Default Probability Forecasting

Default Probability Forecasting is a financial forecasting method that quantifies the likelihood of a borrower failing to meet debt obligations within a specified time horizon, distinguished from other credit risk models by its focus on predictive accuracy and temporal dynamics of default events.

104

Publications

6.7K

Citations

247

Authors

150

Institutions

Publications per year

2017–2026

37

Authors

247

  1. TS
    Tyler Shumway

    University of Michigan, United States

    3 publications · 2.7K citations

    3

    h-index

  2. ST
    Sreedhar T. Bharath

    Arizona State University, United States

    3 publications · 2.7K citations

    3

    h-index

  3. HK
    Hyeongjun Kim

    Sungkyunkwan University, South Korea

    2 publications · 22 citations

    2

    h-index

  4. HP
    H. Ping Tserng

    National Taiwan University, Taiwan

    2 publications · 63 citations

    2

    h-index

  5. LR
    Lisa R. Goldberg

    University of California, Berkeley, United States

    2 publications · 122 citations

    2

    h-index

1–5 of 247

Venues

  1. SSRN Electronic Journal

    Repository · 16 publications · 788 citations

    15

    h-index

  2. The Journal of Fixed Income

    4 publications · 84 citations

    4

    h-index

  3. The Journal of Credit Risk

    3 publications · 52 citations

    3

    h-index

  4. Expert Systems with Applications

    3 publications · 192 citations

    3

    h-index

  5. Review of Accounting Studies

    2 publications · 208 citations

    2

    h-index

1–5