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Recent Developments in Robust Portfolios with a Worst-Case Approach

Author

Listed:
  • Jang Ho Kim

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Woo Chang Kim

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Frank J. Fabozzi

    (EDHEC Business School)

Abstract

Robust models have a major role in portfolio optimization for resolving the sensitivity issue of the classical mean–variance model. In this paper, we survey developments of worst-case optimization while focusing on approaches for constructing robust portfolios. In addition to the robust formulations for the Markowitz model, we review work on deriving robust counterparts for value-at-risk and conditional value-at-risk problems as well as methods for combining uncertainty in factor models. Recent findings on properties of robust portfolios are introduced, and we conclude by presenting our thoughts on future research directions.

Suggested Citation

  • Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    • Handle: RePEc:spr:joptap:v:161:y:2014:i:1:d:10.1007_s10957-013-0329-1
    DOI: 10.1007/s10957-013-0329-1
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    References listed on IDEAS

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