IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/4yb26.html
   My bibliography  Save this paper

Commodity Trade Finance Platform using Distributed Ledger Technology: Token Economics in a Closed Ecosystem using Agent Based Modeling

Author

Listed:
  • Wang, Jianfu

Abstract

Distributed Ledger Technology (DLT) creates a decentralized system for trust and transaction validation using executable smart contracts to update information across a distributed database. This type of ecosystem can be applied to Commodity Trade Finance to alleviate critical issues of information asymmetry and the cost of transacting which are the leading causes of the Trade Finance Gap (ie. the lack of supply of capital to meet total trade finance demand). The possibility of scaling up such ecosystems with a number of Institutional Investors and micro small medium enterprises (MSME) would be advantageous, however, it brings up its own set of challenges including the stability of the system design. Agent-based modeling (ABM) is a powerful method to assess the financial ecosystem dynamics. DLT ecosystems model well under ABM, as the agents present a clearly defined taxonomy. In this study, we use ABM to assess the Aquifer Institute Platform - a DLT-based Commodity Trade Finance system, in which a growing number of participating parties is closely related to the circulation of utility tokens and transaction flows. We study the system dynamics of the platform and propose an appropriate setup for different transaction loads.

Suggested Citation

  • Wang, Jianfu, 2018. "Commodity Trade Finance Platform using Distributed Ledger Technology: Token Economics in a Closed Ecosystem using Agent Based Modeling," OSF Preprints 4yb26, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:4yb26
    DOI: 10.31219/osf.io/4yb26
    as

    Download full text from publisher

    File URL: https://osf.io/download/5ac1be8ca2409b000fa25a33/
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:4yb26. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (OSF). General contact details of provider: https://osf.io/preprints/ .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.