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Strategic Asset Allocation Under a Fractional Hidden Markov Model

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  • Robert J. Elliott

    (University of Adelaide
    University of Calgary
    University of South Australia)

  • Tak Kuen Siu

    (City University London
    Macquarie University)

Abstract

Strategic asset allocation is discussed in a discrete-time economy, where the rates of return from asset classes are explained in terms of some observable and hidden factors. We extend the existing models by incorporating long-term memory in the rates of return and observable economic factors, which have been documented in the empirical literature. Hidden factors are described by a discrete-time, finite-state, hidden Markov chain noisily observed in a fractional Gaussian process. The strategic asset allocation problem is discussed in a mean-variance utility framework. Filtering and parameter estimation are also considered in the hybrid model.

Suggested Citation

  • Robert J. Elliott & Tak Kuen Siu, 2014. "Strategic Asset Allocation Under a Fractional Hidden Markov Model," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 609-626, September.
    • Handle: RePEc:spr:metcap:v:16:y:2014:i:3:d:10.1007_s11009-012-9318-3
    DOI: 10.1007/s11009-012-9318-3
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    References listed on IDEAS

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    Cited by:

    1. Zhu, Dong-Mei & Lu, Jiejun & Ching, Wai-Ki & Siu, Tak-Kuen, 2017. "Discrete-time optimal asset allocation under Higher-Order Hidden Markov Model," Economic Modelling, Elsevier, vol. 66(C), pages 223-232.
    2. Thuener Silva & Davi Valladão & Tito Homem-de-Mello, 2021. "A data-driven approach for a class of stochastic dynamic optimization problems," Computational Optimization and Applications, Springer, vol. 80(3), pages 687-729, December.
    3. Davi Valladão & Thuener Silva & Marcus Poggi, 2019. "Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns," Annals of Operations Research, Springer, vol. 282(1), pages 379-405, November.

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