IDEAS home Printed from https://ideas.repec.org/a/gam/jforec/v8y2026i1p17-d1863903.html

Satellite Data and Artificial Intelligence for FINtech

Author

Listed:
  • Alberto Garinei

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy
    Idea-Re S.r.l., 06128 Perugia, Italy)

  • Massimiliano Proietti

    (Idea-Re S.r.l., 06128 Perugia, Italy)

  • Alessandro Vispa

    (Idea-Re S.r.l., 06128 Perugia, Italy)

  • Stefano Speziali

    (Idea-Re S.r.l., 06128 Perugia, Italy)

  • Giovanni Bartolini

    (Idea-Re S.r.l., 06128 Perugia, Italy)

  • Marcello Marconi

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy
    Idea-Re S.r.l., 06128 Perugia, Italy)

  • Emanuele Piccioni

    (Idea-Re S.r.l., 06128 Perugia, Italy)

  • Matteo Martini

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

  • Francesca Fallucchi

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

  • Romeo Giuliano

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

  • Ernesto William De Luca

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

  • Umberto Di Matteo

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

  • Valerio Lemma

    (Department of Engineering Sciences, Guglielmo Marconi University, 00193 Rome, Italy)

Abstract

The SAIFIN project (Satellite data and Artificial Intelligence for FINtech) develops a novel algorithmic trading system that integrates satellite imagery, financial data, and advanced artificial intelligence to enhance decision-making, particularly in commodity and agricultural markets. This paper presents the motivation, design, implementation, and validation of the SAIFIN framework. Leveraging alternative data and modular multi-agent architectures, SAIFIN aims to deliver robust, context-aware trading signals in diverse market conditions.

Suggested Citation

  • Alberto Garinei & Massimiliano Proietti & Alessandro Vispa & Stefano Speziali & Giovanni Bartolini & Marcello Marconi & Emanuele Piccioni & Matteo Martini & Francesca Fallucchi & Romeo Giuliano & Erne, 2026. "Satellite Data and Artificial Intelligence for FINtech," Forecasting, MDPI, vol. 8(1), pages 1-20, February.
  • Handle: RePEc:gam:jforec:v:8:y:2026:i:1:p:17-:d:1863903
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-9394/8/1/17/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2571-9394/8/1/17/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jforec:v:8:y:2026:i:1:p:17-:d:1863903. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.