Nonlinear Forecasting Models

Nonlinear Forecasting Models is a class of econometric and machine learning models that belong to the broader category of forecasting methods, distinguished by their ability to capture complex, nonlinear relationships and interactions among variables in commodity price dynamics that linear models cannot adequately represent.

1.1K

Publications

72.7K

Citations

2.7K

Authors

1.2K

Institutions

Publications per year

2017–2026

401

Authors

2.7K

  1. TT
    Timo Teräsvirta

    Stockholm School of Economics, Sweden

    14 publications · 2.9K citations

    11

    h-index

  2. XX
    Xiaojie Xu

    North Carolina State University, United States

    11 publications · 1.5K citations

    11

    h-index

  3. SW
    Shouyang Wang

    Chinese Academy of Sciences, China

    11 publications · 820 citations

    10

    h-index

  4. RG
    Rangan Gupta

    University of Pretoria, South Africa

    10 publications · 252 citations

    10

    h-index

  5. CW
    Clive W. J. Granger

    University of California San Diego, United States

    10 publications · 2.6K citations

    10

    h-index

1–5 of 2.7K

Venues

  1. International Journal of Forecasting

    27 publications · 2.9K citations

    22

    h-index

  2. Expert Systems with Applications

    24 publications · 1.9K citations

    21

    h-index

  3. Neurocomputing

    19 publications · 1.7K citations

    19

    h-index

  4. Journal of Forecasting

    28 publications · 1.3K citations

    19

    h-index

  5. Energies

    18 publications · 808 citations

    15

    h-index

1–5