Pension Fund’s Risk Management Investment Portfolio in Tanzania
Abstract
The study intends to assess the risk exposure of assets from the pension funds investment portfolio and suggest possible solutions of mitigating the risk of severe loss that is likely to occur over a given period of time. The study engaged secondary data of annual return series from five individual assets which are Government Securities (GSs), Fixed Deposits (FDs), Corporate Bonds (CBs), Equities and Real Estates (REs) with the total number of 18 observations. In order to achieve the objectives of the study, the author applied the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model and Cornish-Fisher expansion model for data analysis to calculate Value at Risk (VaR) for individual assets in Pension Funds investment portfolio from the financial year 1998/1999 to 2016/2017. The results from both techniques employed indicated that, Corporate Bonds (CBs) has the highest Value at Risk (VaR) followed by, Fixed Deposits (FDs), Equity, Real Estates and Government Securities (GSs). There were some renovations in the social security industry in Tanzania as among the approaches to combat risk that avails with minimal effects in the operationalization of Pension Funds, therefore the findings of the study are relevant to help pension funds in Tanzania to mitigate the risk of strict loss that is likely to occur in their investment portfolio due to market fluctuations over a given period of time.
Downloads
References
Adam, J., (2016). The Research Journey: Navigating Through Obstacles. Dar es Salaam: Dar es Salaam University Press.
Aktas, O. & Sjostrand, M., (2011). Cornish-Fisher Expansion and Value-at-Risk Method in Application to Risk Management of Large Portfolios. s.l.: Halmstad University.
Andersen, T. T. & Frederiksen, T., (2010). Modeling Value-at-Risk under Normal and Extreme Market Conditions. Copenhagen: Copenhagen Business School, Institute of Finance.
Ansah, A. Y., (2016). Modeling of Pension Fund Using GARCH: Case Study of SSNIT, s.l.: The Department of Mathematics, Kwame Nkrumah University of Science and Tenchnology.
Aydın, K & Korkmaz, T. (2002). Using EWMA and GARCH methods in VaR calculations: Application on ISE-30 Index. In ERC/METU 6. International Conference in Economics (pp. 11-14).
Bollerslev, T.: 1986, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 31, 307ñ327.
Čorkalo, Š. (2011). Comparison of value at risk approaches on a stock portfolio. Croatian Operational Research Review, 2(1), 81-90.
Culp, C. L., Mensik, R. & Neves, A. M. P., (1998). Value at Risk for Asset Managers. Derivatives Quarterly, pp. 21-33.
Engle, R., (2001). GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics. Journal of Economic Perspective, 15(4), pp. 157-168.
Franzen, D., (2010). Managing Investment Risk in Defined Benefit Pension Funds. OECD Working Papers on Insurance and Private Pensions, Issue No. 38, OECD Publishing, pp. 1-58.
Gabrielsen, A., Kirchner, A., Liu, Z., &Zagaglia, P. (2015). Forecasting value-at-risk with time-varying variance, skewness and kurtosis in an exponential weighted moving average framework. Annals of Financial Economics, 10(01), 1550005.
Graham, B. &Dodd, D. L. (2009). Security Analysis: Principles and Technique .6thed.Columbia:McGrawHill.
Grimsley, S., (2003). Government Securities: Definitions, Types and Examples. Study.com. [Online]Availableat: https://study.com [Accessed 2018].
Guidolin, M., (2013). Univariate Volatility Models: ARCH and GARCH. Mypage. didattica. unibocconi. It [Accessed 21st July, 2018].
Hu, L. (2017, October). Research on Stock Returns and Volatility-Based on ARCH-GARCH Model. In 7th International Conference on Management, Education, Information and Control (MEICI 2017) (pp. 181-184). Atlantis Press.
Hurlimann, W., (2014). Market Value-At-Risk: ROM Simulation, Cornish-Fisher Var and Chebyshev-Markov Var Bound. British Journal of Mathematics and Computer Science, 4(13), 1797-1814.
IHS Global Inc., (2013). Eviews 8 User's Guide II. s.l.:s.n.
Inderst, G., (2009). Pension Fund Investment in Infrastructure. OECD Working Papers on Insurance and Private Pensions, 32, 1-45.
Isaka, I. C., (2016). Presentation for Updates on Social Security Reforms. s.l., s.n.
Javed, F., &Mantalos, P. (2013). GARCH-type models and performance of information criteria. Communications in Statistics-Simulation and Computation, 42(8), 1917-1933.
Jensen, J. F. B. & Pedersen, K. R. S., (2013). Portfolio Risk: An Empirical Study to Derive an Asymmetry-Adjusted Risk Estimate. Aarhus, Denmark: Aarhus University.
Jorion, P., (2002). How Informative Are Value at Risk Disclosures?, Irvine: University ofCarlifonia.
Jorion, P., (2003). Financial Risk Manager Handbook. 2nd ed. Hoboken, New Jersey: John Wiley and Sons, Inc.
Kaura, V., (2005). Portfolio Optimisation Using Value at Risk, London, UK: Imperial College London.
Kusiluka, M. M., & Kongela, S. M. (2020). A Case for Real Estate Inclusion in Pension Funds Mixed-Asset Portfolios in Tanzania. Current Urban Studies, 8, 428-445.
Lopez, J. A., (1998). Methods for Evaluating Value-at-Risk Estimates. FRBNY Economic Policy Review, October, pp. 119-124.
Mishkin, F. S., (2004). The Economics of Money, Banking and Finacial Markets. 7th ed. Columbia: Columbia University, Longman Publishers.
Pedraza, A., Fuentes, O., Searle, P., & Stewart, F. (2017). Pension funds and the impact of switching regulation on long-term investment. World Bank Policy Research Working Paper, (8143).
Olivier, C., Manesme, A., & Barthélémy, F. (2012). Cornish-Fisher Expansion for Real Estate Value at Risk. Edinburg, s.n.
Orlando, D. K. & Abbott, M. (1998). Introduction To Value-at-Risk. New York, Society of Actuaries.
Palepu, K. G., Healy, P. M., & Peek, E. (2013). Business Analysis and Valuation: Text and Cases. 3rd IFRS ed. Cambridge Massachusetts: Cengage Learning.
Simon, M. K. & Goes, J., (2013). Assumptions, Limitations, Delimitations, and Scope of the Study. Seattle, Washington.
Simons, K., (2000). The Use of Value at Risk by Institutional Investors. New England Economic Review,pp. 21-30.
Sjö, B., (2011). Estimation and Testing for ARCH and GARCH. https://pdfs.semanticscholar.org[Accessed 24th May, 2018].
Soucik, V., (2002). Finding the true performance of Australian managed funds.Joondalup, Australia: Edith Cowan University.
Stewart, F. (2005). Developments in Pension Fund Risk Management in Selected OECD and Asian Countries. OECD Working Paper on Insurance and Private Pensions.
The United Republic of Tanzania (URT). (2017). Special Bill Supplement to the Special Gazette of the United Republic of Tanzania No. 8A Vol. 98. :http://www.tcme.or.tz[Accessed 20th July, 2018].
Tonks, I., (2005). Chapter 23: Pension Fund Management and Investment Performance. In: Clark & Munnel, eds. The Handbook of Pensions, 456-480.
Veldhuijzen, M. (2014). Optimal investment strategy for pension funds in the new dutch pension contract (Doctoral dissertation, Tilburg University).
Geneva, International Labor Office World Bank (2001). Social Protection Sector Strategy: from safety net to springboard. Washington, World Bank. Retrieved on 25th 2021, from http://www.nssfug.org, at 14:00 hours
