برنامه ریزی درازمدت تخصیص دارایی صندوق های بازنشستگی: کاربردی از برنامه ریزی سناریو مبنا

نوع مقاله : مدیریت استراتژیک (برنامه­‌ها، تحلیل‌های استراتژیکی تولید، استراتژی‌های بازاریابی و مدیریت بازار، کسب­وکار، سرمایه گذاری، منابع انسانی، مالی، رقابت، . . . )

نویسندگان

1 دانشجوی دکتری مدیریت مالی، دانشگاه علامه طباطبایی، تهران، ایران

2 دانشیار گروه حسابداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران

3 استادیار گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران

چکیده

صندوق های بازنشستگی دولتی در ایران طی سال های آتی با بحران های جدی ای مواجه می شوند. این بحران ها می توانند ناشی از پیرتر شدن جمعیت، تجمیع بدهی های دولت، پیشی گرفتن تعداد مستمری بگیران از تعداد شاغلین، عدم مدیریت سرمایه گذاری کارآمد و نبود سیاست های سرمایه گذاری صحیح باشند. یکی از راه حل های مواجهه با این بحران، تخصیص علمی و درست دارایی های صندوق های بازنشستگی است. با توجه به راهبردی بودن این تصمیمات، در این پژوهش از برنامه ریزی سناریو مبنا به منظور شناسایی سناریوهای محتمل آتی پیش روی صندوق های بازنشستگی استفاده گردید. به منظور شناسایی مهم ترین عدم قطعیت های موجود و همچنین شناسایی سناریوها از ترکیبی از روش های دلفی فازی، ماتریس ویلسون و تحلیل ریخت شناسانه استفاده گردید. نتایج پژوهش نشان می دهند که پنج سناریوی تورم نفتی، تورم ارزی، تورم غیرنفتی و اقتصاد مقاومتی محتمل ترین سناریوهای پیش رو است و صندوق های بازنشستگی بایستی با توجه به ویژگی های هریک از سناریوها بهترین تخصیص دارایی را انجام دهند. این پژوهش مسیری جدید را به منظور برنامه ریزی راهبردی و تخصیص دارایی صندوق های بازنشستگی پیشنهاد نموده است که می تواند مورد استفاده سیاستمداران و تصمیم سازان این حوزه قرار گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

Long-Range Planning of Asset Allocation in Pension Funds: An Application of Scenario Planning

نویسندگان [English]

  • Seyed Mahdi Razavi 1
  • Moosa Bozorgasl 2
  • meysam amiry 3
1 PhD Student, Tabataba'i University, Tehran, Iran
2 Associate Professor, Accounting Department, Allameh Tabataba'i University, Tehran, Iran
3 Assistant Professor, Department of Banking and Finance, Allameh Tabataba'i University, Tehran, Iran
چکیده [English]

Public pension funds in Iran will encounter serious crises in coming years. These crises could be due to elder population, accumulation of government debts, increasing the number of pensioners in comparison with the current employees, inefficient management of investments, and lack of good investment policies. One of the solutions to tackle this problem is scientific and right asset allocation of pension funds. According to the strategic nature of these decisions, in this research, scenario planning was employed to identify the possible scenarios pension funds encountering with. In order to identifying the most important and relevant uncertainties and scenarios, a combination of Fuzzy Delphi Method, Wilson Matrix, and Morphological analysis were used. Findings depicted five scenarios of oil Inflation, currency inflation, non-oil inflation, and resistant economy are the most probable scenarios and pension funds will have to allocate their assets according to the characteristics of these scenarios. This research, proposes a new strand towards a better asset allocation and strategic planning for pension funds which should be followed by policy makers and decision makers.

کلیدواژه‌ها [English]

  • Pension Fund
  • Social Security
  • Scenario Planning
  • Wilson Matrix
  • Morphological Analysis
Amer, M., Daim, T. U., & Jetter, A. (2013). A review of scenario planning. Futures, 46, 23-40. doi:https://doi.org/10.1016/j.futures. 2012 .10.003.
Azar, A., & Safari, M. (2016). Identifying effective factors of stability in private pension funds by using soft systems methodology and fuzzy cognitive mapping. Journal of Management Sciences Society of Iran, 11(43), 21-58. (In Persian)
Bahmani, Raghfar & Mousavi, M, H.(1398). Parametric correction of Iran’s pension fund system by reducing substitutive rate: general equilibrium model of coveraged  generations and partial labor market. Economic Research Journal, 19 (72), 67-104. (In Persian)
Bradfield, R., Wright, G., Burt, G., Cairns, G., & Van Der Heijden, K. (2005). The origins and evolution of scenario techniques in long range business planning. Futures, 37(8), 795-812.
Bregnard, N., & Salva, C. (2019). Pension Fund Board Governance and Asset Allocation: Evidence from Switzerland. Available at SSRN 3334950.
Campbell, J. Y., Viceira, L. M., & Viceira, L. M. (2002). Strategic asset allocation: portfolio choice for long-term investors, Oxford University Press, USA.
Chen, Z., Li, Z., Zeng, Y., & Sun, J. (2017). Asset allocation under loss aversion and minimum performance constraint in a DC pension plan with inflation risk. Insurance: Mathematics and Economics, 75, 137-150. doi:https://doi.org/10.1016/j.insmatheco.2017.05.009
Cheng, C. H., & Lin, Y. (2002). Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research, 142(1), 174-186.
Dahlquist, M., & Odegaard, B. A. (2018). A Review of Norges Bank's Active Management of the Government Pension Fund Global. Swedish House of Finance Research Paper, (18-7).
Dahlquist, M., Setty, O., & Vestman, R. (2018). On the asset allocation of a default pension fund. The Journal of Finance73(4), 1893-1936.
Han, N.-w., & Hung, M.-w. (2012). Optimal asset allocation for DC pension plans under inflation. Insurance: Mathematics and Economics, 51(1), 172-181.
Hoevenaars, R. P., Molenaar, R. D., Schotman, P. C., & Steenkamp, T. B. (2014). Strategic asset allocation for long‐term investors: Parameter uncertainty and prior information. Journal of Applied Econometrics, 29(3), 353-376.
Hsu, Y.-L., Lee, C.-H., & Kreng, V. B. (2010). The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Expert Systems with Applications, 37(1), 419-425.
Huss, W. R., & Honton, E. J. (1987). Scenario planning—what style should you use? Long Range Planning, 20(4), 21-29.
Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G., Tatsuta, R., & Mieno, H. (1993). The max-min Delphi method and fuzzy Delphi method via fuzzy integration. Fuzzy Sets and Systems, 55(3), 241-253.
Kuzubas, T. U., Saltoğlu, B., Sert, A., & Yüksel, A. (2019). Performance evaluation of the Turkish pension fund system. Journal of Capital Markets Studies.
Lucas, D. J., & Zeldes, S. P. (2009). How should public pension plans invest? American Economic Review, 99(2), 527-532.
Ma, Z., Shao, C., Ma, S., & Ye, Z. (2011). Constructing road safety performance indicators using Fuzzy Delphi Method and Grey Delphi Method. Expert Systems with Applications, 38(3), 1509-1514.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Merton, R. C. (1969). Lifetime portfolio selection under uncertainty: The continuous-time case. The review of Economics and Statistics, 247-257.
Mir, Seyed Javad, Ganjian, Mahdi, and Gholamreza Foruhesh Tehrani. (2013). Challenges and solutions for the pension funds in Iran: a case study of pension fund of Agricultural Jihad, Journal of Strategic and Macro Policies, 2 (7), 111-139. (In Persian)
Rezaei, Ali, Vaez Mahdavi, Mohammad Reza. (1397). Optimal Investment in Mixed Pension Plans with Guaranteed Retirement Benefits. Social Security Quarterly Journal, 13 (3), 41-58. (In Persian)
Roghanizadeh, M. (2010). Challenges of pension fund system in Iran, Journal of Social Security, 29 (9), 13-31. (In Persian)
Rostami, Morteza and Badini, Hassan. (1398). Doing business in pension funds at the Social Security System of Iran. Public Law research, 21 (63), 271-295. (In Persian)
Safari, Mohammad. (1397). Sustainability of hybrid private pension plans based on fuzzy cognitive mapping and system dynamics. Iranian Journal of Insurance Research, 33 (131), 81-104. (In Persian)
Tang, M. L., Chen, S. N., Lai, G. C., & Wu, T. P. (2018). Asset allocation for a DC pension fund under stochastic interest rates and inflation-protected guarantee. Insurance: Mathematics and Economics78, 87-104.
Pagnoncelli, B. K., Reich, D., & Campi, M. C. (2012). Risk-return trade-off with the scenario approach in practice: a case study in portfolio selection. Journal of Optimization Theory and Applications, 155(2), 707-722.
Pennacchi, G., & Rastad, M. (2011). Portfolio allocation for public pension funds. Journal of Pension Economics & Finance, 10(2), 221-245.
Samuelson, P. A. (1975). Lifetime portfolio selection by dynamic stochastic programming. In Stochastic Optimization Models in Finance (pp. 517-524): Elsevier.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students (5th edition ed.). England: Pearson Education Limited.
Schwartz, P. (2012). The art of the long view: planning for the future in an uncertain world: Crown Business.
Vilkkumaa, E., Liesiö, J., Salo, A., & Ilmola-Sheppard, L. (2018). Scenario-based portfolio model for building robust and proactive strategies. European Journal of Operational Research, 266(1), 205-220.
Wilson, I. (2000). From scenario thinking to strategic action. Technological Forecasting and Social Change, 65(1), 23-29.
Levisauskaite, K. (2010). Investment Analysis and Portfolio Management, Retrieved from Canadian Institute for Health Information website: http://www.bcci.bg/ projects/latvia/pdf/8_IAPM_final.pdf