Nonparametric Risk Estimation

Nonparametric Risk Estimation is a risk estimation method that quantifies potential losses or uncertainties without assuming a specific parametric form for the underlying probability distribution, relying instead on empirical data and distribution-free techniques to model risk.

70

Publications

4.3K

Citations

150

Authors

125

Institutions

Publications per year

2017–2026

11

Variants

Non-parametric Risk Estimation

Authors

150

  1. MG
    Mark G. Low

    University of Pennsylvania, United States

    4 publications · 198 citations

    4

    h-index

  2. JV
    José Valentim Machado Vicente

    Central Bank of Brazil, Brazil

    2 publications · 72 citations

    2

    h-index

  3. TB
    Tine Buch-Kromann

    City, University of London, United Kingdom

    2 publications · 28 citations

    2

    h-index

  4. OS
    Olivier Scaillet

    University of Geneva, Switzerland

    2 publications · 297 citations

    2

    h-index

  5. SJ
    Seok‐Oh Jeong

    Hankuk University of Foreign Studies, South Korea

    2 publications · 61 citations

    2

    h-index

1–5 of 150

Venues

  1. The Annals of Statistics

    6 publications · 511 citations

    6

    h-index

  2. SSRN Electronic Journal

    Repository · 5 publications · 202 citations

    5

    h-index

  3. Journal of Econometrics

    3 publications · 920 citations

    3

    h-index

  4. Theory of Probability and Its Applications

    3 publications · 144 citations

    3

    h-index

  5. Annals of Operations Research

    2 publications · 73 citations

    2

    h-index

1–5