IDEAS home Printed from https://ideas.repec.org/p/ies/wpaper/e202105.html
   My bibliography  Save this paper

Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy

Author

Listed:
  • Kristiaan Kerstens

    (IESEG School of Management, CNRS-LEM (UMR 9221), Université de Lille, 3 rue de la Digue, F-59000 Lille, France)

  • Paolo Mazza

    (IESEG School of Management, CNRS-LEM (UMR 9221), 3 rue de la Digue, F-59000 Lille, France)

  • Tiantian Ren

    (Corresponding author: School of Business Administration, Hunan University, Changsha 410081, China, and IESEG School of Management, 3 rue de la Digue, F-59000 Lille, France, Tel: +33 320545892 (switch-board), Fax: +33 320574855)

  • Ignace Van de Woestyne

    (KU Leuven, Research Unit MEES, Warmoesberg 26, B-1000 Brussels, Belgium)

Abstract

This contribution introduces new frontier models to rate mutual funds that can si-multaneously handle multiple moments and multiple times. These new models are empirically applied to hedge fund data, since this category of funds is known to be subject to non-normal return distributions. We define a simple buy-and-hold backtesting strategy to test for the impact of multiple moments and multiple times separately and jointly.

Suggested Citation

  • Kristiaan Kerstens & Paolo Mazza & Tiantian Ren & Ignace Van de Woestyne, 2021. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Working Papers 2021-EQM-03, IESEG School of Management.
    • Handle: RePEc:ies:wpaper:e202105
    as

    Download full text from publisher

    File URL: https://www.ieseg.fr/wp-content/uploads/2021/05/2021-EQM-03.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kerstens, Kristiaan & Mounir, Amine & de Woestyne, Ignace Van, 2011. "Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1190-1201, May.
    2. 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.
    3. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    4. Bertrand Maillet & Emmanuel Jurczenko & Paul Merlin, 2006. "Hedge Funds Portfolio Selection with Higher-order Moments: A Non-parametric Mean-Variance-Skewness-Kurtosis Efficient Frontier," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308993, HAL.
    5. Back, Kerry, 2014. "A characterization of the coskewness–cokurtosis pricing model," Economics Letters, Elsevier, vol. 125(2), pages 219-222.
    6. Briec, Walter & Kerstens, Kristiaan, 2009. "Multi-horizon Markowitz portfolio performance appraisals: A general approach," Omega, Elsevier, vol. 37(1), pages 50-62, February.
    7. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    8. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    9. 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.
    10. U D Kumar & A B Roy & H Saranga & K Singal, 2010. "Analysis of hedge fund strategies using slack-based DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1746-1760, December.
    11. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.
    12. Kris Boudt & Dries Cornilly & Tim Verdonck, 2020. "A Coskewness Shrinkage Approach for Estimating the Skewness of Linear Combinations of Random Variables [International Asset Allocation with Regime Shifts]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 1-23.
    13. 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.
    14. El Kalak, Izidin & Azevedo, Alcino & Hudson, Robert, 2016. "Reviewing the hedge funds literature II: Hedge funds' returns and risk management characteristics," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 55-66.
    15. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    16. Branda, Martin, 2015. "Diversification-consistent data envelopment analysis based on directional-distance measures," Omega, Elsevier, vol. 52(C), pages 65-76.
    17. Darolles, Serge & Gourieroux, Christian, 2010. "Conditionally fitted Sharpe performance with an application to hedge fund rating," Journal of Banking & Finance, Elsevier, vol. 34(3), pages 578-593, March.
    18. Massol, Olivier & Banal-Estañol, Albert, 2014. "Export diversification through resource-based industrialization: The case of natural gas," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1067-1082.
    19. 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.
    20. Eling, Martin & Faust, Roger, 2010. "The performance of hedge funds and mutual funds in emerging markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1993-2009, August.
    21. Bertrand Maillet & Emmanuel Jurczenko, 2006. "Multi-moment Asset Allocation and Pricing Models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308990, HAL.
    22. 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.
    23. Louis Eeckhoudt & Harris Schlesinger, 2006. "Putting Risk in Its Proper Place," American Economic Review, American Economic Association, vol. 96(1), pages 280-289, March.
    24. Fang, Hsing & Lai, Tsong-Yue, 1997. "Co-Kurtosis and Capital Asset Pricing," The Financial Review, Eastern Finance Association, vol. 32(2), pages 293-307, May.
    25. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    26. Gregoriou, Greg N. & Sedzro, Komlan & Zhu, Joe, 2005. "Hedge fund performance appraisal using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 164(2), pages 555-571, July.
    27. Briec, Walter & Comes, Christine & Kerstens, Kristiaan, 2006. "Temporal technical and profit efficiency measurement: Definitions, duality and aggregation results," International Journal of Production Economics, Elsevier, vol. 103(1), pages 48-63, September.
    28. Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2013. "Portfolio selection with skewness: A comparison of methods and a generalized one fund result," European Journal of Operational Research, Elsevier, vol. 230(2), pages 412-421.
    29. Walter Briec & Kristiaan Kerstens & Philippe Venden Eeckaut, 2004. "Non-convex Technologies and Cost Functions: Definitions, Duality and Nonparametric Tests of Convexity," Journal of Economics, Springer, vol. 81(2), pages 155-192, February.
    30. Lin, Ruiyue & Li, Zongxin, 2020. "Directional distance based diversification super-efficiency DEA models for mutual funds," Omega, Elsevier, vol. 97(C).
    31. Serge Darolles & Christian Gourieroux, 2010. "Conditionally fitted Sharpe performance with an application to hedge fund rating," Post-Print halshs-00677727, HAL.
    32. Martin Branda & Miloš Kopa, 2014. "On relations between DEA-risk models and stochastic dominance efficiency tests," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 13-35, March.
    33. Grau-Carles, Pilar & Doncel, Luis Miguel & Sainz, Jorge, 2019. "Stability in mutual fund performance rankings: A new proposal," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 337-346.
    34. Jondeau, Eric & Rockinger, Michael, 2003. "Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements," Journal of Economic Dynamics and Control, Elsevier, vol. 27(10), pages 1699-1737, August.
    35. Heffernan, Shelagh A., 1990. "A characteristics definition of financial markets," Journal of Banking & Finance, Elsevier, vol. 14(2-3), pages 583-609, August.
    36. Bertrand Maillet & Emmanuel Jurczenko, 2006. "Multi-moment Asset Allocation and Pricing Models," Post-Print hal-00308990, HAL.
    37. Li, Qi & Maasoumi, Esfandiar & Racine, Jeffrey S., 2009. "A nonparametric test for equality of distributions with mixed categorical and continuous data," Journal of Econometrics, Elsevier, vol. 148(2), pages 186-200, February.
    38. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    39. Sears, R Stephen & Wei, K C John, 1985. "Asset Pricing, Higher Moments, and the Market Risk Premium: A Note," Journal of Finance, American Finance Association, vol. 40(4), pages 1251-1253, September.
    40. Racicot, François-Éric & Théoret, Raymond, 2018. "Multi-moment risk, hedging strategies, & the business cycle," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 637-675.
    41. Racicot, François-Éric & Théoret, Raymond, 2019. "Hedge fund return higher moments over the business cycle," Economic Modelling, Elsevier, vol. 78(C), pages 73-97.
    42. 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.
    43. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    44. Briec, Walter & Kerstens, Kristiaan, 2010. "Portfolio selection in multidimensional general and partial moment space," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 636-656, April.
    45. Bertrand Maillet & Emmanuel Jurczenko & Paul Merlin, 2006. "Hedge Funds Portfolio Selection with Higher-order Moments: A Non-parametric Mean-Variance-Skewness-Kurtosis Efficient Frontier," Post-Print hal-00308993, HAL.
    46. repec:cdl:ucsbec:30-89 is not listed on IDEAS
    47. Scott, Robert C & Horvath, Philip A, 1980. "On the Direction of Preference for Moments of Higher Order Than the Variance," Journal of Finance, American Finance Association, vol. 35(4), pages 915-919, September.
    48. 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.
    49. Blake, David, 1996. "Financial Intermediation and Financial Innovation in a Characteristics Framework," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(1), pages 16-31, February.
    50. Giovanna Menardi & Francesco Lisi, 2012. "Are performance measures equally stable?," Annals of Finance, Springer, vol. 8(4), pages 553-570, November.
    51. Campbell Harvey & John Liechty & Merrill Liechty & Peter Muller, 2010. "Portfolio selection with higher moments," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 469-485.
    52. Eling, Martin & Schuhmacher, Frank, 2007. "Does the choice of performance measure influence the evaluation of hedge funds?," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2632-2647, September.
    53. Antonella Basso & Stefania Funari, 2016. "DEA Performance Assessment of Mutual Funds," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 229-287, Springer.
    54. Joro, Tarja & Na, Paul, 2006. "Portfolio performance evaluation in a mean-variance-skewness framework," European Journal of Operational Research, Elsevier, vol. 175(1), pages 446-461, November.
    55. Trautmann, Stefan T. & Kuilen, Gijs van de, 2018. "Higher order risk attitudes: A review of experimental evidence," European Economic Review, Elsevier, vol. 103(C), pages 108-124.
    56. Stefano Benati, 2015. "Using medians in portfolio optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(5), pages 720-731, May.
    57. Friend, Irwin & Westerfield, Randolph, 1980. "Co-Skewness and Capital Asset Pricing," Journal of Finance, American Finance Association, vol. 35(4), pages 897-913, September.
    58. Cornes,Richard, 1992. "Duality and Modern Economics," Cambridge Books, Cambridge University Press, number 9780521336017, September.
    59. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    60. Briec, Walter & Dumas, Audrey & Mekki, Ayman, 2021. "Directional distance functions and social welfare: Some axiomatic and dual properties," Mathematical Social Sciences, Elsevier, vol. 113(C), pages 181-190.
    61. Daniel T. Slesnick, 1998. "Empirical Approaches to the Measurement of Welfare," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 2108-2165, December.
    62. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin, Qianying & Basso, Antonella & Funari, Stefania & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2024. "Evaluating different groups of mutual funds using a metafrontier approach: Ethical vs. non-ethical funds," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1134-1145.
    2. Carole Bernard & Massimiliano Caporin & Bertrand Maillet & Xiang Zhang, 2023. "Omega Compatibility: A Meta-analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 493-526, August.
    3. Ren, Tiantian & Wang, Na & Xiao, Helu & Zhou, Zhongbao, 2024. "Efficiency of funding to rural revitalization and regional heterogeneity of technologies in China: Dynamic network nonconvex metafrontiers," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Lin, Ruiyue & Li, Zongxin, 2020. "Directional distance based diversification super-efficiency DEA models for mutual funds," Omega, Elsevier, vol. 97(C).
    3. Kerstens, Kristiaan & Mounir, Amine & de Woestyne, Ignace Van, 2011. "Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1190-1201, May.
    4. Nalpas, Nicolas & Simar, Leopold & Vanhems, Anne, 2016. "Portfolio Selection in a Multi-Input Multi-Output Setting:a Simple Monte-Carlo-FDH Algorithm," LIDAM Discussion Papers ISBA 2016022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. 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.
    6. Lin, Ruiyue & Liu, Qian, 2021. "Multiplier dynamic data envelopment analysis based on directional distance function: An application to mutual funds," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1043-1057.
    7. 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.
    8. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
    9. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    10. 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).
    11. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    12. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.
    13. 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.
    14. 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.
    15. Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2013. "Portfolio selection with skewness: A comparison of methods and a generalized one fund result," European Journal of Operational Research, Elsevier, vol. 230(2), pages 412-421.
    16. Briec, Walter & Kerstens, Kristiaan, 2010. "Portfolio selection in multidimensional general and partial moment space," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 636-656, April.
    17. 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.
    18. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.
    19. 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.
    20. Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2021. "Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 766-781.

    More about this item

    Keywords

    Shortage function; Frontier; Fund rating;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ies:wpaper:e202105. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lies BOUTEN (email available below). General contact details of provider: https://edirc.repec.org/data/iesegfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.