Optimization of The Portfolio of Financial Institution Pension Funds in Indonesia Using the Response Surface Methodology
Abstract
Investments in pension funds consist of government bonds, deposits, bonds, shares, mutual funds, and other investments. Pension funds consist of the Employer Pension Fund (EPF) and the Financial Institution Pension Fund (FIPF). The problem with FIPF is that participants choose investments at the beginning of membership and changes to investment and retirement, so there is a need for research regarding investment placement in FIPF because the average percentage growth in FIPF investments and the average percentage increase in FIPF net worth throughout the 2015–2021 period are the highest. Maximum portfolio placement for each investment, namely government bonds, deposits, bonds, shares, mutual funds, and other investments, which are a combination of independent variables, is the solution for the performance of investment managers at FIPF. In addition, the response variable maximizes the return value and minimizes the standard deviation or risk value to support maximum investment results and determines the maximum portfolio placement of each investment, namely government bonds, deposits, bonds, shares, mutual funds, and other investments, which are free combinations. In the experiment, it is hoped that it can provide alternative literature for investment managers. Apart from knowing the optimal composition of investment placements in FIPF, it is used as a reference for selecting investment packages and for FIPF participants at the start of selecting an investment package and when changing investment packages. The RSM (Response Surface Methodology) method can provide maximum portfolio placement results from each investment: government bonds, bank deposits, corporate bonds, shares, mutual funds, and other investments. Apart from that, the author chose the RSM method because its function is to find out the combination of independent variables to get optimal results, either maximum or minimum, and with an experimental design using several factorial designs that dominate the middle value and points with output in the form of independent variable values and optimal responses previously unknown. The result of this writing is that the maximum return value is 597.294, with the free variable value being the maximization of the return value that supports the maximum return value, such as government bonds = 22.45, deposits = 61.14, bonds = 14.18, shares = 12.76, mutual funds = 5.92, and other investments = 0.46. Based on placement investment and the value of maximization results obtained in the RSM method, which has almost the same results as real data, it proves that the RSM method can confirm the performance behavior of investment managers in FIPF. On the other hand, with the free variable value, the maximum return value is 570.83 and a minimum standard deviation value of 112.38, which is the maximization of the return value, which supports the maximum return value, such as government bonds = 22.45, deposits = 61.14, bonds = 3.49, shares = 2.48, mutual funds = 2.91, and other investments = 0.18. Based on the order and value of the maximization results obtained in the RSM method, the results are almost the same as real data, but by minimizing the standard deviation (risk) value, the percentage of investment placement changes where the placement of bonds, shares, and mutual funds is transferred to deposits and government bonds. This proves that the influence of the minimal standard deviation of the RSM method produces confirmation that is slightly contradictory to the behavior of FIPF investment managers. By using the RSM method in optimizing pension fund investment placement by maximizing the independent variable, the return value reflects the behavior of FIPF pension fund investment managers in half the placement percentage, but in optimizing pension fund investment placement with response variables, maximizing the return value and minimizing the standard deviation (risk) value change the investment placement percentage. By minimizing standard deviation (risk), placements in bonds, shares, and mutual funds are shifted to safe or risk-free assets, namely government bonds and deposits, with the data used from 2015 to 2021 before and during the COVID-19 pandemic. 19, so this research can be used as literature during a crisis, but it is not appropriate to use it during normal conditions
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OECD, (2021), Pension Markets in Focus 2021, www.oecd.org/finance/pensionmarketsinfocus.html, quoted on October 23 2022 at 20:00 WIB.
Sondang Samosir, Indra Tumbelaka, Muhammad Algifari, Nunung Nuryartono, Syamsul Hidayat Pasaribu, Anna Fariyanti, (2020), “What Determines the Participation in the Pension Fund? Evidence from Indonesia?”, OJK Research Seminar on August 15, 2020, Jakarta.
Financial Services Authority, (2022), “Pension Fund Statistics 2021”, first edition, Directorate of Non-Bank Financial Industry Statistics and Information Financial Services Authority, Jakarta.
Financial Services Authority, (2021), “Pension Fund Statistics 2020”, first edition, Directorate of Non-Bank Financial Industry Statistics and Information Financial Services Authority, Jakarta.
Ling Zhang, Hao Zhang dan Haixiang Yao, (2018), “Optimal investment management for a defined contribution pension fund under imperfect information”, Elsevier Ltd, Accepted Manuscript To appear in Insurance: Mathematics and Economics, DOI:10.1016/j.insmatheco.2016.08.005.
Claudiu Herteliu, Susanna Levantesi dan Giulia Rotundo, (2021), “Network analysis of pension funds investments”, Elsevier Ltd, Physica A 579 (2021) 126139, https://doi.org/10.1016/j.physa.2021.126139
Viviana Albani, Heather Brown, Esperanza Vera Toscano, Andrew Kingston, Terje Andreas Eikemo dan Clare Bambra, (2022), “Investigating the impact on mental wellbeing of an increase in pensions: A longitudinal analysis by area-level deprivation in England, 1998–2002”, Elsevier Ltd, Journal Pre-proof to appear in Social Science and Medicine, https://doi.org/10.1016/j.socscimed.2022.115316
Joelle H. Fong, Benedict S.K. Koh, Olivia S. Mitchell dan Susann Rohwedder, (2020), “Financial literacy and financial decision-making at older ages”, Elsevier Ltd, Pacific-Basin Finance Journal 65 (2021) 101481. https://doi.org/10.1016/j.pacfin.2020.101481.
Edikan E. Akpanibah Obinichi C. Mandah Imoleayo S. Asiwaju. (2019). Effect of Supplementary Premium on the Optimal Portfolio Policy in a Defined Contribution Pension Scheme with Refund of Premium Clauses. International Journal of Engineering, Mathematical and Physical Sciences 12.0(5), https://zenodo.org/record/3298568.
Luis Berggrun Preciado. (2010). Performance evaluation, fund selection, and portfolio allocation applied to Colombia’s pension funds. Estudios Gerenciales, 26(117), 13–40. https://doi.org/10.1016/S0123-5923(10)70132-7.
Michail Anthropelos, & Evmorfia Blontzou. (2023). On Valuation and Investments of Pension Plans in Discrete Incomplete Markets. Risks, 11(6), 103. https://doi.org/10.3390/risks11060103.
Vanya Horneff, Raimond Maurer dan Olivia S. Mitchell, (2020), “Putting the pension back in 401(k) retirement plans: Optimal versus default deferred longevity income annuities”, Elsevier Ltd, Journal of Banking and Finance 114 (2020) 105783. https://doi.org/10.1016/j.socscimed.2022.115316.
Herteliu C., Levantesi S., & Rotundo G. (2021). Network analysis of pension funds investments. http://hdl.handle.net/11573/1572195, https://doi.org/10.1016/j.physa.2021.126139.
I. Baltas, L. Dopierala, K. Kolodziejczyk, M. Szczepanski, G.-W. Weber dan A.N. Yannacopoulos, (2021), “Optimal management of defined contribution pension funds under the effect of inflation, mortality, and uncertainty”, Elsevier Ltd, Journal Pre-proof to appear in: European Journal of Operational Research, https://doi.org/10.1016/j.ejor.2021.08.038.
VIGNA, E. (2014). On efficiency of mean-variance based portfolio selection in defined contribution pension schemes. http://hdl.handle.net/2318/108620, http://dx.doi.org/10.2139/ssrn.1775806.
Kevin Maritato, Morton Lane, Matthew Murphy, & Stan Uryasev. (2022). Optimal Allocation of Retirement Portfolios. Journal of Risk and Financial Management, 15(65), 65. https://doi.org/10.3390/jrfm15020065.
Florian Egli, David Scharer dan Bjarne Steffen, (2022), “Determinants of fossil fuel divestment in European pension funds”, Elsevier Ltd, Ecological Economic 191 (2022) 107237, https://doi.org/10.1016/j.ecolecon.2021.107237.
Liu, W., & Jing, K. (2023). ESG portfolio for TDFs with time‐varying higher moments and cardinality constraints. International Transactions in Operational Research. https://doi.org/10.1111/itor.13364.
Gireesh Shrimali. (2019). Do clean energy (equity) investments add value to a portfolio? Green Finance, 1(2), 188–204. https://doi.org/10.3934/GF.2019.2.188.
Mei-Ling Tang, Ting-Pin Wu, & Ming-Chin Hung. (2022). Optimal Pension Fund Management with Foreign Investment in a Stochastic Environment. Mathematics, 10(2468), 2468. https://doi.org/10.3390/math10142468.
Bouchekourte Mustapha, & El Hami Norelislam. (2022). Optimization of equity allocations of institutional investors: study of Moroccan case. International Journal for Simulation and Multidisciplinary Design Optimization, 13, 12. https://doi.org/10.1051/smdo/2021042.
Myers, RH dan DC Montgomery. (1995). Response Surface Methodology: Process and Product Optimization Using Designed Experiments. New York: John Wiley & Sons, Inc.
Montgomery, DC. 2001. Design and Analysis of Experiments 5th edition. New York: John Wiley & Sons, Inc. Myers, RH dan DC Montgomery. 1995. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. New York: John Wiley & Sons, Inc.
M Ismed Surianegara, & Sudjono. (2022). Investment Portfolio Optimization and Performance (Case Study on PLN Pension Fund Period 2010-2020). International Journal of Innovative Science and Research Technology 7(8) 1772-1779. https://zenodo.org/record/7098432, https://doi.org/10.47191/ijcsrr/V6-i2-67
Wisista, R. T., & Noveria, A. (2023). Optimizing Pension Fund Investment Portfolio Using Post-modern Portfolio Theory (PMPT) Study Case: An Indonesian Institution. European Journal of Business and Management Research, 8(5), 55–61. https://doi.org/10.24018/ejbmr.2023.8.5.2097.
Gokmenoglu, K., & Hesami, S. (2019). Real estate prices and the stock market in Germany: analysis based on hedonic price index. International Journal of Housing Markets and Analysis, 12(4), 687–707. https://doi.org/10.1108/ijhma-05-2018-0036.
Ahmad Farahani Darestani, Mohammadreza Miri Lavasani, Hamidreza Kordlouie, & Ghodratallah Talebnia. (2022). Forming Efficient Frontier in Stock Portfolios by Utility Function, Risk Aversion, and Target Return. Iranian Journal of Finance, 6(2), 95–119. https://doi.org/10.30699/ijf.2021.256924.1172.
DOI: https://doi.org/10.53889/gmpics.v3.421
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