Algorithmic Trading Surveillance

Algorithmic Trading Surveillance is a systematic monitoring framework within financial market oversight that specifically detects and analyzes algorithmically generated trading behaviors to identify potential manipulative or non-compliant activities distinct from conventional trading patterns.

20

Publications

595

Citations

58

Authors

35

Institutions

Publications per year

2017–2026

6

Authors

58

  1. LC
    Longbing Cao

    University of Technology Sydney, Australia

    2 publications · 28 citations

    2

    h-index

  2. HA
    Henrique Andrade

    IBM (United States), United States

    2 publications · 32 citations

    2

    h-index

  3. SN
    Senthil Nathan

    IBM Research - India, India

    2 publications · 32 citations

    2

    h-index

  4. YP
    Yoonho Park

    IBM (United States), United States

    2 publications · 32 citations

    2

    h-index

  5. RP
    Richard P. King

    IBM (United States), United States

    2 publications · 32 citations

    2

    h-index

1–5 of 58

Venues

  1. Computer law & security review

    2 publications · 45 citations

    2

    h-index

  2. The Social Science Journal

    1 publications · 11 citations

    1

    h-index

  3. 1

    h-index

  4. Technological Forecasting and Social Change

    1 publications · 147 citations

    1

    h-index

  5. UTS ePRESS (University of Technology Sydney)

    Repository · 1 publications · 13 citations

    1

    h-index

1–5