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Asset-Liability Management under time-varying Investment Opportunities

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  • Ferstl, Robert
  • Weissensteiner, Alex

Abstract

In this paper, we propose multi-stage stochastic linear programming for asset-liability management under time-varying investment opportunities. We use a first-order unrestricted vector autoregressive process to model predictability in the asset returns and the state variables, where - additional to equity returns and dividend-price ratios - Nelson/Siegel parameters are included to account for the evolution of the yield curve. As objective function we minimize conditional value at risk of the shareholder value, i.e. the difference between the mark-to-market value of (financial) assets and the present value of future liabilities. Our results indicate strong hedging demands to mitigate interest rate risks.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 15068.

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Date of creation: 05 May 2009
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Handle: RePEc:pra:mprapa:15068

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Keywords: predictability; stochastic programming; scenario generation; VAR process;

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References

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Cited by:
  1. Leo de Haan & Jan Kakes, 2010. "Momentum or Contrarian Investment Strategies:Evidence from Dutch institutional investors," DNB Working Papers, Netherlands Central Bank, Research Department 242, Netherlands Central Bank, Research Department.
  2. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, Elsevier, vol. 35(9), pages 2311-2318, September.
  3. Gülpinar, Nalan & Pachamanova, Dessislava, 2013. "A robust optimization approach to asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, Elsevier, vol. 37(6), pages 2031-2041.

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