Portfolio optimization under lrisk measure

X. Cai, K. L. Teo, Xiaoqi Yang, X. Y. Zhou

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

3 Citations (Scopus)


In this paper, a new model for portfolio selection is introduced to address the situation where a risk averse investor wants to minimize the maximum individual risk among assets to be invested. The model uses an l∞function as a risk aversion measure. This differs from previous studies where either an l2function or an l1function is suggested, which may not model the concern of very cautious investors properly. We formulate our problem as a bi-criteria piecewise linear program, where one criterion is to minimize the l∞risk function while the other is to maximize the total expected return. This bi-criteria optimization problem is converted into an equivalent scalarized problem with a single combined criterion. An interesting finding is that an optimal solution to the scalarized optimization problem can be derived analytically. The solution exhibits a simple structure, which selects successively assets to be invested in accordance with the ratio of the difference in their return rates to their risks.
Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Decision and Control
Number of pages6
Publication statusPublished - 1 Dec 1996
Externally publishedYes
EventProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4) - Kobe, Japan
Duration: 11 Dec 199613 Dec 1996


ConferenceProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

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