Cross-sectional data on stablecoin characteristics

Katarzyna Włosik; Blanka Łęt; Konrad Sobański; Wojciech Świder

doi:10.12688/f1000research.126298.1

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Data Note

Cross-sectional data on stablecoin characteristics

[version 1; peer review: 2 approved]

Katarzyna Włosik ¹, Blanka Łęt², Konrad Sobański³, Wojciech Świder⁴

PUBLISHED 17 Oct 2022

Author details Author details

¹ Department of Investment and Financial Markets, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
² Department of Applied Mathematics, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
³ Department of International Finance, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
⁴ Department of Public Finance, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland

Katarzyna Włosik
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Validation, Writing – Original Draft Preparation

Blanka Łęt
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Software, Writing – Review & Editing

Konrad Sobański
Roles: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing

Wojciech Świder
Roles: Data Curation, Funding Acquisition, Investigation, Writing – Review & Editing

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REVIEWER STATUS

This article is included in the Data: Use and Reuse collection.

Abstract

The article presents a dataset on the characteristics of stablecoins. Stablecoins represent a relatively young but increasingly important branch of the cryptocurrency market. Although they all share the same goal of maintaining a stable value in the digital market, they form a highly heterogeneous group. They differ in terms of collateral and stabilization mechanism, peg, availability of the technical documentation, presence on crypto exchanges or age. The dataset is cross-sectional and was created based on internet research. Individual information was collected from websites of the stablecoin projects and a crypto-data aggregator, and to a lesser extent from other auxiliary sources (websites related to finance and cryptocurrencies). The dataset is unique as there are no publicly available databases encompassing the features of stablecoins. It can be used in all stablecoin-related analyses to characterise the examined coins and to investigate the relationship between cryptocurrency market developments and stablecoin features.

Keywords

Stablecoin, cryptocurrency, whitepaper, exchanges, market cap, collateral type

Corresponding author: Katarzyna Włosik

Competing interests: No competing interests were disclosed.

Grant information: The project financed within the Regional Initiative for Excellence programme of the Minister of Education and Science of Poland, years 2019-2023, grant no. 004/RID/2018/19, financing 3,000,000 PLN.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Włosik K et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Włosik K, Łęt B, Sobański K and Świder W. Cross-sectional data on stablecoin characteristics [version 1; peer review: 2 approved]. F1000Research 2022, 11:1188 (https://doi.org/10.12688/f1000research.126298.1) First published: 17 Oct 2022, 11:1188 (https://doi.org/10.12688/f1000research.126298.1) Latest published: 17 Oct 2022, 11:1188 (https://doi.org/10.12688/f1000research.126298.1)

Introduction

Stablecoins can be defined as digital units of value that, through special stabilisation mechanisms, are supposed to maintain a stable value in relation to a selected benchmark – one or more traditional currencies or other types of assets, including crypto assets.¹ Stablecoins are drawing the attention of policymakers due to their dynamic growth, the increasing number of use cases and the risks they may pose to financial stability.¹ The stablecoin market is also appealing to investors and researchers. Nevertheless, very few papers explore the importance of stablecoin features. The work of García et al.,² who consider stablecoin features when developing a framework for risk assessment, is among the exceptions. Jarno and Kołodziejczyk³ analyse the volatility of stablecoins with respect to the type of these digital assets. It is worth noting that while all stablecoins aim to maintain a stable value, they differ in many aspects. This fact creates research opportunities.

The dataset presented in this Data Note combines multiple data sources on individual stablecoins to form a unique database on the stablecoin market (on features of stablecoins). It can be useful for researchers and practitioners interested in the functioning and development of the cryptocurrency market. The dataset might be used for cross-sectional comparative studies on the stablecoin market. This branch of the cryptocurrency market is relatively young and there are no publicly available databases encompassing the features of these digital assets. The dataset can be applied in all stablecoin-related analyses to characterise the examined coins and investigate the relationship between cryptocurrency market developments and stablecoin features without the need to dedicate efforts to time-consuming studies of individual stablecoins.

Methods

The data was collected via internet research. The list of stablecoins was compiled from information available on the website of CoinMarketCap – the aggregator of cryptocurrency data which is frequently used in research (see for example Refs. 4–7). Then, data on these stablecoins was collected from various sources – websites of the stablecoin projects, CoinMarketCap, and, to a limited extent, other websites.

Out of the group of 98 stablecoins that were listed by CoinMarketCap (as of 8 May 2022) the data was collected for 30 of them. A coin was excluded from the analysis if:

• it was launched after 1 July 2021,
• there was virtually no information on this stablecoin and the project’s website was not working when the study took place (e.g. Xaurum.org),
• it was misclassified as a stablecoin – such cases were determined based on the price charts provided by CoinMarketCap and also the analysis of the projects’ websites (e.g. Reserve Rights – RSR, was classified as a stablecoin when the study took place, however the price chart showed great variability⁸ and the website of the project informed that RSR was a governance token supporting the functioning of a stablecoin developed within the same protocol⁹^,¹⁰),
• its operation has been suspended (e.g. DigixDAO¹¹).

The information used to create the database came from several sources:

• the CoinMarketCap.com website (list of stablecoins, tickers, approximated start date, market capitalisation, number of crypto exchanges listing a particular stablecoin, number of trading pairs in which a particular stablecoin is included),
• websites of the analysed stablecoin projects (type of stablecoin, availability of whitepaper/documentation, peg),
• other websites (other relevant information, e.g. link to any crypto exchange).

Due to the large number of websites, their addresses are provided in the dataset file. Each data point is accompanied there by a source.

Data description

The dataset (see Underlying data ¹²) includes 30 stablecoins: 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 database contains 14 features characterising each of the above-mentioned stablecoins. The features were selected to show different aspects of stablecoins, including their technical properties, connections to different trading venues and properties that may affect their attractiveness, credibility and availability for market participants. The description of these characteristics is provided in Table 1.

Table 1. Characteristics of stablecoins included in the database and their description.

Characteristic	Description
1. Link to any crypto exchange	Stablecoins can be bought or sold on various trading venues – so-called crypto exchanges. In the case of ten stablecoins that are included in the dataset, there are some relationships between the stablecoin project and a crypto exchange. As indicated by Rosa and Pareschi,¹³ there are co-ownership and co-administrative relationships between the issuer of Tether and Bitfinex. Pax dollar and the crypto exchange itBit are linked via the company Paxos.¹⁴ The issuer of HUSD is a strategic partner of Huobi Global.¹⁵ USD Coin is related to Coinbase,¹⁶ Binance USD to Binance,¹⁷ and TerraUSD was launched in cooperation with Bittrex Global.¹⁸ OKEx launched USDK¹⁹ and Gemini – Gemini dollar.²⁰ Decentralized Forex (DeFo) is a decentralized exchange that is an extension of the Neutrino protocol on which Neutrino USD is based.²¹^,²² And sUSD is linked to Kwenta.²³ In the database, this is a dummy variable (1 – stablecoin is linked to a crypto exchange; 0 – stablecoin is not linked to any crypto exchange).
2. Peg to the USD (United States dollar)	Prices of stablecoins are pegged to selected benchmarks. This variable shows whether a stablecoin is pegged to the USD, as the USD is one of the most frequently used benchmarks in the stablecoin universe and it also dominates in the dataset. The remaining stablecoins that are included in the dataset are pegged to the euro (Stasis Euro), the Chinese yuan (Qcash), the Indonesian rupiah (Rupiah Token), the Swiss franc (CryptoFranc), the Singapore dollar (XSGD), and the South Korean won (TerraKRW). For one stablecoin – Italian Lira, there is no official information on the peg. In the database, this is a dummy variable (1 – stablecoin is pegged to the USD; 0 – stablecoin is not pegged to the USD).
3. Availability of a whitepaper or documentation on the stablecoin website	During the data collection phase, it was verified whether a whitepaper or technical documentation for the stablecoin project was available on its website. It is worth noting that there are websites that collect whitepapers related to cryptocurrency projects. However, it is not always possible to verify by whom and when the document was provided. This is why only the official websites of the projects have been considered. In the database, this is a dummy variable (1 – a whitepaper/ documentation is available on the stablecoin website; 0 – a whitepaper/documentation is not available on the stablecoin website).
4. Approximated age of the analysed stablecoins (in days)	Stablecoins differ also in terms of age. For many stablecoins, the exact date of inception has not been provided by their issuers. Therefore, the starting data point from the CoinMarketCap website is used as a proxy for the inception date. The age is expressed as the number of days between the inception date and 6 May 2022.
5. Classes of stablecoins based on their age	Stablecoins can be grouped by age (based on variable 4). They are classified as ‘old’ if they were launched at least 1,000 days before 6 May 2022. They are considered ‘young’ if the number of days is 500 or less. Otherwise, they are included in the ‘middle’ category.
6. Presence of stablecoins on major exchanges	Stablecoins can be traded on crypto exchanges. However, these digital assets differ significantly in terms of the number of exchanges that list them. A major exchange is defined here as one of the top ten crypto exchanges by share in total trading volume according to the CoinMarketCap ranking. This variable shows the number of major exchanges that list a given stablecoin.
7. Classes of stablecoins based on their presence on major exchanges	This variable presents classes of stablecoins based on their presence on major exchanges (based on variable 6). Some stablecoins included in the dataset were not listed by any of these exchanges (class ‘none’). If a stablecoin was listed by only one major exchange, its presence is ‘limited’. If it was listed by two to ten major exchanges, its presence is classified as ‘significant’.
8. Number of crypto exchanges listing a particular stablecoin	Stablecoins also differ in terms of the total number of exchanges that list them, which is reflected by this variable.
9. Classes of stablecoins based on the number of crypto exchanges listing a particular stablecoin	Based on the general number of crypto exchanges that list a particular stablecoin (based on variable 8), these cryptocurrencies can be divided into groups. The number of exchanges is considered ‘large’ when it is equal to or exceeds 50. This number is considered ‘moderate’ if it is between 11 and 49. Otherwise, it is considered ‘small’.
10. Number of trading pairs containing a particular stablecoin	Even on a single exchange, a particular stablecoin can be included in multiple trading pairs (e.g. BTC/USDT – Bitcoin to Tether). This variable reports the approximated number of such pairs for each stablecoin.
11. Classes of stablecoins based on the number of trading pairs containing a particular stablecoin	Based on the number of trading pairs containing a particular stablecoin (based on variable 10), these digital assets are divided into three groups. The number of pairs is considered ‘large’ when it is at least 200. The number is considered ‘moderate’ when it is between 31 and 199, and ‘small’ – when it is up to 30.
12. Stablecoin type	Stablecoins differ in type. They can be backed by assets – traditional assets, usually fiat currencies or assets denominated in fiat currencies, and digital assets – cryptocurrencies and other digital tokens. There are also algorithmic stablecoins. These are governed by an algorithm and smart contracts that regulate their supply and aim to ensure price stability. The number of stablecoin units in circulation is reduced when the price falls below peg, and increases when the price exceeds peg.²⁴ A systematic discussion of stablecoin design characteristics can be found in Ref. 25. In the dataset, four groups of stablecoins are distinguished based on their type. The first group contains stablecoins that are backed by fiat currencies and/or assets denominated in fiat currencies. The second group – stablecoins that are at least partially crypto-backed. The evolution of the cryptocurrency market has led to the emergence of hybrid stablecoins, which combine features of different types. Therefore, this category contains stablecoins that are either collateralised by crypto assets or are both collateralised by these assets and use an algorithm at the same time. It is worth noting, however, that the collateral is declared by the developer. The third group contains algorithmic stablecoins. For one coin – Italian Lira, no information is available.
13. Median market capitalisation in USD	This variable reflects the median market capitalisation for each stablecoin included in the dataset. The median is calculated over the period from 23 November 2021 to 6 May 2022 based on daily data.
14. Median trade volume in USD	The median trade volume for each stablecoin from the dataset is calculated over the period from 23 November 2021 to 6 May 2022 based on daily data. It needs to be underlined, however, that when analysing trade volume that is aggregated across exchanges, one needs to be aware of its limitations. This variable is criticised in the literature for being biased and inflated (for a discussion see Ref. 26).

Data availability

Underlying data

Mendeley Data: Cross-sectional data on stablecoin characteristics. https://doi.org/10.17632/v4pgsyn6dr.1.¹²

This project contains the following underlying data:

- Dataset.xlsx

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

References

1. Adachi M, Pereira Da Silva PB, Born A, et al.: Stablecoins’ role in crypto and beyond: functions, risks and policy.European Central Bank;2022. (accessed 14 September 2022).Reference Source
2. García A, Lands B, Yanchus D: Stablecoin assessment framework.Bank of Canada Staff Discussion Paper, 2021, No. 2021-6, Bank of Canada, Ottawa.
3. Jarno K, Kołodziejczyk H: Does the Design of Stablecoins Impact Their Volatility? J. Risk Fin. Manag. 2021; 14(42). Publisher Full Text
4. Kristoufek L: Tethered, or Untethered? On the interplay between stablecoins and major cryptoassets. Financ. Res. Lett. 2021; 43: 101991. Publisher Full Text
5. Assaf A, Bhandari A, Charif H, et al.: Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19. Int. Rev. Financ. Anal. 2022; 82: 102132. Publisher Full Text
6. Long H, Zaremba A, Demir E, et al.: Seasonality in the Cross-Section of Cryptocurrency Returns. Financ. Res. Lett. 2020; 35: 101566. Publisher Full Text
7. Meyer A, Ante L: Effects of initial coin offering characteristics on cross-listing returns. Digital Finance. 2020; 2: 259–283. Publisher Full Text
8. CoinMarketCap: Reserve Rights.2022. (accessed 8 May 2022).Reference Source
9. Reserve: Introduction to the Reserve protocol.(accessed 8 May 2022).Reference Source
10. Reserve Rights (RSR): Introduction to the Reserve protocol.(accessed 8 May 2022).Reference Source
11. Digix: Customer Notice.(accessed 8 May 2022).Reference Source
12. Włosik K, Łęt B, Sobański K, et al.: Cross-sectional data on stablecoin characteristics, Mendeley Data, V1, 2022. [Dataset].Reference Source
13. Rosa G, Pareschi R: Tether: A Study on Bubble-Networks. Front. Blockchain. 2021; 4: 686484. Publisher Full Text
14. Paxos: Pax Dollar (USDP): White Paper.2021. (accessed 8 July 2022).Reference Source
15. Huobi Global: The Safe and Secure Stablecoin. Frequently Asked Questions. Who is the issuer of HUSD?2022. (accessed 8 July 2022).Reference Source
16. Centre: Introducing USD COIN: A stablecoin brought to you by Circle and Coinbase.2022. (accessed 8 July 2022).Reference Source
17. Paxos: Binance USD (BUSD).2022. (accessed 8 July 2022).Reference Source
18. Kwon D: Announcing TerraUSD (UST) – the Interchain Stablecoin.2020. (accessed 8 July 2022).Reference Source
19. Perryman E: What is the USDK stablecoin?2019. (accessed 8 July 2022).Reference Source
20. Gemini: Gemini dollar.2022. (accessed 8 July 2022).Reference Source
21. Neutrino: Decentralized Forex. Trade national currencies on a decentralized exchange.2022. (accessed 8 July 2022).Reference Source
22. Neutrino: USDN.2022. (accessed 8 July 2022).Reference Source
23. Kwenta: FAQ.2022. (accessed 8 July 2022).Reference Source
24. Gemini: What Are Stablecoins?2022. (accessed 8 July 2022).Reference Source
25. Moin A, Sekniqi K, Sirer EG:SoK: A Classification Framework for Stablecoin Designs.Bonneau J, Heninger N, editors. Financial Cryptography and Data Security. FC 2020. Lecture Notes in Computer Science. Cham:Springer;2020; 12059.
26. Alexander C, Dakos M: A critical investigation of cryptocurrency data and analysis. Quant. Finance. 2020; 20(2): 173–188. Publisher Full Text

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Version 1

VERSION 1 PUBLISHED 17 Oct 2022

Author details Author details

¹ Department of Investment and Financial Markets, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
² Department of Applied Mathematics, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
³ Department of International Finance, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland
⁴ Department of Public Finance, Poznań University of Economics and Business, Al. Niepodległości 10, 61-875 Poznań, Poland

Katarzyna Włosik
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Validation, Writing – Original Draft Preparation

Blanka Łęt
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Software, Writing – Review & Editing

Konrad Sobański
Roles: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing

Wojciech Świder
Roles: Data Curation, Funding Acquisition, Investigation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The project financed within the Regional Initiative for Excellence programme of the Minister of Education and Science of Poland, years 2019-2023, grant no. 004/RID/2018/19, financing 3,000,000 PLN.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Published: 17 Oct 2022, 11:1188

https://doi.org/10.12688/f1000research.126298.1

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© 2022 Włosik K et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Włosik K, Łęt B, Sobański K and Świder W. Cross-sectional data on stablecoin characteristics [version 1; peer review: 2 approved]. F1000Research 2022, 11:1188 (https://doi.org/10.12688/f1000research.126298.1)

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Reviewer Report 03 Feb 2023

Rekha Pillai, College of Business Administration, Ajman University, Ajman, United Arab Emirates

Approved

https://doi.org/10.5256/f1000research.138695.r154508

The article is novel. The rationale for creating the aforesaid data set is clearly outlined. The authors have collected Individual information from websites of the stablecoin projects and a crypto-data aggregator and they have clearly mentioned about the limited availability ... Continue reading

The article is novel. The rationale for creating the aforesaid data set is clearly outlined. The authors have collected Individual information from websites of the stablecoin projects and a crypto-data aggregator and they have clearly mentioned about the limited availability of stablecoin related information available on the public domain. It can be considered as an exploratory study as it unearths the stable coin dimensions, a less researched topic but one of high significance.

Future studies can build on the same and this is the main contribution of the paper. The data set is clearly presented in a useable and accessible format. It is clearly evident that no other cross- sectional studies of a similar nature has been conducted till date. However, as a suggestion, you may also justify the rationale behind why only 30 stable coins were selected, although the attempt is highly appreciated. You have clearly highlighted the rationale in excluding certain stable coins but you may elaborate on the total available, ones included and those excluded for providing a comprehensive picture.

As a recommendation to improve the paper, a brief literature review in a tabular form which only contains author names, year and key findings can add value. The paper may include a concluding paragraph, wrapping up the study with some future research/practical implications. Limitations of the study can be highlighted and suggest potential use of aforesaid data collected as recommendations for future research.

Finally thank you for giving this opportunity to review the paper and I hope the comments will be taken positively.

Is the rationale for creating the dataset(s) clearly described?

Yes
Are the protocols appropriate and is the work technically sound?

Yes
Are sufficient details of methods and materials provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Corporate governance, cryptocurrency, firm performance, behavioral finance

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

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17

Reviewer Report 05 Dec 2022

Sergio Luis Náñez Alonso, DEKIS Research Group, Department of Economics, Catholic University of Ávila, Avila, Spain

Approved

https://doi.org/10.5256/f1000research.138695.r156525

The data note under review presents a brief introduction to the characterization of digital currencies called Stablecoins. This has allowed the authors to build up a novel database on stablecoins, mainly by searching the Internet. It is therefore a brief ... Continue reading

The data note under review presents a brief introduction to the characterization of digital currencies called Stablecoins. This has allowed the authors to build up a novel database on stablecoins, mainly by searching the Internet. It is therefore a brief scientific review of the current state of the art on stablecoins, proposing a database that can be used by other researchers in their studies. It is in this last point that the value of the study lies.

After reviewing the data note, it can be qualified as highly original, given that there are no other cross-sectional databases available for consultation by potential cryptocurrency researchers. This means that the contribution to scholarship is also high. Regarding the structure, the data note under evaluation is of the short-paper type, so the introduction is sufficient.

There are a few issues that should be improved by the authors:

In the methodology section, the authors should refer to previous database generation studies with their limitations.

In the data description section, the authors should indicate a valid reason why only 30 Stablecoins were selected. In other words, originality in the attempt to construct this database is appreciated. The methodology details the criteria for selecting the sample of 30 stablecoins based on the information that appears in CoinMarketCap, the websites of the stablecoins themselves and other websites (at this point, they could mention some, perhaps including references). I understand that of the 98 listed on CoinMarketCap as of May 2022, many were excluded (down to 30) for the reasons stated. I don't know if Terra USD is no longer classified as a stablecoin after the crash that month (it dropped 40% in value). Do you guys consider keeping it in the sample? If so, I would like you to explain.

I find table 1 very interesting as it raises 14 characteristics (a sufficient number) and a description of these. It is a research note that adds value to academic research on this topic. I recommend, however, to expand the references, either in the text or in Table 1, as there are many publications on stablecoins, in order to characterize stablecoins with previous studies and authors.

Finally, I thank you for inviting me to review this data note. I found it relevant and interesting.

Is the rationale for creating the dataset(s) clearly described?

Yes
Are the protocols appropriate and is the work technically sound?

Yes
Are sufficient details of methods and materials provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Digital Economy, Decentralised Finance, Central Bank digital Currency

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Sergio Luis Náñez Alonso, Catholic University of Ávila, Avila, Spain
Rekha Pillai, Ajman University, Ajman, United Arab Emirates

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Rekha Pillai, College of Business Administration, Ajman University, Ajman, United Arab Emirates

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Approved

The article is novel. The rationale for creating the aforesaid data set is clearly outlined. The authors have collected Individual information from websites of the stablecoin projects and a crypto-data aggregator and they have clearly mentioned about the limited availability of stablecoin related information available on the public domain. It can be considered as an exploratory study as it unearths the stable coin dimensions, a less researched topic but one of high significance.

Future studies can build on the same and this is the main contribution of the paper. The data set is clearly presented in a useable and accessible format. It is clearly evident that no other cross- sectional studies of a similar nature has been conducted till date. However, as a suggestion, you may also justify the rationale behind why only 30 stable coins were selected, although the attempt is highly appreciated. You have clearly highlighted the rationale in excluding certain stable coins but you may elaborate on the total available, ones included and those excluded for providing a comprehensive picture.

As a recommendation to improve the paper, a brief literature review in a tabular form which only contains author names, year and key findings can add value. The paper may include a concluding paragraph, wrapping up the study with some future research/practical implications. Limitations of the study can be highlighted and suggest potential use of aforesaid data collected as recommendations for future research.

Finally thank you for giving this opportunity to review the paper and I hope the comments will be taken positively.

Is the rationale for creating the dataset(s) clearly described?

Yes
Are the protocols appropriate and is the work technically sound?

Yes
Are sufficient details of methods and materials provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Corporate governance, cryptocurrency, firm performance, behavioral finance

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

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Reviewer Report

17 Views

05 Dec 2022 | for Version 1

Sergio Luis Náñez Alonso, DEKIS Research Group, Department of Economics, Catholic University of Ávila, Avila, Spain

17 Views Cite this report Responses(0)

Approved

The data note under review presents a brief introduction to the characterization of digital currencies called Stablecoins. This has allowed the authors to build up a novel database on stablecoins, mainly by searching the Internet. It is therefore a brief scientific review of the current state of the art on stablecoins, proposing a database that can be used by other researchers in their studies. It is in this last point that the value of the study lies.

After reviewing the data note, it can be qualified as highly original, given that there are no other cross-sectional databases available for consultation by potential cryptocurrency researchers. This means that the contribution to scholarship is also high. Regarding the structure, the data note under evaluation is of the short-paper type, so the introduction is sufficient.

There are a few issues that should be improved by the authors:

In the methodology section, the authors should refer to previous database generation studies with their limitations.

In the data description section, the authors should indicate a valid reason why only 30 Stablecoins were selected. In other words, originality in the attempt to construct this database is appreciated. The methodology details the criteria for selecting the sample of 30 stablecoins based on the information that appears in CoinMarketCap, the websites of the stablecoins themselves and other websites (at this point, they could mention some, perhaps including references). I understand that of the 98 listed on CoinMarketCap as of May 2022, many were excluded (down to 30) for the reasons stated. I don't know if Terra USD is no longer classified as a stablecoin after the crash that month (it dropped 40% in value). Do you guys consider keeping it in the sample? If so, I would like you to explain.

I find table 1 very interesting as it raises 14 characteristics (a sufficient number) and a description of these. It is a research note that adds value to academic research on this topic. I recommend, however, to expand the references, either in the text or in Table 1, as there are many publications on stablecoins, in order to characterize stablecoins with previous studies and authors.

Finally, I thank you for inviting me to review this data note. I found it relevant and interesting.

Is the rationale for creating the dataset(s) clearly described?

Yes
Are the protocols appropriate and is the work technically sound?

Yes
Are sufficient details of methods and materials provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Digital Economy, Decentralised Finance, Central Bank digital Currency

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

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[1] 1. Adachi M, Pereira Da Silva PB, Born A, et al.: Stablecoins’ role in crypto and beyond: functions, risks and policy.European Central Bank;2022. (accessed 14 September 2022).Reference Source

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Cross-sectional data on stablecoin characteristics

Abstract

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Data description

Table 1. Characteristics of stablecoins included in the database and their description.

Data availability

Underlying data

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