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HEC-Ecole de gestion de l'Université de Liège
HEC-Ecole de gestion de l'Université de Liège
MASTER THESIS
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What are the effects of the CEO's background on the success of his/her Initial Coin Offering (ICO), and how does it compare to other known determinants of success?

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Robe, Xavier ULiège
Promotor(s) : Torsin, Wouter ULiège
Date of defense : 5-Sep-2022/10-Sep-2022 • Permalink : http://hdl.handle.net/2268.2/15557
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Title : What are the effects of the CEO's background on the success of his/her Initial Coin Offering (ICO), and how does it compare to other known determinants of success?
Author : Robe, Xavier ULiège
Date of defense  : 5-Sep-2022/10-Sep-2022
Advisor(s) : Torsin, Wouter ULiège
Committee's member(s) : Boudt, Kris 
Language : English
Number of pages : 72
Keywords : [en] CEO characteristic
[en] Initial Coin Offering (ICO)
[en] Token offering
[en] Token listing
[en] Fundraising
[en] Finance
[en] Blockchain
[en] University degree
[en] Investors
[en] Entrepreneurs
[en] Cryptocurrencies
[en] Moral hazard
[en] Country restriction
[en] Scam
Discipline(s) : Business & economic sciences > Strategy & innovation
Target public : Professionals of domain
General public
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master en ingénieur de gestion, à finalité spécialisée en Financial Engineering
Faculty: Master thesis of the HEC-Ecole de gestion de l'Université de Liège

Abstract

[en] This work demonstrates the value of the CEO’s background in determining the success of ICOs. The definition of success can differ between entrepreneurs and investors and corresponds to
the maximum amount of money raised for the former, and the listing of the ICO’s tokens for the latter. These outcomes are uncoupled from each other through breaches of contract (frauds), i.e., the fact that ICOs that have reached their hard caps do not list their tokens in up to 26.71% of the cases. As a result, both outcomes are influenced by different sets of ICOs’ characteristics, and some characteristics can influence both outcomes in opposite directions (KYC).
We provide models that help determine both outcomes based on factual, easy-to-gather information, including an easy-to-use RPA predictive model for the likelihood of token listing.


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Author

  • Robe, Xavier ULiège Université de Liège > Master ingé. gest., à fin.

Promotor(s)

Committee's member(s)

  • Boudt, Kris
  • Total number of views 82
  • Total number of downloads 201










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