Algorithmic Trading In Commodities

Algorithmic Trading in Commodities is a computational trading methodology that automates the execution of commodity market transactions through predefined algorithmic rules, distinguished from conventional trading approaches by its reliance on mathematical models, high-frequency data processing, and systematic risk-control mechanisms to exploit price inefficiencies across commodity markets.

14

Publications

275

Citations

34

Authors

19

Institutions

Publications per year

2017–2026

7

Authors

34

  1. CL
    Camillo Lento

    Lakehead University, Canada

    1 publications · 11 citations

    1

    h-index

  2. PG
    Philip Garcia

    University of Illinois Urbana-Champaign, United States

    1 publications · 17 citations

    1

    h-index

  3. IK
    Ioannis Karkanis

    1 publications · 14 citations

    1

    h-index

  4. LZ
    Luyao Zhang

    Duke Kunshan University, China

    1 publications · 28 citations

    1

    h-index

  5. CP
    Chaiyuth Padungsaksawasdi

    Thammasat University, Thailand

    1 publications · 41 citations

    1

    h-index

1–5 of 34

Venues

  1. Journal of Futures Markets

    4 publications · 92 citations

    4

    h-index

  2. Journal of risk and financial management

    JRFM · 2 publications · 25 citations

    2

    h-index

  3. Applied Economics

    1 publications · 17 citations

    1

    h-index

  4. Pacific-Basin Finance Journal

    1 publications · 24 citations

    1

    h-index

  5. Computer law & security review

    1 publications · 13 citations

    1

    h-index

1–5