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Massachusetts Institute of Technology

Convertible Trade Credits: a new way of creating value

Abstract

dc:description.abstract

This paper aims to explore the possibility of a vendor supporting a firm’s growth opportunities in sequential financing rounds in exchange for shares in the firm’s common stock. We departed from an initial setup where a firm has a positive NPV growth opportunity and easy access to financing (Myers and Read, 2020). We moved forward to set up a scenario where the firm had difficulties raising funding for the same real call option and asked whether it would be advantageous to rely on key vendors to finance it. The answer to the question was affirmative. We found that the new proposed Convertible Trade Credits Contract creates value for both parties in the transaction by allowing the firm to realize the growth opportunity <optimal investment policy> while sharing risks and returns with the vendor <diversification>. We relied on discrete binomial event trees to price real call options and the constant dividend growth model to price the firm’s stock under different states of nature. The example we provide assumes a world with no corporate taxes.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Sloan School of Management
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sanabria, Pedro A.
Advisor dc:contributor.advisor
  • Myers, Stewart C.

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/146684
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/146684

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Sanabria, Pedro A.. Convertible Trade Credits: a new way of creating value. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/146684