Cross-sectional Return Analysis

Cross-Sectional Return Analysis is a quantitative method in security analysis that examines the variation in asset returns across a set of securities at a single point in time to identify systematic risk factors, mispricing, or predictive anomalies distinct from time-series return patterns.

276

Publications

53.3K

Citations

504

Authors

343

Institutions

Publications per year

2017–2026

75

Authors

504

  1. AY
    Andrew Y. Chen

    Federal Reserve Board of Governors, United States

    6 publications · 539 citations

    6

    h-index

  2. CR
    Campbell R. Harvey

    Duke University, United States

    6 publications · 3.6K citations

    6

    h-index

  3. TG
    Turan G. Bali

    Georgetown University, United States

    6 publications · 1.3K citations

    6

    h-index

  4. TZ
    Tom Zimmermann

    University of Cologne, Germany

    6 publications · 540 citations

    6

    h-index

  5. NC
    Nusret Cakici

    Fordham University, United States

    5 publications · 971 citations

    5

    h-index

1–5 of 504

Venues

  1. The Journal of Finance

    26 publications · 32.7K citations

    25

    h-index

  2. SSRN Electronic Journal

    Repository · 49 publications · 2.4K citations

    25

    h-index

  3. Review of Financial Studies

    14 publications · 5K citations

    14

    h-index

  4. Journal of Financial and Quantitative Analysis

    JFQA · 11 publications · 1.9K citations

    11

    h-index

  5. Journal of Financial Economics

    10 publications · 2.3K citations

    10

    h-index

1–5