Nonlinear Expectations

Nonlinear Expectations is a mathematical framework within the theory of stochastic processes that generalizes classical linear expectations by allowing the expectation operator to satisfy sublinearity or convexity properties, thereby enabling the modeling of uncertainty and risk aversion in the analysis of stopping times.

63

Publications

3.2K

Citations

81

Authors

67

Institutions

Publications per year

2017–2026

9

Authors

81

  1. SP
    Shigē Péng

    Shandong University, China

    10 publications · 996 citations

    10

    h-index

  2. RJ
    Robert J. Elliott

    University of Calgary, Canada

    4 publications · 103 citations

    4

    h-index

  3. SN
    Samuel N. Cohen

    University of Oxford, United Kingdom

    4 publications · 113 citations

    4

    h-index

  4. CZ
    Chao Zhou

    National University of Singapore, Singapore

    3 publications · 86 citations

    3

    h-index

  5. NT
    Nizar Touzi

    École Polytechnique, France

    3 publications · 118 citations

    3

    h-index

1–5 of 81

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 190 citations

    4

    h-index

  2. The Annals of Applied Probability

    4 publications · 206 citations

    4

    h-index

  3. Stochastic Processes and their Applications

    4 publications · 154 citations

    4

    h-index

  4. Stochastic Analysis and Applications

    3 publications · 84 citations

    3

    h-index

  5. Journal of Business and Economic Statistics

    JBES · 3 publications · 284 citations

    3

    h-index

1–5