Cross-sectional data on stablecoin characteristics

Published: 1 August 2022| Version 1 | DOI: 10.17632/v4pgsyn6dr.1
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Description

This cross-sectional dataset depicts the characteristics of stablecoins. Stablecoins are digital currencies that are designed to have a non-volatile value relative to other assets. They represent a relatively young but increasingly important branch of the cryptocurrency market. The dataset qualitatively and quantitatively describes several features for each stablecoin analysed, including information about the affiliation with any cryptocurrency exchange, presence on cryptocurrency exchanges, trading pairs, peg, availability of technical documentation on the stablecoin websites, age, market capitalisation, trading volume, type specified based on collateral and stabilisation mechanism. The dataset was compiled from websites of the stablecoin projects, a crypto-data aggregator, and other auxiliary sources. Each data item presented in this dataset is accompanied by a detailed source. The dataset includes 30 stablecoins that were listed by CoinMarketCap.com (as of 8 May 2022) and launched before 1 July 2021. These are: Tether, USD Coin, Binance USD, Terra USD, Dai, True USD, Pax Dollar, Neutrino USD, Frax, HUSD, Origin Dollar, Gemini Dollar, Stasis Euro, sUSD, Celo Dollar, Qcash, Vai, Steem Dollars, mStable USD, USDK, Rupiah Token, EOSDT, CryptoFranc, NuBits, Italian Lira, Fei, Liquity USD, XSGD, TerraKRW, Basis Cash. The dataset excludes stablecoins that has been suspended, or for which the project’s website was either not available or uninformative or a misclassification as stablecoin was identified. This dataset could be used by researchers, investors, or regulators for cross-sectional comparative studies on the stablecoin market, especially when investigating the relationship between cryptocurrency market developments and stablecoin characteristics.

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Institutions

Uniwersytet Ekonomiczny w Poznaniu

Categories

Exchange, Alternative Investment, Comparative Study, Cross-Sectional Research Method, Trading Volume, Digital Economy, Cryptocurrency

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