Cvar Optimization

CVaR Optimization is a risk-sensitive decision-making framework that belongs to the class of stochastic optimization methods, distinguished by its focus on minimizing the Conditional Value-at-Risk—a coherent measure of tail risk—thereby prioritizing performance in the worst-case outcomes beyond a specified quantile threshold.

208

Publications

16.3K

Citations

543

Authors

282

Institutions

Publications per year

2017–2026

115

Variants

Conditional Value-at-risk Optimization

Authors

543

  1. SU
    Stan Uryasev

    University of Florida, United States

    6 publications · 7K citations

    6

    h-index

  2. SM
    Shie Mannor

    Technion – Israel Institute of Technology, Israel

    5 publications · 328 citations

    5

    h-index

  3. AT
    Aviv Tamar

    Technion – Israel Institute of Technology, Israel

    5 publications · 328 citations

    5

    h-index

  4. MG
    M. Grazia Speranza

    University of Brescia, Italy

    4 publications · 207 citations

    4

    h-index

  5. SZ
    Shushang Zhu

    Fudan University, China

    4 publications · 779 citations

    4

    h-index

1–5 of 543

Venues

  1. European Journal of Operational Research

    10 publications · 489 citations

    10

    h-index

  2. arXiv (Cornell University)

    Repository · 12 publications · 342 citations

    10

    h-index

  3. International Journal of Production Economics

    7 publications · 412 citations

    7

    h-index

  4. Annals of Operations Research

    7 publications · 269 citations

    7

    h-index

  5. Quantitative Finance

    7 publications · 371 citations

    7

    h-index

1–5