Predicting cryptocurrency defaults

ABSTRACT

We examine all available 146 Proof-of-Work-based cryptocurrencies that started trading prior to the end of 2014 and track their performance until December 2018. We find that about 60% of those cryptocurrencies were eventually in default. The substantial sums of money involved mean those bankruptcies will have an enormous societal impact. Employing cryptocurrency-specific data, we estimate a model based on linear discriminant analysis to predict such defaults. Our model is capable of explaining 87% of cryptocurrency bankruptcies after only one month of trading and could serve as a screening tool for investors keen to boost overall portfolio performance and avoid investing in unreliable cryptocurrencies.

KEYWORDS:

• Cryptocurrency
• bitcoin
• bankruptcy
• default
• credit risk

JEL CLASSIFICATION:

• G10
• G12
• G14
• G17

Acknowledgments

We would like to thank Simon Moore for a lively, interesting, and detailed discussion of our paper in the U.S. Business Magazine Forbes entitled “How To Tell If Your Cryptocurrency Will Go Bust” on 28 May 2019. Moreover, valuable comments were received from participants of the 2019 Graduate School Seminar at the University of Vaasa. We also received valuable comments from the 2019 Aalto University Graduate School of Finance Workshop at the University of Jyväskyla. In particular, we would like to thank Mika Veihekoski for an encouraging discussion and helpful comments. Furthermore, we are grateful for having received valuable comments from the 2019 Economics & Finance Seminar at Hanken School of Economics. Especially we would like to thank Timo Korkeamäki, Kenneth Högholm and Emilia Vähämaa for useful comments. Moreover, we received interesting comments from the participants from the 2019 Blockchain Seminar at the University of Vaasa. We would like to thank Robert Faff and the participants of the FINANCE, PROPERTY, TECHNOLOGY, AND THE ECONOMY CONFERENCE 2019, University of South Australia. Finally, we would like to thank an anonymous reviewer for helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The Bloomberg interview took place on 2 October 2014.

² The dead coin tracking website coinopsy.com lists the following as the main reasons for default: abandoned, abandoned/website, abandoned/volume, abandoned/buyback, abandoned/scam, scam, scam project/virus, joke, no exchanges/struggling, failed fork, failed/pre-mine no/low trade volume, pump and dump, and crashed (see https://www.coinopsy.com/dead-coins/).

³ See https://coinmarketcap.com (accessed on 15 February 2019, 11:00 EST).

⁴ Note that Howell, Niessner, and Yermack (2019, 1) define three types of coins, Figure 1 accounts for the whole universe of digital assets. For instance, as of 2014, 146 out of 517 coins were cryptocurrencies that have the Proof-of-Work consensus protocol which are subject of examination in this study.

⁵ It is also noteworthy that cryptocurrencies exhibit different types of consensus protocols to verify transactions such as Proof-of-Work, Proof-of-Stake or a mixture of both which is often referred to as Hybrid. Before 2015, however, there were only few cryptocurrencies issued that were implemented using the Proof of Stake (PoS) mechanism. PoS was first introduced by Sunny King and Scott Nadal in 2012 and later in 2013 Sunny King created the first cryptocurrency Peercoin (PPC) implementing the PoS protocol. PoS is created to solve the high energy consumption problem of Bitcoin which uses the Proof-of-Work mechanism. In order to keep our sample homogenous, we exclude those cryptocurrencies using a PoS mechanism from our sample.

⁶ We used the following sources: mapofcoins.com (name of the respective cryptocurrency, categorization of ‘running’ and ‘defunct’), coinmarketcap.com (historical price data), deadcoins.com (confirmation of the categorization ‘defunct’), coinopsy.com/dead-coins (life span and founder information of dead coins), bitcointalk.org (announcement date and other technical specifications), and personal websites of coins for gathering any missing data.

⁷ PoW is the very first consensus algorithm in decentralized public blockchains where miners solve complex cryptographic puzzles to add a block to a specific blockchain in exchange for coins as rewards.

⁸ We downloaded price history from the coinmarketcap.com. The earliest data provided by this website start on 28 April 2013. Though Bitcoin (BTC), Litecoin (LTC), Namecoin (NMC), Terracoin (TRC), Devcoin (DVC) and Novacoin (NVC) started trading before this date. To have uniformity and consistency across our data set; however, we set 28 April 2013 as the first day of trade for the above-mentioned coins.

⁹ There are a few cryptocurrencies in the list of functioning cryptocurrencies in coinmarketcap.com even though these cryptocurrencies do not exhibit any trading activities. In our data set, we adjusted for these errors.

¹⁰ See https://cryptodaily.co.uk/2018/08/premined-coins-like-xrp-trx-xlm-and-neo-are-causing-problems-for-index-funds (published on 29 August 2018).

¹¹ We categorized algorithms into three types: ‘SHA’ (Secure Hash Algorithm), ‘Scrypt’, and ‘others’. ‘Others’ contains all other algorithms besides SHA and Scrypt family algorithms.

¹² The average success rate of Altman’s (1968) model between year one and four prior to bankruptcy is 61%.

¹³ Note that Altman (1968, 592) highlights that ‘there is reason to believe that some of the measurements will have a high degree of correlation or collinearity with each other’.

¹⁴ Note, ${\mu }_1=\frac{\left(41.67+53.33\right)}{2}=47.50$, $\sigma =\frac{\left(53.33-47.50\right)}{1.96}=\frac{\left(58.33-52.50\right)}{1.96}=2.9745$,${\mu }_2=\frac{\left(46.67+58.33\right)}{2}=52.50$.

¹⁵ See footnote 8.