Fraud and Anomaly Detection in the Digital Asset Economy
A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Economics and Finance".
Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 622
Special Issue Editors
Interests: extreme value analysis and distribution theory in analysing financial commodities data and cryptocurrency data, and financial risk models
Special Issues, Collections and Topics in MDPI journals
Interests: statistics and distribution theory with financial applications; cryptocurrencies; blockchain and social networks
Special Issues, Collections and Topics in MDPI journals
Interests: multivariate and extreme value analysis; big data sets; cryptocurrencies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The market for digital assets has exploded over the past few years. Digital assets consist mostly of speculative investments, such as cryptocurrencies, decentralised finance (DeFi), initial coin offerings (ICOs), and nonfungible tokens (NFTs). These assets are being embraced by governments, and both major financial and non-financial institutions. As a result of their great potential and the rising popularity of these technological systems, digital assets are vulnerable to anomalies and fraud that can have serious consequences for the integrity and security of these assets. The aim of this Special Issue is to provide a collection of papers from leading experts in the area of anomaly and fraud detection in digital assets. The topics covered in this Special Issue include, but are not limited to:
- Blockchain networks
- Nonfungible Tokens
- Web 3.0
- Stablecoins
- Cryptocurrencies
- Digital Banking
- Criminology
- Cybercrime
Dr. Stephen Chan
Dr. Jeffrey Chu
Dr. Yuanyuan Zhang
Guest Editors
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