Are Bitcoin and Ether Affected by Strictly Anonymous Crypto-Currencies? An Exploratory Study.

• Author: Schinckus, Christophe

1. Introduction

   There is an increasing number of works investigating the pros and cons of Bitcoin and other crypto-currencies (Polasik et al., 2015; Thies and Molnar, 2018). This growing literature mainly focuses on the financial characteristics of crypto-currencies or their relationship with economic or energetic indicators (Schinckus et al., 2020; Schinckus, 2020; 2021). This article takes another angle by investigating the extent to which the major strictly anonymous crypto-currencies (Monero, Dash, Verge, Zcash, and Bitcoin Private) can partly explain/influence the dynamics of the two most important pseudo-anonymous crypto-currencies: Ether and Bitcoin. It is important to understand that the vast majority of existing crypto-currencies are not really anonymous but instead pseudo-anonymous in a sense that, even though these digital assets do not require traders to use their real names to operate, there is still a way of tracking their exchanges. For instance, Bitcoin and Ether addresses are public key hashes rather than real identities so that they offer a form of anonymity--however, this public hashes are still traceable since it is possible to identify all exchanges made by the same users. Strictly anonymous crypto-currencies compile pseudo-anonymity with un-linkability in a way that all interactions of the same users with the system are not linkable to each other. In other words, strictly anonymous crypto-currencies offer a particular technical configuration in which the money is not tied to a person or a trader but instead to particular computational keys/addresses that can be hidden in the exchanges.

   Our study is exploratory simply because we mainly focus on the identification of the empirical relationships between strictly anonymous and pseudo-anonymous crypto-currencies while the technological/economic reasons explaining these links might be much more complex. In this context, this article can be seen as the first step of a research aiming at investigating the nature of the potential interaction/relationship between Ether/Bitcoin and strictly anonymous crypto-currencies. An analysis of the influence of the latter is timely given the growing importance of Bitcoin and Ether (related to Ethereum platform and its smart contracts); it is essential to estimate if there exist potential manipulation of these markets through the use of another crypto-asset that would ensure the traders' anonymity. We select here the five major strictly anonymous crypto-currencies to study the extent to which traders might be tempted to take positions on these crypto-currencies markets to influence their strategy on pseudo-anonymous market (such as Bitcoin (BTC) or Ether (ETH)). With this purpose, our study analyses the dynamics of the BTC and ETH (returns and volatility spillover) with the five most important anonymous crypto-currencies including Moreno (XMR), Dash (DASH), Verge (XVG), Zcash (Zcash), and Bitcoin private (BTCP). (1) More detailed information about these assets are provided in the section dedicated to our methodology.

   This paper contributes to the rapidly extending literature on crypto-currencies. The main contribution of the paper is that it looks at the dynamic interdependence among various crypto-currencies by using different methods to identify structural breaks (where the literature typically focuses on either one crypto-currency or one method). Our study offers some new insights into the dynamics of crypto-currency markets especially in the distinction between pseudo and strictly anonymous crypto-currencies.

   The article is structured as follows. The next section will present an overview of the major studies dealing with Bitcoin and Ether dynamics while the third section will present our methodology and data. The fourth section will discuss our results before concluding this study with some recommendations in the fifth section.

2. Literature Review

   The global development of crypto-currencies generated a lot of debates (Alvarez-Ramirez et al., 2018; Balcilar et al., 2017; Brandvold et al., 2015; Brauneis and Mestel, 2018; Jiang et al., 2018; Koutmos, 2018; Takaishi, 2018; Van Vliet, 2018). Roughly speaking, the studies dealing with crypto-currencies can be classified into two categories: those focusing on their financial behaviour and those studying their relationships with economic indicators. Being the first crypto-currency, Bitcoin has been widely analysed in the literature. Cheah and Fry (2015) explained that Bitcoin does not have a fundamental value and it appears to be driven by speculative bubbles. Corbet et al. (2017) acknowledged there are some speculative periods in the Bitcoin and Ether behaviour, however, the authors added that these crypto-currencies are also partly related to some real economic indicators. Su et al. (2018) confirmed this claim by studying the Bitcoin's prices dynamics during speculative period in the US. Tan et al. (2020) offered a volatility-based measure to capture the speculative nature of crypto-currencies whereas Siswantor et al. (2020) discussed the ethical debates raging on the speculative dimensions of crypto-currencies.

   Regarding the potential relationship between crypto-currencies and economic indicators (such as stock markets, gold, oil), Baur et al. (2018) showed that Bitcoin's dynamics exhibits independent behaviour compared to other assets such as gold and the US dollar. Ciaian et al. (2018) documented that macro-financial indicators might determine the altcoin price formation to a slightly greater degree than Bitcoin does in the long-run, suggesting that this crypto-currency is related to real economic indicators. Demir et al. (2018) explained that Bitcoin could be used in hedging strategy against stocks in the Financial Times Stock Exchange Index and against the American dollar. On the hedging nature of Bitcoin, Al Mamun et al. (2019) explained that global economic policy uncertainty appears to be a factor explaining the Bitcoin risk profile-however, on this point, Shaik (2020) documented that Bitcoin returns can also be the origin of a national economic uncertainty (with a negative effect in the US and in Japan but a positive one in China). Arouri et al. (2016) or Fang et al. (2019) found that Bitcoin could be a good hedging instrument during a context of decreasing market. Another study (Paule-Vianez et al., 2020) showed that Bitcoin's dynamics adopts a similar pattern than gold suggesting that Bitcoin could be perceived as a safe investment. Wu et al. (2019) nuanced this claim by documenting that neither gold nor Bitcoin can be used as a good hedging asset against economic policy uncertainty-these authors also listed the major differences between Bitcoin and gold indicating that these two assets could not be compared. Klein et al. (2018) confirmed this perspective by explaining that Bitcoin cannot play a hedging role in times of market distress as it appears to be positively correlated with downward markets.

   The second strand of the existing literature mainly focused on the interaction between crypto-currencies. Kyriazis et al. (2019) documented a strong interrelation between the 5 largest crypto-currencies while Nguyen et al. (2019) extended these results to other digital assets. Schinckus et al. (2020) used network analysis to show the moving nature of the interrelation between crypto-currencies. Ciaian et al. (2018) observed that Bitcoin and other crypto-currencies' prices are interdependent especially in the short-run. Guidici et al. (2019) discussed the fundamental value of crypto-currencies and the extent to which they should/could be related to economic indicators while Ali Nasir et al. (2019) explained that significant statistical links can be found between crypto-currencies' prices and the search engines enquiries.

   Qi et al. (2019) documented that the connectedness between six crypto-currencies is larger via their negative returns than their positive ones. Other studies (Qureshi et al., 2020; Bouri et al., 2021a; 2021b; Naeem et al., 2021; Shahzad et al., 2021) found evidence of asymmetry, tail dependency and time scales in the relationship between crypto-currencies. However, all the aforementioned studies do not make any distinction between pseudo-and strictly anonymous crypto-currencies. This is the key contribution of this article-to our knowledge, the only existing research on this matter is Griffin and Shams (2020) who explained that a particular crypto-currency named Tether influenced other crypto-currencies during the 2017 boom suggesting some potential manipulations of the markets.

   This article contributes to the second strand of literature by investigating the relationship between the five largest strictly anonymous crypto-currencies with the two biggest pseudo-anonymous ones. The following section presents our data and the way we treat them.

3. Methodology and Data

   To identify potential patterns connecting the five most important anonymous crypto-currencies and the two most important pseudo-anonymous ones (Bit-coin, BTC, and Ether, ETH); we examine their relationship in terms of returns but also volatility spillovers. The five anonymous crypto-currencies are the following: Moreno (XMR), Dash (DASH), Verge (XVG), Zcash (Zcash), and Bitcoin private (BTCP); (2) which are ranked as 14th, 19th, 86th, 26th, 1007th in term of market capitalization, (3) respectively. We collected the daily closing prices of each crypto-currency from the website "coinmarket.com,"-we then clean our data to ensure that we do have a consistent set of data. Given the availability of data, the best period of study is from 07Aug2015 (first day of ETH) to 19 Apr 2020. We treat our data by using a common methodology: the price is taken in their logarithmic form and expressed in their 1st difference to form the daily return of crypto-currency (Dyhrberg, 2016; Katsiampa, 2017; Nguyen et al., 2019). This process also helps in reducing the fluctuation in...