Asset liability management for the Bank of Uganda defined benefits scheme by stochastic programming

• Autorzy: Mukalazi Herbert , Larsson Torbjörn , Kasozi Juma , Mayambala Fred

Identyfikatory

DOI

10.37190/ord220207

• Języki publikacji: EN

Abstrakty

EN

We develop a model for asset liability management of pension funds, which is solved by stochastic programming techniques. Using data provided by the Bank of Uganda Defined Benefits Scheme, which is closed to new members, we obtain the optimal investment policies. Randomly sampled scenario trees using the mean and covariance structure of the return distribution are used for generating the coefficients of the stochastic program. Liabilities are modelled by remaining years of life expectancy and guaranteed period for monthly pension. We obtain the funding situation of the scheme at each stage, and the terminal cash injection by the sponsor required to meet all future benefit payments, in absence of contributing members.

Słowa kluczowe

EN

closed scheme; finance; asset liability management; scenario generation; stochastic programming

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2022
• Tom: Vol. 32, No. 2
• Strony: 105--124
• Opis fizyczny: Bibliogr. 28 poz., rys.

Twórcy

autor

Mukalazi Herbert

• Department of Mathematics, Makerere University, Uganda

• https://orcid.org/0000-0001-9729-3943

autor

Larsson Torbjörn

• Department of Mathematics, Linköping University, Sweden

• https://orcid.org/0000-0003-2094-7376

autor

Kasozi Juma

• Department of Mathematics, Makerere University, Uganda

• https://orcid.org/0000-0002-0941-9604

autor

Mayambala Fred

• Department of Mathematics, Makerere University, Uganda

Bibliografia

• [1] Bai, M., and Ma, J. The CVaR constrained stochastic programming ALM model for defined benefit pension funds. International Journal of Modelling, Identification and Control 8, 1 (2009), 48–55.
• [2] Birge, J. R., and Louveaux, F. Introduction to Stochastic Programming. Springer Science & Business Media, 2011.
• [3] Boender, G. C. E. A hybrid simulation/optimization scenario model for asset/liability management. European Journal of Operational Research 99, 1 (1997), 126–135.
• [4] Bogentoft, E., Romeijn, H. E., and Uryasev, S. Asset/liability management for pension funds using CVaR constraints. Journal of Risk Finance 3, 1 (2001), 57–71.
• [5] Bogomolova, T., Impavido, G., and Pallares-Miralles, M. An assessment of reform options for the public service pension fund in Uganda. Tech. rep., World Bank Policy Research Working Paper No. 4091, 2006.
• [6] Bukuluki, P., Mukuye, R., Mubiru, J. B., and Namuddu, J. Social protection and social work in Uganda. In Handbook of Social Work and Social Develpment in Africa, M. Gray, Ed. Routledge, 2016, pp. 256–285.
• [7] Cariño, David, R., Kent, T., Myers, David, H., Stacy, C., Sylvanus, M., Turner, Andrew, L., Watanabe, K., and Ziemba, William, T. The Russell-Yasuda Kasai model: An asset/liability model for a Japanese insurance company using multistage stochastic programming. Interfaces 24, 1 (1994), 29–49.
• [8] Chiu, M. C., and Li, D. Asset and liability management under a continuous-time mean–variance optimization framework. Insurance: Mathematics and Economics 39, 3 (2006), 330–355.
• [9] Consigli, G., and Dempster, M. A. H. Dynamic stochastic programmingfor asset liability management. Annals of Operations Research 81 (1998), 131–162.
• [10] Consiglio, A., Cocco, F., and Zenios, S. A. Asset and liability modelling for participating policies with guarantees. European Journal of Operational Research 186, 1 (2008), 380–404.
• [11] Dert, C. Asset Liability Management for Pension Funds: A Multistage Chance Constrained Programming Approach. Ph.D. thesis, Erasmus University Rotterdam, 1995.
• [12] Drijver, S. J. Asset liability management for pension funds using multistage mixed-integer stochastic programming. Ph.D. thesis, niversity of Groningen, 2005.
• [13] Dupačová, J., and Polívka, J. Asset-liability management for Czech pension funds using stochastic programming. Annals of Operations Research 165, 1 (2009), 5–28.
• [14] Geyer, A., and Ziemba, W. T. The Innovest Austrian pension pund financial planning model InnoALM. Operations Research 56, 4 (2008), 797–810.
• [15] Gruber, J., and Wise, D. A. Social Security and Retirement Around the World. University of Chicago Press, 2008.
• [16] Haneveld, W. K. K., Streutker, M. H., and Van Der Vlerk, M. H. An ALM model for pension funds using integrated chance constraints. Annals of Operations Research 177, 1 (2010), 47–62.
• [17] Hibiki, N. Multi-period stochastic optimization models for dynamic asset allocation. Journal of Banking & Finance 30, 2 (2006), 365–390.
• [18] Hilli, P., Koivu, M., Pennanen, T., and Ranne, A. A stochastic programming model for asset liability management of a Finnish pension company. Annals of Operations Research 52, 1 (2007), 115–139.
• [19] John, A., Larsson, T., Singull, M., and Mushi, A. Asset liability management for Tanzania pension funds by stochastic programming. Afrika Statistika 13, 3 (2018), 1733–1758.
• [20] Kamukama, M. Adopting the Twin Peaks Model as a Consumer Protection Mechanism in the Financial Sector: The Ugandan Perspective. PhD thesis, University of the Western Cape, 2015.
• [21] Kouwenberg, R. Scenario generation and stochastic programming models for asset liability management. European Journal of Operational Research 134, 2 (2001), 279–292.
• [22] Mukalazi, H., Larsson, T., Kasozi, J., and Mayambala, F. Asset liability management for the parliamentary pension cheme of Uganda by stochastic programming. Afrika Statistika 16, 2 (2021), 2689–2715.
• [23] Mulvey, J. M., Rosenbaum, D. P., and Shetty, B. Strategic financial risk management and operations research. European Journal of Operational Research 97, 1 (1997), 1–16.
• [24] Nzabona, A., Ntozi, J., and Rutaremwa, G. Loneliness among older persons in Uganda: examining social, economic and demographic risk factors. Ageing and Society 36, 4 (2016), 860–888.
• [25] Schwarz, A. Old Age Security and Social Pensions. The World Bank, 2003.
• [26] Shapiro, A., Dentcheva, D., and Ruszczyński, A. Lectures on stochastic programming: modeling and theory. SIAM, 2009.
• [27] Yu, L., Wang, S., Wu, Y., and Lai, K. K. A dynamic stochastic programming model for bond portfolio management. In Computational Science - ICCS 2004. Lecture Notes in Computers Science vol. 3039 (2004), M. Bubak, G. D. van Albada, P. M. A. Sloot, and J. Dongarra, Eds., Springer, pp. 876–883.
• [28] Yu, L.-Y., Ji, X.-D., and Wang, S.-Y. Stochastic programming models in financial optimization: A survey. AMO – Advanced Modeling and Optimization 5, 1 (2003).

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).