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Mortality Risk and Real Optimal Asset Allocation for Pension Funds

Author

Listed:
  • Francesco Menoncin

    () (Dipartimento di Scienze Economiche, Università di Brescia, Italy and IRES, Université catholique de Louvain, Louvain-La-Neuve, Belgique)

  • Olivier Scaillet

    (HEC Genève and FAME)

Abstract

We analyze the problem of real optimal asset allocation for a pension fund maximising the expected CRRA utility of its real disposable wealth. The financial horizon of the analysis coincides with the random death time of a representative subscriber. We consider a very general setting where there exists a stochastic investment opportunity set together with stochastic contributions and pensions and we derive a quasi-explicit solution. When the market price of risk is independent of the state variables we are also able to compute a closed-form solution. Numerical simulations provide useful practical guidelines regarding the optimal investment strategy.

Suggested Citation

  • Francesco Menoncin & Olivier Scaillet, 2003. "Mortality Risk and Real Optimal Asset Allocation for Pension Funds," FAME Research Paper Series rp101, International Center for Financial Asset Management and Engineering.
  • Handle: RePEc:fam:rpseri:rp101
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    File URL: http://www.swissfinanceinstitute.ch/rp101.pdf
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    References listed on IDEAS

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    Cited by:

    1. Katarzyna Romaniuk, 2007. "The optimal asset allocation of the main types of pension funds: a unified framework," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(2), pages 113-128, December.

    More about this item

    Keywords

    pension fund; asset allocation; mortality risk; inflation risk;

    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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