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Counterparty Credit Risk on the Blockchain
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Motpartsrisk på blockkedjan (Swedish)
Abstract [en]

Counterparty credit risk is present in trades offinancial obligations. This master thesis investigates the up and comingtechnology blockchain and how it could be used to mitigate counterparty creditrisk. The study intends to cover essentials of the mathematical model expectedloss, along with an introduction to the blockchain technology. After modellinga simple smart contract and using historical financial data, it was evidentthat there is a possible opportunity to reduce counterparty credit risk withthe use of blockchain. From the market study of this thesis, it is obvious thatthe current financial market needs more education about blockchain technology.

Abstract [sv]

Motpartsrisk är närvarande i finansiella obligationer. Den här uppsatsen un- dersöker den lovande teknologin blockkedjan och hur den kan användas för att reducera motpartsrisk. Studien har för avsikt att täcka det essentiel- la i den matematiska modellen för förväntad förlust, samt en introduktion om blockkedjeteknologi. Efter att ha modellerat ett enkelt smart kontrakt, där historiska finansiella data använts, var det tydligt att det kan finnas en möjlighet att reducera motpartsrisk med hjälp av blockkedjan. Från mark- nadsundersökningen gjord i studien var det uppenbart att den nuvarande finansiella marknaden är i stort behov av mer utbildning om blockkedjan.

Place, publisher, year, edition, pages
2017.
Series
TRITA-MAT-E ; 2017:69
Keywords [en]
Counterparty Credit Risk, Expected Loss, Blockchain, Smart Contracts
Keywords [sv]
Motpartsrisk, Förväntad Förlust, Blockkedjan, Smarta Kontrakt
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-215493OAI: oai:DiVA.org:kth-215493DiVA, id: diva2:1149193
External cooperation
Safello
Subject / course
Financial Mathematics
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2017-10-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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  • nn-NB
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  • Other locale
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Output format
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