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Dominance-Based Decision Rules for Pension Fund Selection under Different Distributional Assumptions

Author

Listed:
  • Audrius Kabašinskas

    (Department of Mathematical Modelling, Faculty of Mathematics and Natural Sciences, Kaunas University of Technology, 44249 Kaunas, Lithuania
    These authors contributed equally to this work.)

  • Kristina Šutienė

    (Department of Mathematical Modelling, Faculty of Mathematics and Natural Sciences, Kaunas University of Technology, 44249 Kaunas, Lithuania
    These authors contributed equally to this work.)

  • Miloš Kopa

    (Department of Mathematical Modelling, Faculty of Mathematics and Natural Sciences, Kaunas University of Technology, 44249 Kaunas, Lithuania
    Department of Probability and Mathematical statistics, Faculty of Mathematics and Physics, Charles University, 121 16 Prague, Czech Republic
    These authors contributed equally to this work.)

  • Kęstutis Lukšys

    (Department of Applied Mathematics, Faculty of Mathematics and Natural Sciences, Kaunas University of Technology, 44249 Kaunas, Lithuania
    These authors contributed equally to this work.)

  • Kazimieras Bagdonas

    (Department of Computer Science, Faculty of Informatics, Kaunas University of Technology, 44249 Kaunas, Lithuania
    These authors contributed equally to this work.)

Abstract

The pension landscape is changing due to the market situation, and technological change has enabled financial innovations. Pension savers usually seek financial advice to make a personalised decision in selecting the right pension fund for them. As such, decision rules based on the assumed risk profile of the decision maker could be generated by making use of stochastic dominance (SD). In the paper, the second-pillar pension funds operating in Lithuania and Slovakia are analysed according to SD rules. The importance of the distributional assumption is explored while comparing the results of empirical, student- t , Hyperbolic and Normal Inverse Gaussian distributions to generate SD-based rules that could be integrated into an advisory solution. Moreover, due to the differences in SD results under different distributional assumptions, a new SD ratio is proposed that condenses the dominance-based relations for all considered dominance orders and probability distributions. The empirical results indicate that this new SD ratio efficiently characterises not only the preference of each fund individually but also of a group of funds with the same attributes, thus enabling multi-risk and multi-country comparisons.

Suggested Citation

  • Audrius Kabašinskas & Kristina Šutienė & Miloš Kopa & Kęstutis Lukšys & Kazimieras Bagdonas, 2020. "Dominance-Based Decision Rules for Pension Fund Selection under Different Distributional Assumptions," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:5:p:719-:d:353759
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    References listed on IDEAS

    as
    1. Thierry Post & Yi Fang & Miloš Kopa, 2015. "Linear Tests for Decreasing Absolute Risk Aversion Stochastic Dominance," Management Science, INFORMS, vol. 61(7), pages 1615-1629, July.
    2. Willem Klein Haneveld & Matthijs Streutker & Maarten Vlerk, 2010. "An ALM model for pension funds using integrated chance constraints," Annals of Operations Research, Springer, vol. 177(1), pages 47-62, June.
    3. Miloš Kopa & Vittorio Moriggia & Sebastiano Vitali, 2018. "Individual optimal pension allocation under stochastic dominance constraints," Annals of Operations Research, Springer, vol. 260(1), pages 255-291, January.
    4. Pierre Matek & Marko Lukač & Vedrana Repač, 2015. "Performance appraisal of Croatian mandatory pension funds," Effectus - Working Paper Series 0004, Effectus - University College for Law and Finance.
    5. Audrius Kabašinskas & Francesca Maggioni & Kristina Šutienė & Eimutis Valakevičius, 2019. "A multistage risk-averse stochastic programming model for personal savings accrual: the evidence from Lithuania," Annals of Operations Research, Springer, vol. 279(1), pages 43-70, August.
    6. Farinelli, Simone & Ferreira, Manuel & Rossello, Damiano & Thoeny, Markus & Tibiletti, Luisa, 2008. "Beyond Sharpe ratio: Optimal asset allocation using different performance ratios," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2057-2063, October.
    7. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
    8. World Bank, 2008. "The World Bank Pension Conceptual Framework," World Bank Publications - Reports 11139, The World Bank Group.
    9. Carlos Pestana Barros & Maria Teresa Medeiros Garcia, 2006. "Performance Evaluation of Pension Funds Management Companies with Data Envelopment Analysis," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 9(2), pages 165-188, September.
    10. Annamaria Lusardi, 2019. "Financial literacy and the need for financial education: evidence and implications," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-8, December.
    11. Maram Alwohaibi & Diana Roman, 2018. "ALM models based on second order stochastic dominance," Computational Management Science, Springer, vol. 15(2), pages 187-211, June.
    12. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, December.
    13. Virginie Konlack Socgnia & Diane Wilcox, 2014. "A Comparison of Generalized Hyperbolic Distribution Models for Equity Returns," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-15, June.
    14. Thierry Post & Miloš Kopa, 2017. "Portfolio Choice Based on Third-Degree Stochastic Dominance," Management Science, INFORMS, vol. 63(10), pages 3381-3392, October.
    15. Richard Hinz & Heinz P. Rudolph & Pablo Antolin & Juan Yermo, 2010. "Evaluating the Financial Performance of Pension Funds," World Bank Publications - Books, The World Bank Group, number 2405, December.
    16. Alois Geyer & William T. Ziemba, 2008. "The Innovest Austrian Pension Fund Financial Planning Model InnoALM," Operations Research, INFORMS, vol. 56(4), pages 797-810, August.
    17. M. I. Kusy & W. T. Ziemba, 1986. "A Bank Asset and Liability Management Model," Operations Research, INFORMS, vol. 34(3), pages 356-376, June.
    18. Petr Kupčík & Pavel Gottwald, 2016. "The Return-risk Performance of Selected Pension Fund in OECD with Focus on the Czech Pension System," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(6), pages 1981-1988.
    19. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    20. Giuseppe Carone & Per Eckefeldt & Luigi Giamboni & Veli Laine & Stéphanie Pamies Sumner, 2016. "Pension Reforms in the EU since the Early 2000's: Achievements and Challenges Ahead," European Economy - Discussion Papers 042, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    21. Moriggia, Vittorio & Kopa, Miloš & Vitali, Sebastiano, 2019. "Pension fund management with hedging derivatives, stochastic dominance and nodal contamination," Omega, Elsevier, vol. 87(C), pages 127-141.
    22. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Racheva-Iotova, Boryana & Fabozzi, Frank J., 2011. "Fat-tailed models for risk estimation," Working Paper Series in Economics 30, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    23. Kumar, Rajesh, 2014. "Strategies of Banks and Other Financial Institutions," Elsevier Monographs, Elsevier, edition 1, number 9780124169975.
    24. Post, Thierry & Kopa, Miloš, 2013. "General linear formulations of stochastic dominance criteria," European Journal of Operational Research, Elsevier, vol. 230(2), pages 321-332.
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