IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v35y2011i1p182-192.html
   My bibliography  Save this article

Asset-liability management under time-varying investment opportunities

Author

Listed:
  • Ferstl, Robert
  • Weissensteiner, Alex

Abstract

Stochastic linear programming is a suitable numerical approach for solving practical asset-liability management problems. In this paper, we consider a multi-stage setting under time-varying investment opportunities and propose a decomposition of the benefits in dynamic re-allocation and predictability effects. We use a first-order unrestricted vector autoregressive process to model asset returns and state variables and include, in addition to equity returns and dividend-price ratios, Nelson/Siegel parameters to account for the evolution of the yield curve. The objective is to minimize the Conditional Value at Risk of shareholder value, i.e., the difference between the mark-to-market value of (financial) assets and the present value of future liabilities.

Suggested Citation

  • Ferstl, Robert & Weissensteiner, Alex, 2011. "Asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 182-192, January.
  • Handle: RePEc:eee:jbfina:v:35:y:2011:i:1:p:182-192
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-4266(10)00294-3
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, pages 1455-1508.
    3. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 433-495.
    4. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    5. Campbell, John Y. & Chan, Yeung Lewis & Viceira, Luis M., 2003. "A multivariate model of strategic asset allocation," Journal of Financial Economics, Elsevier, vol. 67(1), pages 41-80, January.
    6. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2008. "Pricing options on scenario trees," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 283-298, February.
    7. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
    8. Campbell, John Y. & Chacko, George & Rodriguez, Jorge & Viceira, Luis M., 2004. "Strategic asset allocation in a continuous-time VAR model," Journal of Economic Dynamics and Control, Elsevier, vol. 28(11), pages 2195-2214, October.
    9. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    10. Wachter, Jessica A., 2002. "Portfolio and Consumption Decisions under Mean-Reverting Returns: An Exact Solution for Complete Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(01), pages 63-91, March.
    11. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    12. Jérôme B. Detemple & René Garcia & Marcel Rindisbacher, 2003. "A Monte Carlo Method for Optimal Portfolios," Journal of Finance, American Finance Association, vol. 58(1), pages 401-446, February.
    13. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    14. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    15. Bertocchi, Marida & Giacometti, Rosella & Zenios, Stavros A., 2005. "Risk factor analysis and portfolio immunization in the corporate bond market," European Journal of Operational Research, Elsevier, vol. 161(2), pages 348-363, March.
    16. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    17. Paul A. Samuelson, 2011. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," World Scientific Book Chapters,in: THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 31, pages 465-472 World Scientific Publishing Co. Pte. Ltd..
    18. Consiglio, Andrea & Saunders, David & Zenios, Stavros A., 2006. "Asset and liability management for insurance products with minimum guarantees: The UK case," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 645-667, February.
    19. Kessler, Stephan & Scherer, Bernd, 2009. "Varying risk premia in international bond markets," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1361-1375, August.
    20. Canner, Niko & Mankiw, N Gregory & Weil, David N, 1997. "An Asset Allocation Puzzle," American Economic Review, American Economic Association, vol. 87(1), pages 181-191, March.
    21. Ralph S. J. Koijen & Theo E. Nijman & Bas J. M. Werker, 2010. "When Can Life Cycle Investors Benefit from Time-Varying Bond Risk Premia?," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 741-780, February.
    22. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
    23. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
    24. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    25. Kim, Tong Suk & Omberg, Edward, 1996. "Dynamic Nonmyopic Portfolio Behavior," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 141-161.
    26. Brennan, Michael J. & Schwartz, Eduardo S. & Lagnado, Ronald, 1997. "Strategic asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1377-1403, June.
    27. Yihong Xia, 2001. "Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," Journal of Finance, American Finance Association, vol. 56(1), pages 205-246, February.
    28. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March.
    29. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
    30. Mulvey, John M. & Erkan, Hafize G., 2006. "Applying CVaR for decentralized risk management of financial companies," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 627-644, February.
    31. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    32. Dempster, M. A. H. & Germano, M. & Medova, E. A. & Villaverde, M., 2003. "Global Asset Liability Management," British Actuarial Journal, Cambridge University Press, vol. 9(01), pages 137-195, April.
    33. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
    34. Quaranta, Anna Grazia & Zaffaroni, Alberto, 2008. "Robust optimization of conditional value at risk and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2046-2056, October.
    35. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gülpinar, Nalan & Pachamanova, Dessislava, 2013. "A robust optimization approach to asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2031-2041.
    2. Platanakis, Emmanouil & Sutcliffe, Charles, 2016. "Pension scheme redesign and wealth redistribution between the members and sponsor: The USS rule change in October 2011," Insurance: Mathematics and Economics, Elsevier, pages 14-28.
    3. Nalan Gülpınar & Dessislava Pachamanova & Ethem Çanakoğlu, 2016. "A robust asset–liability management framework for investment products with guarantees," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(4), pages 1007-1041, October.
    4. Grzegorz Hałaj, 2016. "Dynamic Balance Sheet Model With Liquidity Risk," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(07), pages 1-37, November.
    5. repec:eee:insuma:v:77:y:2017:i:c:p:177-188 is not listed on IDEAS
    6. Agnieszka Konicz & David Pisinger & Alex Weissensteiner, 2015. "Optimal annuity portfolio under inflation risk," Computational Management Science, Springer, vol. 12(3), pages 461-488, July.
    7. Kourosh Rasmussen & Claus Madsen & Rolf Poulsen, 2014. "Can home-owners benefit from stochastic programming models? A study of mortgage choice in Denmark," Computational Management Science, Springer, vol. 11(1), pages 5-23, January.
    8. Mark Freeman & Ben Groom, 2015. "Using equity premium survey data to estimate future wealth," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 665-693, November.
    9. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.
    10. de Haan, Leo & Kakes, Jan, 2011. "Momentum or contrarian investment strategies: Evidence from Dutch institutional investors," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2245-2251, September.

    More about this item

    Keywords

    Asset-liability management Predictability Stochastic programming Scenario generation VAR process;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:35:y:2011:i:1:p:182-192. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jbf .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.