, July.
    36. Helu Xiao & Tiantian Ren & Teng Ren, 2020. "Estimation of fuzzy portfolio efficiency via an improved DEA approach," Post-Print hal-03281789, HAL.
    37. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    38. Helu Xiao & Tiantian Ren & Zhongbao Zhou & Wenbin Liu, 2021. "Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach," Post-Print hal-03281804, HAL.
    39. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    40. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    41. Briec, Walter & Kerstens, Kristiaan, 2009. "Multi-horizon Markowitz portfolio performance appraisals: A general approach," Omega, Elsevier, vol. 37(1), pages 50-62, February.
    42. Dominique Deprins & Léopold Simar & Henry Tulkens, 2006. "Measuring Labor-Efficiency in Post Offices," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 285-309, Springer.
    43. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    44. Zhou, Zhongbao & Jin, Qianying & Xiao, Helu & Wu, Qian & Liu, Wenbin, 2018. "Estimation of cardinality constrained portfolio efficiency via segmented DEA," Omega, Elsevier, vol. 76(C), pages 28-37.
    45. Murthi, B. P. S. & Choi, Yoon K. & Desai, Preyas, 1997. "Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach," European Journal of Operational Research, Elsevier, vol. 98(2), pages 408-418, April.
    46. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    47. Benati, Stefano & Rizzi, Romeo, 2007. "A mixed integer linear programming formulation of the optimal mean/Value-at-Risk portfolio problem," European Journal of Operational Research, Elsevier, vol. 176(1), pages 423-434, January.
    48. Briec, Walter & Liang, Qi Bin, 2011. "On some semilattice structures for production technologies," European Journal of Operational Research, Elsevier, vol. 215(3), pages 740-749, December.
    49. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    50. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    51. Shushang Zhu & Masao Fukushima, 2009. "Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management," Operations Research, INFORMS, vol. 57(5), pages 1155-1168, October.
    52. Jianjun Gao & Duan Li, 2013. "Optimal Cardinality Constrained Portfolio Selection," Operations Research, INFORMS, vol. 61(3), pages 745-761, June.
    53. Lamb, John D. & Tee, Kai-Hong, 2012. "Data envelopment analysis models of investment funds," European Journal of Operational Research, Elsevier, vol. 216(3), pages 687-696.
    54. Politis, Dimitris N., 2004. "A heavy-tailed distribution for ARCH residuals with application to volatility prediction," University of California at San Diego, Economics Working Paper Series qt7r89639x, Department of Economics, UC San Diego.
    55. Cuoco, Domenico, 1997. "Optimal Consumption and Equilibrium Prices with Portfolio Constraints and Stochastic Income," Journal of Economic Theory, Elsevier, vol. 72(1), pages 33-73, January.
    56. Morey, Matthew R. & Morey, Richard C., 1999. "Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking," Omega, Elsevier, vol. 27(2), pages 241-258, April.
    57. Nalpas, Nicolas & Simar, Leopold & Vanhems, Anne, 2017. "Portfolio selection in a multi-moment setting: A simple Monte-Carlo-FDH algorithm," LIDAM Reprints ISBA 2017027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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