Master Thesis Online
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?
Robe, Xavier 
Promoteur(s) :
Torsin, Wouter
Date de soutenance : 5-sep-2022/10-sep-2022 • URL permanente : http://hdl.handle.net/2268.2/15557
Xavier_Robe_Master_Thesis_2022_Uni.pdfDétails
| Titre : | 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? |
| Auteur : | Robe, Xavier
|
| Date de soutenance : | 5-sep-2022/10-sep-2022 |
| Promoteur(s) : | Torsin, Wouter
|
| Membre(s) du jury : | Boudt, Kris |
| Langue : | Anglais |
| Nombre de pages : | 72 |
| Mots-clés : | [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) : | Sciences économiques & de gestion > Stratégie & innovation |
| Public cible : | Professionnels du domaine Grand public |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Diplôme : | Master en ingénieur de gestion, à finalité spécialisée en Financial Engineering |
| Faculté : | Mémoires de la HEC-Ecole de gestion de l'Université de Liège |
Résumé
[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.
Fichier(s)
Document(s)
Citer ce mémoire
L'Université de Liège ne garantit pas la qualité scientifique de ces travaux d'étudiants ni l'exactitude de l'ensemble des informations qu'ils contiennent.
