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Dynamic Portfolio Optimization: Beyond MPT

In: Advanced REIT Portfolio Optimization

Author

Listed:
  • W. Brent Lindquist

    (Texas Tech University)

  • Svetlozar T. Rachev

    (Texas Tech University)

  • Yuan Hu

    (University of California San Diego)

  • Abootaleb Shirvani

    (Kean University)

Abstract

Optimization based solely on the REIT returns in a historical time window is severely restricted by that set of realized historical returns, leaving the portfolio vulnerable to downturns unseen in the historical data. Dynamic portfolio optimization, which determines portfolio composition using a massive ensemble of return predictions that are statistically consistent with historical returns but include extreme events safeguard against this vulnerability. Dynamic optimization, based upon ARMA-GARCH models with heavy-tailed innovations and non-Gaussian copulas, is developed in this Chapter for mean variance and conditional value-at-risk measures as well as for the Black–Litterman model. Dynamically optimized portfolios comprised of domestic REITs are computed and their performance compared to corresponding portfolios optimized under the classical historical return approach. Fairly dramatic performance improvement is seen under dynamic optimization.

Suggested Citation

  • W. Brent Lindquist & Svetlozar T. Rachev & Yuan Hu & Abootaleb Shirvani, 2022. "Dynamic Portfolio Optimization: Beyond MPT," Dynamic Modeling and Econometrics in Economics and Finance, in: Advanced REIT Portfolio Optimization, chapter 0, pages 93-112, Springer.
    • Handle: RePEc:spr:dymchp:978-3-031-15286-3_7
    DOI: 10.1007/978-3-031-15286-3_7
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    Cited by:

    1. Liu, Yiying & Zhou, Yongbin & Niu, Juanjuan, 2023. "Portfolio optimization: A multi-period model with dynamic risk preference and minimum lots of transaction," Finance Research Letters, Elsevier, vol. 55(PB).

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