Stopping Time Decomposition

Stopping Time Decomposition is a mathematical framework in stochastic process theory that decomposes a stopping time into a predictable and a totally inaccessible component, thereby characterizing the structure of random times with respect to the underlying filtration.

15

Publications

655

Citations

21

Authors

11

Institutions

Publications per year

2017–2026

2

Authors

21

  1. MJ
    Marius Junge

    University of Illinois Urbana-Champaign, United States

    1 publications · 10 citations

    1

    h-index

  2. JP
    Jeffrey Pai

    University of Manitoba, Canada

    1 publications · 15 citations

    1

    h-index

  3. FÁ
    Fernando Álvarez

    Institut Jean-Pierre Bourgin, France

    1 publications · 17 citations

    1

    h-index

  4. YC
    Yu Cheng

    University of Wisconsin–Madison, United States

    1 publications · 15 citations

    1

    h-index

  5. CK
    Constantinos Kardaras

    London School of Economics and Political Science, United Kingdom

    1 publications · 12 citations

    1

    h-index

1–5 of 21

Venues

  1. Probability Theory and Related Fields

    2 publications · 37 citations

    2

    h-index

  2. The Annals of Probability

    2 publications · 175 citations

    2

    h-index

  3. The Annals of Applied Probability

    1 publications · 12 citations

    1

    h-index

  4. Insurance Mathematics and Economics

    1 publications · 15 citations

    1

    h-index

  5. Advances in Mathematics

    1 publications · 159 citations

    1

    h-index

1–5