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Bitcoin and Altcoins Price Dependency: Resilience and Portfolio Allocation in COVID-19 Outbreak

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Bitcoin and Altcoins Price Dependency: Resilience and Portfolio Allocation in COVID-19 Outbreak risks Article Bitcoin and Altcoins Price Dependency: Resilience and Portfolio Allocation in COVID-19 Outbreak Ahmet Faruk Aysan 1,* , Asad Ul Islam Khan 2 and Humeyra Topuz 3 1 Islamic Finance and Economy Program, College of Islamic Studies, Hamad Bin Khalifa University, 34110 Doha, Qatar 2 Department of Economics, School of Humanities and Social Sciences, Ibn Haldun University, 34480 Istanbul, Turkey; [email protected] 3 Department of Business Administration, Universidad Carlos III de Madrid, 28001 Madrid, Spain; [email protected] * Correspondence: [email protected] Abstract: The main aim of this article is to examine the inter-relationships among the top cryptocur- rencies on the crypto stock market in the presence and absence of the COVID-19 pandemic. The nine chosen cryptocurrencies are Bitcoin, Ethereum, Ripple, Litecoin, Eos, BitcoinCash, Binance, Stellar, and Tron and their daily closing price data are captured from coinmarketcap over the period from 13 September 2017 to 21 September 2020. All of the cryptocurrencies are integrated of order 1 i.e., I(1). There is strong evidence of a long-run relationship between Bitcoin and altcoins irrespective of whether it is pre-pandemic or pandemic period. It has also been found that these cryptocurrencies’ prices and their inter-relationship are resilient to the pandemic. It is recommended that when the investors create investment plans and strategies they may highly consider Bitcoin and altcoins jointly as they give sustainability and resilience in the long run against the geopolitical risks and even in the tough time of the COVID-19 pandemic. Citation: Aysan, Ahmet Faruk, Asad Ul Islam Khan, and Humeyra Topuz. Keywords: bitcoin; altcoins; cointegration; price dependency; COVID-19 2021. Bitcoin and Altcoins Price Dependency: Resilience and Portfolio JEL Classification: C30; E58; G28; O35 Allocation in COVID-19 Outbreak. Risks 9: 74. https://doi.org/10.3390/ risks9040074 Academic Editor: Pawel Smaga 1. Introduction Bitcoin is known to be the first distributed cryptocurrency in the foremost tech- Received: 18 March 2021 nology of blockchain system, which was instigated by Satoshi Nakamoto in 2008. Be- Accepted: 6 April 2021 cause of this invention, more than two thousand cryptocurrencies adhere to Bitcoin. Published: 13 April 2021 These currencies are known as altcoins, which are traded non-stop, 24/7 in the crypto stock markets (CoinMarketCap 2019). Each of them has its own story which includes Publisher’s Note: MDPI stays neutral its mission, vision, and values. For instance, Ethereum is a global, open-source plat- with regard to jurisdictional claims in form from which investors can run their smart contracts for decentralized applications, published maps and institutional affil- (Ethereum White Paper 2019). As another example, even though Ripple’s system is based iations. on a central structure, Ripple aims to create a network among the international financial in- stitutions to decrease their transaction costs and to facilitate faster global payments. Unlike many other alt currencies, Ripple is working with governments and central financial insti- tutions (Ripple White Paper 2019). On the contrary, Binance was initiated to be an altcoin Copyright: © 2021 by the authors. to create an independent ecosystem by freeing users from central organizations and gov- Licensee MDPI, Basel, Switzerland. ernment regulations. In addition, on the infrastructure of Tron (TRX)’s system, investors or This article is an open access article users can freely create, publish, and store their data sets. By using this feature of blockchain distributed under the terms and infrastructure, Tron strives to create a global entertainment platform for content creators conditions of the Creative Commons and consumers in the blockchain-based decentralized platform, (Tron White Paper 2019). Attribution (CC BY) license (https:// After Bitcoin, these attempts of altcoins have brought about a sudden rise in the market size creativecommons.org/licenses/by/ of cryptocurrencies. Whilst many altcoins emerged after Nakamoto’s initiative. Bitcoin, 4.0/). Risks 2021, 9, 74. https://doi.org/10.3390/risks9040074 https://www.mdpi.com/journal/risks Risks 2021, 9, 74 2 of 13 Ethereum, Ripple, Litecoin, Eos, BitcoinCash, Binance, Stellar, and Tron have been ranked among the top 20 cryptocurrencies over time by market capitalization and considered mainstream coins (CoinMarketCap 2019). Especially after a sudden price increase of Bitcoin in 2017, people showed a great interest which has led to the rapid growth of cryptocurrencies. These attempts triggered scholars, crowdfunding managers, investors, and crypto portfolio managers to assess the long and short-term relationship among cryptocurrencies in the crypto stock market. A lot of studies were carried out to investigate about the price bubbles in cryptocurrencies in general especially Bitcoin, trading strategies and opportunities, financial bubbles being created by the crypto market, the spillovers between different crypto markets, and many more. Some of these studies are (Giudici and Pagnottoni 2019; Agosto and Cafferata 2020; Resta et al. 2020; J McNeil 2021) and many more. In addition, highly volatile cryptocur- rencies have high correlations. Therefore, the number of research papers has increased to figure out long-term co-movements of prices of different cryptocurrencies and mean- reverting strategies which analyze whether prices revert to the average or mean price, (Leung and Nguyen 2019). To construct meaningful and stable models, researchers use various variables and prediction techniques. (Chuen et al. 2017), for example, examined the possibility of diversification of cryptocurrency portfolio for investors as a new invest- ment opportunity based upon historical price and trading volume of a cryptocurrency. Accordingly, they found out that there is a low corrselation between cryptocurrencies and traditional investments. Another result showed that most cryptocurrencies have higher daily returns than traditional assets. Another strand of literature is about the possibility of cointegrating relationships among cryptocurrencies, which makes scholars keen to search for cointegration studies. Leung and Nguyen(2019) focused on the process of constructing cointegrated portfolios of cryptocurrencies by employing Johansen and Engle–Granger cointegration tests. In addition to that Bação et al.(2018) observed that a robust relationship exists between information transmission and Bitcoin, Litecoin, Ripple, Ethereum, and Bitcoin Cash prices by using the Vector Auto-Regression (VAR) modeling approach from 1 May 2013 to 14 March 2018. Their results suggest that Bitcoin has the power to dominate others regard- ing information transmission due to its paramount capacity of trading volume, market capitalization, and exchange trading volume. On the other hand, they found some counter- arguments against their hypothesis. Some delayed information takes place, especially from Litecoin to Bitcoin. Furthermore, the main aim of Ciaian and Rajcaniova(2018) empirical investigation was to assess the virtual relationships between Bitcoin and altcoins in the short and long run. Their empirical results conclude that Bitcoin and altcoin markets are interdependent based on daily data from 2013 to 2016. Their findings confirm that in the long run, macroeconomic indicators have an impact on price creation to a certain degree. Therefore, exogenous factors might be recognized as determinants to a certain extent for the crypto market. Furthermore, the ARDL technique was used by Sovbetov(2018), to reveal that the attractiveness of cryptocurrencies plays an important role in price formation solely in the long run. On the other hand, market beta, trading volume, and volatility (crypto market-related factors) matter for both long- and short-term price determination based on evidence from Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010–2018, using weekly data. Nicaise et al.(2019) examined the co-movements in market quality of cryptocurrencies by using intraday data of the transactions and order book of the cryp- tocurrencies which have the highest market capitalization from August 2017 to July 2018. Finally, Joline(2019) organized his analysis according to Engle-Granger two-step approach, Johansen Cointegration test, and Vector Error Correction Model (VECM) to demonstrate cointegration between Bitcoin and other altcoins; Ethereum, Ripple, Bitcoin Cash, EOS, and Litecoin based upon daily prices in five different periods that due is 9 April 2019. Findings prove that Bitcoin has cointegration with Ripple, Litecoin, Bitcoin Cash, and Ethereum, albeit not with EOS. Hence, he concluded that Bitcoin is statistically crucial for the price formation of Ripple, Litecoin, Bitcoin Cash, and Ethereum, but not EOS. Risks 2021, 9, 74 3 of 13 Overall, this paper highlights the need for new analysis to examine price dependency and long and short-term cointegration among all cryptocurrencies regarding different periods, as this crypto market continues to develop with its new coins, along with its new applications, regulations, and attractive narratives. More specifically the long-run relationship among Bitcoin and altcoins has not been assessed in presence of the current pandemic (COVID-19). Our paper contributes to this gap. Furthermore, the resilience of this long run relationship has not been tested in the literature. This paper is aimed to address these two issues. Our results reveals that some cryptocurrencies have
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