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Asset-liability management under time-varying investment opportunities

  • Ferstl, Robert
  • Weissensteiner, Alex

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.

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Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 35 (2011)
Issue (Month): 1 (January)
Pages: 182-192

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Handle: RePEc:eee:jbfina:v:35:y:2011:i:1:p:182-192
Contact details of provider: Web page: http://www.elsevier.com/locate/jbf

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