Operations Research
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OPERATIONS RESEARCH
Vol. 56, No. 4, July-August 2008, pp. 797-810
DOI: 10.1287/opre.1080.0564
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The Innovest Austrian Pension Fund Financial Planning Model InnoALM

Alois Geyer, William T. Ziemba

University of Economics and Vienna Graduate School of Finance, Vienna, Austria
Sauder School of Business, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2, and Visiting Professor, Mathematical Institute, Oxford University, Oxford, United Kingdom 0X1 3LB, and ICMA Centre, University of Reading, Reading, United Kingdom RG6 6BA

alois.geyer{at}wu-wien.ac.at
wtzimi{at}mac.com

This paper describes the financial planning model InnoALM we developed at Innovest for the Austrian pension fund of the electronics firm Siemens. The model uses a multiperiod stochastic linear programming framework with a flexible number of time periods of varying length. Uncertainty is modeled using multiperiod discrete probability scenarios for random return and other model parameters. The correlations across asset classes, of bonds, stocks, cash, and other financial instruments, are state dependent using multiple correlation matrices that correspond to differing market conditions. This feature allows InnoALM to anticipate and react to severe as well as normal market conditions. Austrian pension law and policy considerations can be modeled as constraints in the optimization. The concave risk-averse preference function is to maximize the expected present value of terminal wealth at the specified horizon net of expected discounted convex (piecewise-linear) penalty costs for wealth and benchmark targets in each decision period. InnoALM has a user interface that provides visualization of key model outputs, the effect of input changes, growing pension benefits from increased deterministic wealth target violations, stochastic benchmark targets, security reserves, policy changes, etc. The solution process using the IBM OSL stochastic programming code is fast enough to generate virtually online decisions and results and allows for easy interaction of the user with the model to improve pension fund performance. The model has been used since 2000 for Siemens Austria, Siemens worldwide, and to evaluate possible pension fund regulation changes in Austria.

Subject classifications: scenarios; correlation matrices; pension fund planning; stochastic linear programming.
History: Received July 2003; revision received March 2007; accepted March 2007.







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