Risk-sensitive Value Functions

Risk-Sensitive Value Functions is a mathematical framework in decision theory that extends classical value functions by incorporating preferences over risk through sensitivity parameters, thereby modeling how agents evaluate stochastic outcomes differently based on their risk attitudes.

230

Publications

13.1K

Citations

418

Authors

285

Institutions

Publications per year

2017–2026

43

Authors

418

  1. AB
    Alejandro Balbás

    Universidad Carlos III de Madrid, Spain

    4 publications · 109 citations

    4

    h-index

  2. RB
    Raquel Balbás

    Universidad Carlos III de Madrid, Spain

    4 publications · 109 citations

    4

    h-index

  3. VS
    Vivek S. Borkar

    Tata Institute of Fundamental Research, India

    4 publications · 108 citations

    4

    h-index

  4. PK
    Peter Kischka

    Friedrich Schiller University Jena, Germany

    3 publications · 122 citations

    3

    h-index

  5. RW
    Ruodu Wang

    University of Waterloo, Canada

    3 publications · 113 citations

    3

    h-index

1–5 of 418

Venues

  1. European Journal of Operational Research

    11 publications · 668 citations

    11

    h-index

  2. SSRN Electronic Journal

    Repository · 6 publications · 195 citations

    6

    h-index

  3. Finance and Stochastics

    6 publications · 609 citations

    6

    h-index

  4. Management Science

    6 publications · 624 citations

    6

    h-index

  5. Journal of Risk and Uncertainty

    6 publications · 365 citations

    6

    h-index

1–5