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Optimal Multiperiod Asset Allocation: Matching Assets to Liabilities in a Discrete Model

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  • Hong‐Chih Huang

Abstract

Investment and risk control are becoming increasingly important for financial institutions. Asset allocation provides a fundamental investing principle to manage the risk and return trade‐off in financial markets. This article proposes a general formulation of a first approximation of multiperiod asset allocation modeling for institutions that invest to meet the target payment structures of a long‐term liability. By addressing the shortcomings of both single‐period models and the single‐point forecast of the mean variance approach, this article derives explicit formulae for optimal asset allocations, taking into account possible future realizations in a multiperiod discrete time model.

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  • 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.
  • Handle: RePEc:bla:jrinsu:v:77:y:2010:i:2:p:451-472
    DOI: 10.1111/j.1539-6975.2009.01350.x
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    2. Peter A. Forsyth & George Labahn, 2017. "$\epsilon$-Monotone Fourier Methods for Optimal Stochastic Control in Finance," Papers 1710.08450, arXiv.org, revised Apr 2018.
    3. Huang, Hong-Chih & Lee, Yung-Tsung, 2020. "A study of the differences among representative investment strategies," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 131-149.
    4. Tang, Mei-Ling & Chen, Son-Nan & Lai, Gene C. & Wu, Ting-Pin, 2018. "Asset allocation for a DC pension fund under stochastic interest rates and inflation-protected guarantee," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 87-104.

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