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Stochastic Programming pp 257–275Cite as

Multistage Financial Planning Models: Integrating Stochastic Programs and Policy Simulators

Part of the International Series in Operations Research & Management Science book series (ISOR,volume 150)

Abstract

This chapter reviews multistage financial planning models, with a focus on practical approaches for optimizing investors´ performance over time. We discuss two major frameworks for constructing financial planning models: (1) policy rule simulation and optimization and (2) multistage stochastic programming. We advocate an integrated approach, in which a stylized stochastic program helps the investor discover robust decision/policy rules. In the second stage, the policy optimizer compares policy rules as well as provides additional information about future investment performance. To illustrate benefits, we apply the dual strategy to the defined benefit pension plans in the USA

Keywords

  • Stochastic Program
  • Policy Rule
  • Momentum Strategy
  • Investment Performance
  • Dual Strategy

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 12.1
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Fig. 12.6

Notes

  1. 1.

    The advantages of the equal weighted S&P 500 index is partially due to rebalancing gains and partially due to the higher performance of midsize companies over the discussed period.

References

  • Arbeleche, S., Dempster, M.A.H., Medova, E.A., Thompson, G.W.P., Villaverde, M.: Portfolio Management for Pension Funds, vol. 2690. Springer, Berlin (2003)

    Google Scholar 

  • Bertsekas, D., Tsitsiklis, J.: Neuro-Dynamic Programming. Athena Scientific, Belmont, MA (1996)

    Google Scholar 

  • Boender, G.C.E., van Aalst, P.C., Heemskerk F.: Modelling and management of assets and liabilities of pension plans in the Netherlands, in w. In: Ziemba, T., Mulvey, J.M. (eds.) Worldwide Asset and Liability Modeling, pp. 561–580. Cambridge University Press, UK (1998)

    Google Scholar 

  • Campbell, J.Y., Viceira, L.M.: Strategic Asset Allocation. Oxford University Press, New York, NY (2002)

    CrossRef  Google Scholar 

  • Cariño, D.R., Kent, T., Myers, D.H., Stacy, C., Sylvanus, M., Turner, A., Watanabe, K., Ziemba, W.: The Russell-Yasuda Kasai model: An asset/liability model for a Japanese insurance company using multistage stochastic programming. Interfaces 24(29), 29–49 (1994)

    CrossRef  Google Scholar 

  • Chan, L.K.C., Jegadeesh, N., Lakonishok, J.: Momentum strategies. J. Finance 51(5), 1681–1713 (1996)

    CrossRef  Google Scholar 

  • Cleary, S., Inglis, M.: Momentum in Canadian stock returns. Revue Canadienne Des Sciences De L’Administration 15(3), 279–291 (1998)

    CrossRef  Google Scholar 

  • Consigli, G., Dempster, M.A.H.: Dynamic stochastic programming for asset-liability management. Ann. Oper. Res. 81, 131–162 (1998)

    CrossRef  MathSciNet  MATH  Google Scholar 

  • Dantzig, G.B., Infanger, G.: Multi-stage stochastic linear programs for portfolio optimization. Ann. Oper. Res. 45, 59–76 (1993)

    CrossRef  MathSciNet  MATH  Google Scholar 

  • De Bondt, W.F.M., Thaler, R.: Does stock market overreact? J. Finance 40(3), 793–805 (1985)

    CrossRef  Google Scholar 

  • De Bondt, W.F.M., Thaler, R.: Further evidence on investor overreaction and stock market seasonality. J. Finance 42(3), 557–581 (1987)

    CrossRef  Google Scholar 

  • Demir, I., Muthuswamy, J., Walter, T.: Momentum returns in Australian equities: The influences of size, risk, liquidity and return computation. Pac.-Basin Finance J. 12, 143–158 (2004)

    CrossRef  Google Scholar 

  • Dempster, M.A.H., Germano, M., Medova, E.A., Rietbergen, M.I., Sandrini, F., Scrowston, M.: Managing guarantees. J. Portfolio Manage. 32, 51–61 (2006)

    CrossRef  Google Scholar 

  • Dert, C.L.: Asset liability management for pension funds. PhD thesis, Erasmus University, Rotterdam, Netherlands (1995)

    Google Scholar 

  • Fabozzi, F.J., Focardi, S., Jonas, C.: Can modeling help deal with the pension funding crisis? Working paper, The Intertek Group (2004)

    Google Scholar 

  • Fernholz, R.: Stochastic Portfolio Theory. Springer, New York, NY (2002)

    MATH  Google Scholar 

  • Fernholz, R., Shay, B.: Stochastic portfolio theory and stock market equilibrium. J. Finance 37(2), 615–624 (1982)

    CrossRef  Google Scholar 

  • George, T.J., Hwang, C.: The 52-week high and momentum investing. J. Finance 59(5), 2145–2176 (2004)

    CrossRef  Google Scholar 

  • Geyer, A., Herold, W., Kontriner, K., Ziemba, W.T.: The innovest Austrian pension fund financial planning model innoALM. Working paper, University of British Columbia, Vancouver, BC, Canada (2005)

    Google Scholar 

  • Hilli, P., Koivu, M., Pennanen T., Ranne, A.: A stochastic programming model for asset liability management of a Finnish pension company. Annals of Operations Research 152(1), 115–139 (2007)

    CrossRef  MathSciNet  MATH  Google Scholar 

  • Infanger, G.: Planning Under Uncertainty - Solving Large-Scale Stochastic Linear Programs. The Scientific Press Series, Boyd & Fraser San Francisco, CA (1994)

    MATH  Google Scholar 

  • Jegadeesh, N.: Evidence of predictable behavior of security returns. J. Finance 45(3), 881–898 (1990)

    CrossRef  Google Scholar 

  • Jegadeesh, N., Titman, S.: Returns to buying winners and selling losers: Implications for stock market efficiency. J. Finance 48(1), 65–91 (1993)

    CrossRef  Google Scholar 

  • Kang, J., Liu, M., Ni, S.X.: Contrarian and momentum strategies in the china stock market: 1993–2000. Pac.-Basin Finance J. 10, 243–265 (2002)

    CrossRef  Google Scholar 

  • Kouwenberg, R., Zenios, S.A.: Stochastic programming models for asset liability management. Working Paper 01-01, HERMES Center on Computational Finance, & Economics, University of Cyprus, Nicosia, Cyprus (2001)

    Google Scholar 

  • Lehmann, B.N.: Fads, martingales, and market efficiency. Quart. J. Econ. 105(1), 1–28 (1990)

    CrossRef  Google Scholar 

  • Luenberger, D.: Investment Science. Oxford University Press, New York, NY (1998)

    Google Scholar 

  • Merton, R.C.: Lifetime portfolio selection under uncertainty: The continuous-time case. Rev. Econ. Stat. 51(3), 247–257 (1969)

    CrossRef  Google Scholar 

  • Merton, R.C.: An intertemporal capital asset pricing model. Econometrica 41(5), 867–887 (1973)

    CrossRef  MathSciNet  MATH  Google Scholar 

  • Mulvey, J.M.: Multi-period stochastic optimization models for long-term investors. In: Avellaneda, M., (ed.) Quantitative Analysis in Financial Markets, vol. 3. World Scientific, Singapore (2000)

    Google Scholar 

  • Mulvey, J.M.: Essential portfolio theory. A rydex investment white paper, Princeton University, Princeton, NJ (2005)

    Google Scholar 

  • Mulvey, J.M., Kim, W.C.: Constructing a portfolio of industry-level momentum strategies across global equity markets. Princeton university report, Department of OR and Financial Engineering, Princeton University, Princeton, NJ (2007)

    Google Scholar 

  • Mulvey, J.M., Kim, W.C.: The role of alternative assets for optimal portfolio construction. Wiley, New York, NY (2008) referenced 2007 but appeared in 2008

    Google Scholar 

  • Mulvey, J.M., Simsek, K.D.: Rebalancing strategies for long-term investors. In: Rustem, B., Kontoghiorghes, E.J., Siokos, S. (eds.) Computational Methods in Decision Making, Economics and Finance: Optimization Models. Kluwer, Netherlands (2002)

    Google Scholar 

  • Mulvey, J.M., Ziemba, W.T.: Asset and liability management systems for long-term investors. In: Ziemba, W.T., Mulvey, J.M. (eds.) Worldwide Asset and Liability Modeling. Cambridge University Press, Cambridge (1998)

    Google Scholar 

  • Mulvey, J.M., Gould, G., Morgan, C.: An asset and liability management system for towers perrin-tillinghast. Interfaces 30, 96–114 (2000)

    CrossRef  Google Scholar 

  • Mulvey, J.M., Pauling, B., Madey, R.E.: Advantages of multiperiod portfolio models. J. Portfolio Manage. 29, 35–45 (2003a)

    CrossRef  Google Scholar 

  • Mulvey, J.M., Simsek, K.D., Pauling, B.: A stochastic network approach for integrated pension and corporate financial planning. In: Nagurney, A. (ed.) Innovations in Financial and Economic Networks. Edward Elgar, UK (2003b)

    Google Scholar 

  • Mulvey, J.M., Kaul, S.S.N., Simsek, K.D.: Evaluating a trend-following commodity index for multi-period asset allocation. J. Alter. Invest. 7(1), 54–69 (2004a)

    CrossRef  Google Scholar 

  • Mulvey, J.M., Simsek, K.D., Zhang, Z., Holmer, M.: Preliminary analysis of defined-benefit pension plans. Princeton university report, Department of OR and Financial Engineering, Princeton University, Princeton, NJ (2004b)

    Google Scholar 

  • Mulvey, J.M., Ural, C., Zhang, Z.: Optimizing performance for long-term investors: Wide diversification and overlay strategies. Princeton university report, Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ (2006)

    Google Scholar 

  • Peskin, M.W.: Asset allocation and funding policy for corporate-sponsored defined-benefit pension plans. J. Portfolio Manage. 23(2), 66–73 (1997)

    CrossRef  MathSciNet  Google Scholar 

  • Pflug, G.C., Swietanowski, A.: Asset-Liability Optimization for Pension Fund Management. Operations Research Proceedings, Springer Verlag pp. 124–135 (2000)

    Google Scholar 

  • Pflug, G.C., Dockner, E., Swietanowski, A., Moritsch, H.: The aurora financial management system: Model and parallel implementation design. Ann. Oper. Res. 99, 189–206 (2000)

    CrossRef  MathSciNet  MATH  Google Scholar 

  • Powell, W.B.: Approximate Dynamic Programming: Solving the Curses of Dimensionality. Wiley, Hoboken, NJ (2006)

    Google Scholar 

  • Rouwenhorst, K.G.: International momentum strategies. J. Finance 53(1), 267–284 (1998)

    CrossRef  Google Scholar 

  • Rudolf, M., Ziemba, W.T.: Intertemporal asset-liability management. J. Econ. Dynam. Control 28(4), 975–990 (2004)

    CrossRef  MathSciNet  Google Scholar 

  • Samuelson, P.A.: Lifetime portfolio selection by dynamic stochastic programming. Rev. Econ. Stat. 51(3), 239–246 (1969)

    CrossRef  Google Scholar 

  • Sutton, R., Barto, A.: Reinforcement Learning. The MIT Press, Cambridge, MA (1998)

    Google Scholar 

  • White, D.A., Sofge, D.A. (eds.) Handbook of Intelligent Control. Von Nostrand Reinhold, New York, NY (1992)

    Google Scholar 

  • Zenios, S.A., Ziemba, W.T. (eds.) Handbook of Asset and Liability Management. Handbooks in Finance vol. 1. Elsevier, Amsterdam (2006)

    Google Scholar 

  • Zenios, S.A., Ziemba, W.T. (eds.) Handbook of Asset and Liability Management. Handbooks in Finance vol. 2. Elsevier, Amsterdam (2007)

    Google Scholar 

  • Zhang, Z.: Stochastic optimization for enterprise risk management. PhD thesis, Princeton, NJ (2006)

    Google Scholar 

  • Ziemba, W.T., Mulvey, J.M. (eds.) Worldwide Asset and Liability Modeling. Cambridge University Press, Cambridge (1998)

    MATH  Google Scholar 

  • Ziemba, W.T.: The Stochastic Programming Approach to Asset-Liability and Wealth Management. AIMR-Blackwell Charlottesville, VA (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ, 08544, USA

    John M. Mulvey

  2. Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea

    Woo Chang Kim

Authors
  1. John M. Mulvey
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  2. Woo Chang Kim
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Correspondence to John M. Mulvey .

Editor information

Editors and Affiliations

  1. Dept. Management Science & Engineering, Stanford University, Stanford, 94305, California, USA

    Gerd Infanger

Appendix

Appendix

Fig. 12.7
figure 7

Performance of dynamic diversification portfolio. Dynamic diversification portfolio is an equally weighted fixed mix portfolio of 30 momentum strategies—five regions, six settings. Each number next to a point on the line represents leverage; 3-month US T-bill is used. The sample period is 1980 through 2006

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Mulvey, J.M., Kim, W.C. (2010). Multistage Financial Planning Models: Integrating Stochastic Programs and Policy Simulators. In: Infanger, G. (eds) Stochastic Programming. International Series in Operations Research & Management Science, vol 150. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1642-6_12

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