We analyze the path from cryptocurrencies to official Central Bank Digital Currencies (CBDCs), to shed some light on the ultimate dematerialization of money. To that end, we made an extensive search that resulted in a review of more than 100 academic and grey literature references, including official positions from central banks. We present and discuss the characteristics of the different CBDC variants being consideredânamely, wholesale, retail, and, for the latter, the account-based, and token-basedâas well as ongoing pilots, scenarios of interoperability, and open issues. Our contribution enables decision-makers and society at large to understand the potential advantages and risks of introducing CBDCs, and how these vary according to many technical and economic design choices. The practical implication is that a debate becomes possible about the trade-offs that the stakeholders are willing to accept.
This study is an integrated survey of GARCH methodologies applications on 67 empirical papers that focus on cryptocurrencies. More sophisticated GARCH models are found to better explain the fluctuations in the volatility of cryptocurrencies. The main characteristics and the optimal approaches for modeling returns and volatility of cryptocurrencies are under scrutiny. Moreover, emphasis is placed on interconnectedness and hedging and/or diversifying abilities, measurement of profit-making and risk, efficiency and herding behavior. This leads to fruitful results and sheds light on a broad spectrum of aspects. In-depth analysis is provided of the speculative character of digital currencies and the possibility of improvement of the riskâreturn trade-off in investorsâ portfolios. Overall, it is found that the inclusion of Bitcoin in portfolios with conventional assets could significantly improve the riskâreturn trade-off of investorsâ decisions. Results on whether Bitcoin resembles gold are split. The same is true about whether Bitcoins volatility presents larger reactions to positive or negative shocks. Cryptocurrency markets are found not to be efficient. This study provides a roadmap for researchers and investors as well as authorities.
The study investigates the safe haven properties and sustainability of the top five cryptocurrencies (Bitcoin, Ethereum, Dash, Monero, and Ripple) and gold for BRICS stock markets during the COVID-19 crisis period from 31 January 2020 to 17 September 2020 in comparison to the precrisis period from 1 January 2016 to 30 January 2020, in a nonlinear and asymmetric framework using Nonlinear Autoregressive Distributed Lag (NARDL) methodology. Our results show that the relationship dynamics of stock market and cryptocurrency returns both in the short and long run are changing during the COVID-19 crisis period, which justifies our study using the nonlinear and asymmetric model. As far as a sustainable safe haven is concerned, Dash and Ripple are found to be a safe haven for all the five markets before the pandemic. However, all five cryptocurrencies are found to be a safe haven for three emerging markets, such as Brazil, China, and Russia, during the financial crisis. In a comparative framework, gold is found to be a suitable safe haven only for Brazil and Russia. The results have implications for index fund managers of BRICS markets to include Dash and Ripple in their portfolio as safe haven assets to protect its value during a stock market crisis.
This study investigates the performance of Bitcoin as a diversifier under different constraining portfolio optimization frameworks. The study employs different constraining optimization frameworks that seek to maximize risk-adjusted returns (Sharpe ratio) of the portfolio by optimizing allocations to each asset class (asset allocation). The performance attributes are evaluated by comparing the portfolios both with and without Bitcoin under frameworks ranging from equal-weighted, risk-parity, and semi-constrained to unconstrained. This study suggests that Bitcoin, due to its exotic nature, unwavering appeal, and unknown set of drivers, could act as a diversifier in normal market conditions, and it might also have some borderline hedge to safe haven properties. The results further suggest that while Bitcoin may be a potential diversifier for a risk-seeking investor, the risk-averse investor must exercise caution by limiting their exposure to Bitcoin in their portfolios, as unnecessary exposure may increase the probability of losses in extreme market conditions.
Purpose In addition to leading a new tide of global financial technology, blockchain delivers advantages in terms of risk control compared to traditional financial systems. By exploring the relationship between blockchain technology and macroeconomic uncertainty, this study aims to identify the hedge risk attribute of blockchain technology. Design/methodology/approach From a data set comprising 6,323 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges in 2015â2018, the authors obtain the use of blockchain technology by listed companies on the basis of annual reports, news reports, search engines and prospectuses. These documents are then subjected to text analyses based on computer technology. Cross-sectional and propensity score matching analyses are used to ensure robustness. Findings The empirical results show that with an increase in macroeconomic uncertainty, blockchain technology can potentially enable companies to reduce their systemic risks and enhance their investment efficiency. Originality/value This study expands the literature on the application of blockchain technology, offers references for enterprises to address future risks based on specific macroeconomically uncertain environments and provides guidelines for governments to maintain financial market stability.
In today's technology-oriented world, electronic devices are becoming increasingly important for everyone. Because of this, the emergence of cryptocurrency seems natural. Thus, there is an urgent need to understand the impact brought by cryptocurrency to the world financial system. As a type of currency, how will the cryptocurrency influence the other types of traditional currency? We use data related to Bitcoin to illustrate the connection between those two types of currency. By applying machine learning to the data, we found out that there is scarcely any correlation between Bitcoin value and conventional currency value, with the exception of the USD. With this result, we hope to contribute to the establishment of a better currency system and therefore, provide the world with a healthier economic environment. At the same time, the economic society may get a clearer understanding of the interrelationship between the new currency---Bitcoin and several typical examples of conventional currency. Meanwhile, throughout the research, we can acknowledge the main difference on investing strategies between conventional currencies and cryptocurrencies, which will therefore, help us make a wiser decision when it comes to the purchases of money power.
Hashem Abdullah AlNemer, Besma Hkiri, Muhammad Asif Khan
This study attempts to investigate the nexus between investor sentiment and cryptocurrencies prices. Our empirical investigation merges bivariate and multivariate wavelet tools to examine the investor sentiment nexus to inter-cryptocurrencies prices. The study outcomes show that the Sentix Investor Confidence index provides significant information in explaining long-term changes in Bitcoin and Litecoin prices. Moreover, the findings generated from the multiple wavelet coherence illustrate the simultaneous contribution of cryptocurrencies and the Sentix Investor Confidence index in explaining the Bitcoin index movement across frequencies and over horizons, especially during bubble burst periods. The study also suggests a time-dependent relationship of Bitcoin prices with alternative cryptocurrencies and the Sentix Investor Confidence index, mostly pronounced during the Bitcoin bubble. We discuss our results using GSV-based investor sentiment. Our findings remain robust and confirm the strong predictive power of investor sentiment in cryptocurrencies price movements over time and across scales.
Purpose The purpose of this paper is to examine empirically the impact of COVID-19 pandemic news in USA and in China on the dynamic conditional correlation between Bitcoin and Gold. Design/methodology/approach This paper offers a crucial viewpoint to the predictive capacity of COVID-19 surprises and production pronouncements for the dynamic conditional correlation (DCC) among Bitcoin and Gold returns and volatilities using generalized autoregressive conditional heteroskedasticity-DCC-(1,1) through the period of study since July 1, 2019 to June 30, 2020. To assess the unexpected impact of COVID-19, this study pursues the Kuttnerâs (2001) methodology. Findings The empirical findings indicate strong important correlation among Bitcoin and Gold if COVID-19 surprises are integrated in variance. This study validates the financialization hypothesis of Bitcoin and Gold. The correlation between Bitcoin and Gold begin to react significantly further in the case of COVID-19 surprises in USA than those in China. Originality/value This paper contributes to the literature on assessing the impact of COVID-19 confirmed cases surprises on the correlation between Bitcoin and Gold. This paper gives for the first time an approach to capture the COVID-19 surprise component. Also, this study helps to improve financial backers and policymakers' comprehension of the digital currencies' market elements, particularly in the hours of amazingly unpleasant and inconspicuous occasions.
The volatility of bitcoin (BTC) and time horizon is the center point for investment decisions. However, attention is not often drawn to the relationship between BTC and equity indices. Thus, the purpose of this paper is to investigate the volatility and time frequency domain of BTC with stock markets.
Samet GĂŒnay, Kerem KaĆkaloÄlu, Shahnawaz Muhammed
This study examines the interaction of Bitcoin with fiat currencies of three developed (euro, pound sterling and yen) and three emerging (yuan, rupee and ruble) market economies. Empirical investigations are executed through symmetric, asymmetric and non-linear causality tests, and Markov regime-switching regression (MRSR) analysis. Results show that Bitcoin has a causal nexus with Chinese yuan and Indian rupee for price and various return components. The MRSR analysis justifies these findings by demonstrating the presence of interaction in contractionary regimes. Accordingly, it can be stated that when markets display a downward trend, appreciation of the Chinese yuan and Indian rupee positively and strongly affects the value of Bitcoin, possibly due to the market timing. The MRSR analysis also exhibits a transition from a tranquil to a crisis regime in March 2020 because of the pandemic. However, a shorter duration spent in the crisis regime in 2020 indicates the limited and relatively less harmful effect of the pandemic on the cryptocurrency market when compared to the turmoil that occurred in 2018.
Since the creation of Bitcoin, the adequacy of data in the cryptocurrency market has not been widely analysed by scholars. Indeed, the research conducted by Alexander and Dakos (2020) is the only one that has focused on the properties and differences of several data sources, underlining inconsistencies in the time series of prices. In our paper, we contribute to this strand of the literature by examining one of the main features of digital currencies: the cryptocurrency market never sleeps. Given that cryptocurrencies trade on a 24/7 basis, specialised crypto companies offer two kinds of prices (close and weighted prices) to proxy Bitcoin daily prices. However, scholars and practitioners have not considered this issue in their analyses. We show that these prices are statistically different, which affects the financial decisions of investors and the most relevant fields in the cryptocurrency market (efficiency, risk management and volatility forecasting). Therefore, our paper demonstrates that the data processing used by specialised crypto firms is a relevant issue that changes the underlying mechanism of Bitcoin data, affecting the results of investors and scholars.
Pavel Ciaian, dâArtis Kancs, Miroslava RajÄĂĄniovĂĄ
We studied the extent to which bitcoin blockchain security permanently depends on the underlying distribution of cryptocurrency market outcomes using daily blockchain and bitcoin data for 2014â2019 and employing the autoregressive-distributed lag (ARDL) approach. We tested three equilibrium hypotheses: (i) sensitivity of the bitcoin blockchain to mining reward, (ii) security outcomes of the bitcoin blockchain and the proof-of-work cost, and (iii) the speed of adjustment of the bitcoin blockchain security to deviations from the equilibrium path. Our results suggest that bitcoin price and mining rewards were intrinsically linked to bitcoin security outcomes.The bitcoin blockchain securityâs dependency on mining costs was geographically differenced â it was more significant for the global mining leader China than for other world regions. Bitcoin blockchain security tended to revert relatively fast to its equilibrium security level after the input or output of price shocks.
This paper examines interlinkages and hedging opportunities between nine major cryptocurrencies for the period between 30 September 2015 and 4 June 2020, which notably includes the coronavirus disease 2019 (COVID-19) outbreak lasting from early 2020 through the end of the sample period. The results of dynamic conditional correlation (DCC) analysis using a minimum connectedness approach show a high degree of correlation between cryptocurrencies throughout the sample period. However, the correlations reach their minimum values during the COVID-19 pandemic, which indicates that cryptocurrencies acted as a hedge or safe haven during the stressful period of the COVID-19 pandemic. The weight of cryptocurrencies was significantly reduced and their hedging effectiveness varied greatly during the pandemic, which indicates that investors’ preferences changed during the COVID-19 period.
In this paper, the HestonâNandi futures option pricing model is applied to Bitcoin futures options. The model prices are compared to market prices to give an indication of the pricing performance. In addition, a multivariate Bitcoin futures option pricing methodology based on a multivatiate GARCH model is developed. The empirical results show that a symmetric model is a better fit when applied to Bitcoin futures returns, and also produces more accurate option prices compared to market prices for two out of three expiry dates considered.
Abstract Stablecoins are a rapidly evolving subcategory of cryptocurrency that aim to reduce the price fluctuations of traditional cryptocurrencies and thus become a common digital payment instrument. This paper aims to assess the material substance of fiatâbacked stablecoins to determine whether fiatâbacked stablecoins could be considered, in accordance with IFRS, as cash or cash equivalents. We chose 11 fiatâbacked stablecoins representing 99.97% of the total market capitalisation of all fiatâbacked stablecoins. Using a threeâstep approach, we performed an analysis of the legal and general terms and conditions of the selected stablecoins and of cryptocurrency exchanges, and quantitatively analysed their risk characteristics in comparison with fiat currency pairs, money market indexes and instruments, and traditional cryptocurrencies. The results show that nine of the 11 stablecoins met the objective requirements of cash equivalents according to their material substance and, using an extensive interpretation of IAS 7, could be reported as cash equivalents. This study enhances understanding of the material substance of fiatâbacked stablecoins for their financial reporting and can be used by entities when creating accounting policies under existing IFRS rules and by accounting standard setters as evidence when formulating new rules or officially interpreting existing ones to provide guidance on the financial reporting of fiatâbacked stablecoins.