• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Norges Handelshøyskole
  • Thesis
  • Master Thesis
  • View Item
  •   Home
  • Norges Handelshøyskole
  • Thesis
  • Master Thesis
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Measuring decentralised finance regulatory uncertainty

Zmaznev, Egor
Master thesis
Thumbnail
View/Open
masterthesis.pdf (942.3Kb)
URI
https://hdl.handle.net/11250/2769995
Date
2021
Metadata
Show full item record
Collections
  • Master Thesis [4657]
Abstract
develop and compare two DeFi regulatory uncertainty indexes based on the specialised media

coverage frequency. By applying active learning in combination with SVM to identify

uncertainty-related news articles, I show how regulatory uncertainty can be captured for

emerging industries with limited data intervals. Both indexes display rising levels of DeFi

regulatory uncertainty in recent years with the highest index spikes appearing during the first

wave of the COVID-19 pandemic. By constructing a structural VAR model, I identified the

negative effects of regulatory uncertainty shocks on total value locked in smart contracts of

decentralised financial services. The negative response is consistent among the leading DeFi

categories, such as lending services and decentralised exchanges. However, uncertainty shocks

cause an increase of total value locked in derivatives and payment protocols.

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit