Towards a taxonomy for crypto assets
AbstractWe explore the taxonomy of cryptocurrencies and integrate our analysis with traditional ways of understanding financial assets. We thus classify cryptocurrencies using the time series and distributional properties of returns. Cryptocurrencies appear inherently speculative in nature. The resu...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
|
| Series: | Cogent Economics & Finance |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23322039.2023.2207266 |
| _version_ | 1797658351923888128 |
|---|---|
| author | John Fry Olamide Ibiloye |
| author_facet | John Fry Olamide Ibiloye |
| author_sort | John Fry |
| collection | DOAJ |
| description | AbstractWe explore the taxonomy of cryptocurrencies and integrate our analysis with traditional ways of understanding financial assets. We thus classify cryptocurrencies using the time series and distributional properties of returns. Cryptocurrencies appear inherently speculative in nature. The result is even more clear cut when time series measures of distance are used. Results tally with wider concerns raised regarding excessive volatility of stablecoins. |
| first_indexed | 2024-03-11T17:57:50Z |
| format | Article |
| id | doaj.art-3bc726b4a4634156b4d71fa11d21de1a |
| institution | Directory Open Access Journal |
| issn | 2332-2039 |
| language | English |
| last_indexed | 2024-03-11T17:57:50Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Economics & Finance |
| spelling | doaj.art-3bc726b4a4634156b4d71fa11d21de1a2023-10-17T10:51:07ZengTaylor & Francis GroupCogent Economics & Finance2332-20392023-12-0111110.1080/23322039.2023.2207266Towards a taxonomy for crypto assetsJohn Fry0Olamide Ibiloye1Centre for Mathematical Sciences, School of Natural Sciences, University of Hull, Hull, UKCentre of Excellence for Data Science Artificial Intelligence and Modelling, University of Hull, Hull, UKAbstractWe explore the taxonomy of cryptocurrencies and integrate our analysis with traditional ways of understanding financial assets. We thus classify cryptocurrencies using the time series and distributional properties of returns. Cryptocurrencies appear inherently speculative in nature. The result is even more clear cut when time series measures of distance are used. Results tally with wider concerns raised regarding excessive volatility of stablecoins.https://www.tandfonline.com/doi/10.1080/23322039.2023.2207266Bitcoincryptocurrencyfin techprobability distributionstatisticstime series |
| spellingShingle | John Fry Olamide Ibiloye Towards a taxonomy for crypto assets Cogent Economics & Finance Bitcoin cryptocurrency fin tech probability distribution statistics time series |
| title | Towards a taxonomy for crypto assets |
| title_full | Towards a taxonomy for crypto assets |
| title_fullStr | Towards a taxonomy for crypto assets |
| title_full_unstemmed | Towards a taxonomy for crypto assets |
| title_short | Towards a taxonomy for crypto assets |
| title_sort | towards a taxonomy for crypto assets |
| topic | Bitcoin cryptocurrency fin tech probability distribution statistics time series |
| url | https://www.tandfonline.com/doi/10.1080/23322039.2023.2207266 |
| work_keys_str_mv | AT johnfry towardsataxonomyforcryptoassets AT olamideibiloye towardsataxonomyforcryptoassets |