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Optimization with Performance-Attribution Constraints

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

How well a portfolio performs is of primary concern for investors and governs investor confidence in the portfolio’s management. Attribution analysis provides measures for how well a portfolio is being managed. While performance-attribution measures have been used traditionally as a diagnostic tool, this chapter introduces the recent development to include these measures as constraints in portfolio optimization. Two such measures, asset allocation and the selection effect, are used to constrain conditional value-at-risk optimization of the domestic REIT portfolio under historical and dynamic optimization. The results are analyzed in terms of price and reward-to-risk performance measures. Performance improvement is then characterized in terms of the attribution measure used as the constraint, the optimization method, and the level of turnover constraint.

Suggested Citation

  • W. Brent Lindquist & Svetlozar T. Rachev & Yuan Hu & Abootaleb Shirvani, 2022. "Optimization with Performance-Attribution Constraints," Dynamic Modeling and Econometrics in Economics and Finance, in: Advanced REIT Portfolio Optimization, chapter 0, pages 181-196, Springer.
    • Handle: RePEc:spr:dymchp:978-3-031-15286-3_11
    DOI: 10.1007/978-3-031-15286-3_11
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    Cited by:

    1. Yi Deng & Ziyi Mao & Jinling Huang & Faling Yan & Shenghai Han & Anqi Li, 2022. "Spatial Patterns of Natural Protected Areas and Construction of Protected Area Groups in Guangdong Province," IJERPH, MDPI, vol. 19(22), pages 1-25, November.
    2. Shaobo Liu & Yiting Xia & Yifeng Ji & Wenbo Lai & Jiang Li & Yicheng Yin & Jialing Qi & Yating Chang & Hao Sun, 2023. "Balancing Urban Expansion and Ecological Connectivity through Ecological Network Optimization—A Case Study of ChangSha County," Land, MDPI, vol. 12(7), pages 1-21, July.

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