IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/wp01988.html
   My bibliography  Save this paper

A Stochastic Linear Programming Model for Asset Liability Management: The Case of an Indian Insurance Company

Author

Listed:
  • Garg Ankur
  • Tiwari Apoorva
  • Dutta, Goutam
  • Basu Shankarshan

Abstract

Asset - Liability management is one of the most critical tasks for any financial institution for determining its cushion against the risk and the net returns. The problem of asset liability management for an insurance company requires matching the cash inflows from premium collections and investment income with the cash outflows due to casualty and maturity claims. Thus, what is required is a prudent investment strategy such that the returns earned on the assets match the liability claims at all points of time in future. Conventionally, the asset allocation has been done using the Mean Variance approach due to Markowitz (1952, 1959). While such a strategy ensures that the asset value always match or are greater than the liability for the next year, it does not maximise the net worth of the firm nor does it take care of all the cash inflows and outflows over a long term period. A stochastic linear programming model (on the lines of Pirbhai, 2004) maximises the net worth of the firm and also takes care of the uncertainties. While there are instances of stochastic linear programming being applied for ALM in financial institutions in developed markets, no such practical application has been reported in this area in Indian context as yet. In this paper, we describe the development of a multi stage stochastic linear programming model for insurance companies. The multi-stage stochastic linear programming model was developed on the modelling language AMPL (Fourer, 2002).

Suggested Citation

  • Garg Ankur & Tiwari Apoorva & Dutta, Goutam & Basu Shankarshan, 2006. "A Stochastic Linear Programming Model for Asset Liability Management: The Case of an Indian Insurance Company," IIMA Working Papers WP2006-10-08, Indian Institute of Management Ahmedabad, Research and Publication Department.
  • Handle: RePEc:iim:iimawp:wp01988
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/2006-10-08_gdutta.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. G. Consigli & M. Dempster, 1998. "Dynamic stochastic programmingfor asset-liability management," Annals of Operations Research, Springer, vol. 81(0), pages 131-162, June.
    3. Yehuda Kahane, 1977. "Determination of the Product Mix and the Business Policy of an Insurance Company--A Portfolio Approach," Management Science, INFORMS, vol. 23(10), pages 1060-1069, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hong‐Chih Huang, 2010. "Optimal Multiperiod Asset Allocation: Matching Assets to Liabilities in a Discrete Model," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(2), pages 451-472, June.
    2. Terho, Harri & Halinen, Aino, 2007. "Customer portfolio analysis practices in different exchange contexts," Journal of Business Research, Elsevier, vol. 60(7), pages 720-730, July.
    3. Gaivoronski, Alexei A. & Krylov, Sergiy & van der Wijst, Nico, 2005. "Optimal portfolio selection and dynamic benchmark tracking," European Journal of Operational Research, Elsevier, vol. 163(1), pages 115-131, May.
    4. Das, Sanjiv R. & Ostrov, Daniel & Radhakrishnan, Anand & Srivastav, Deep, 2022. "Dynamic optimization for multi-goals wealth management," Journal of Banking & Finance, Elsevier, vol. 140(C).
    5. Li, S. X., 1995. "An insurance and investment portfolio model using chance constrained programming," Omega, Elsevier, vol. 23(5), pages 577-585, October.
    6. Maurer, Raimond H., 2003. "Institutional investors in Germany: Insurance companies and investment funds," CFS Working Paper Series 2003/14, Center for Financial Studies (CFS).
    7. Huang, Zhimin & Li, Susan X., 1996. "Dominance stochastic models in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 95(2), pages 390-403, December.
    8. Li, Susan X. & Huang, Zhimin, 1996. "Determination of the portfolio selection for a property-liability insurance company," European Journal of Operational Research, Elsevier, vol. 88(2), pages 257-268, January.
    9. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    10. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    11. Pichler, Anton & Poledna, Sebastian & Thurner, Stefan, 2021. "Systemic risk-efficient asset allocations: Minimization of systemic risk as a network optimization problem," Journal of Financial Stability, Elsevier, vol. 52(C).
    12. Peter A. Abken & Milind M. Shrikhande, 1997. "The role of currency derivatives in internationally diversified portfolios," Economic Review, Federal Reserve Bank of Atlanta, vol. 82(Q 3), pages 34-59.
    13. Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2018. "A Big data analytical framework for portfolio optimization," Papers 1811.07188, arXiv.org, revised Nov 2018.
    14. Leonard J. Mirman & Egas M. Salgueiro & Marc Santugini, 2013. "Integrating Real and Financial Decisions of the Firm," Cahiers de recherche 1333, CIRPEE.
    15. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    16. Andriosopoulos, Kostas & Nomikos, Nikos, 2014. "Performance replication of the Spot Energy Index with optimal equity portfolio selection: Evidence from the UK, US and Brazilian markets," European Journal of Operational Research, Elsevier, vol. 234(2), pages 571-582.
    17. Raffestin, Louis, 2014. "Diversification and systemic risk," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 85-106.
    18. Sridhar, Shrihari & Naik, Prasad A. & Kelkar, Ajay, 2017. "Metrics unreliability and marketing overspending," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 761-779.
    19. Vithayasrichareon, Peerapat & MacGill, Iain F., 2013. "Assessing the value of wind generation in future carbon constrained electricity industries," Energy Policy, Elsevier, vol. 53(C), pages 400-412.
    20. Gruber, Lutz F. & West, Mike, 2017. "Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear models," Econometrics and Statistics, Elsevier, vol. 3(C), pages 3-22.

    More about this item

    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:iim:iimawp:wp01988. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.