The valuation of cryptocurrencies is important given the increasing significance of this potential asset class. However, most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factors or sentiments and use out-of-date data sources. In this study, a robust cryptocurrency valuation method is developed using the up-to-date datasets. Using various panel regression models and moving-window regression tests, the impacts of fundamental factors and sentiments in the valuation of cryptocurrencies are explored with data covering from January 1, 2009 to April 30, 2023. The research shows the importance of sentiments and suggests that fear and greed index can indicate when to make cryptocurrency investment, while Google search interest of cryptocurrency are crucial when choosing the appropriate type of cryptocurrency. Moreover, consensus mechanism and initial coin offering have significant effects on cryptocurrencies without stablecoins, while their impacts on cryptocurrencies with stablecoins are insignificant. Other fundamental factors, such as the type of supply and the presence of smart contracts, do not have a significant influence on cryptocurrency. Findings from this study can enhance cryptocurrency marketisation and provide insightful guidance for investors, portfolio managers and policymakers in assessing the utility level of each cryptocurrency.
M.A. Ehyaei, A. Tofighi, Marc A. Rosen, Hamed Afshari ¡ 6 authors
Bitcoin, the first decentralized digital currency introduced by an anonymous person or group since 2008, has attracted worldwide attention. A significant number of economists have introduced Bitcoin as a new phenomenon in the 21st century that could reduce global inflation. Given the tens of thousands of digital currencies that have emerged since the advent of Bitcoin and its price growth trend over more than a decade, which are signs of the growth of this business. In addition to being money, Bitcoin has always been considered a tool for investing and storing value, which is why it is called digital gold. One of the most important problems in the production or extraction of Bitcoins is the high-power consumption by miners. If the energy sources of electricity generation are supplied by non-renewable energy sources, in addition to emitting air pollutant gases, it will increase greenhouse gases and consequently contribute to climate change. In this research, based on the idea of the authors, which is that the economic support of Bitcoin is energy, a strategy for producing Bitcoin from renewable energy sources is considered. First, the amount of electrical energy consumption by Bitcoin production is calculated based on statistical data, and then based on the price of electricity in different countries of the world and its global average, the base price of Bitcoin is calculated. In the following, four scenarios are proposed for the production of Bitcoin by electricity supplied from non-renewable energy sources. These scenarios include coal-fired steam power plants, natural gas-fired power plants, natural gas/oil gas-fired power plants, and dual-cycle (steam and gas cycles) natural gas-fired power plants. Based on the amount of electricity required to produce one Bitcoin, the amount of pollutants emitted to produce Bitcoin and its social costs are calculated. These costs should be added to the base cost of Bitcoin production if non-renewable energy sources are used to produce Bitcoin. Then, renewable energy sources for Bitcoin production based on the price of electricity generated by renewable energy sources are examined. Based on the analyses, how to choose the best renewable energy source to produce Bitcoin is presented as a scenario. This article briefly answers two key questions: 1. At what price of Bitcoin is it cost-effective for governments to produce it? 2. What is the best renewable energy source to produce it? These two questions can be useful in creating a roadmap and strategy for economists and governments.
Bitcoin is a newly created currency, which is also considered as âDigital Gold.â Whereas, Gold is a precious yellow metal. Bitcoins are more independent of the government than gold. Both gold and bitcoins are scanty resources, and thus, prices of both these assets appreciate or deteriorate depending on the demand and supply. An attempt was made to examine the association between prices of these two currencies. For this purpose, three different models were run: independent sample t-test, correlation analysis, and regression analysis. The outcomes of the independent sample t-test revealed that there exists a significant difference between the gold and bitcoin prices. However, the findings of correlation analysis show that movements in gold prices are statistically and positively linked to bitcoin prices. These findings indicate that gold prices move in the same direction as bitcoin prices. Further, the results of regression analysis also depicted that movement of bitcoin prices depends on movement of gold prices. Since its genesis, bitcoin prices have experienced around 37,418 appreciations, which make it an extraordinary currency. However, this study argued that bitcoin is establishing itself as an investment asset for the short term only because fluctuation in prices is very abnormal and unreliable in the long run. Moreover, robustness checks further show that gold prices are increasing at a steady rate, but increments are regular and trustworthy. Finally, the study found that bitcoin provides much higher returns to investors than gold. These results are crucial for the risk-taker investors who are looking for higher returns because bitcoins are getting growing public exposure day by day and attracting investments throughout the world.
Andreea-Elena DrÄgnoiu, Moritz Platt, Zixin Wang, Zhixuan Zhou
The energy consumption of popular cryptocurrencies varies greatly: cryptocurrencies based on proof-of-work (e.g. Bitcoin) consume much more electricity than their counterparts that use alternative consensus mechanisms, such as proof-of-stake (e.g. Ethereum). Nevertheless, proof-of-work cryptocurrencies dominate the market. We investigate whether energy labelling, i.e., displaying electricity consumption information on centralized exchanges, influences consumersâ product preferences. We conduct a control/treatment study: during this study, participants with an interest in cryptocurrencies (N = 200) are presented with a fictitious cryptocurrency exchange user interface. The treatment group is shown a user interface that displays energy labels, while the control group receives no information related to electricity consumption. Participants then declare how likely they are to acquire particular cryptocurrencies. We measure the treatment effect and find a significant negative correlation (p = 0.002) between being exposed to energy labels and expressing a strong preference for energy-ineďŹcient cryptocurrencies. Based on this finding, we reflect on the sustainability issues of cryptocurrencies and discuss how energy labelling on centralized exchanges can be applied to nudge investors away from energy-ineďŹcient cryptocurrencies. This indicates that regulators would be well advised to consider energy labelling to address the adverse climate impacts of cryptoassets.
We examine the reactions of the cryptocurrency market to two events that occurred during the escalation of the RussiaâUkraine war in February 2022. Using hourly data, we find that the escalation exerted a negative influence on both liquidity and returns. Interestingly, the actual escalation triggered a more pronounced drop than the threat of escalation shortly before. This contrasts with the stock market, where threats of geopolitical events are found to have a greater impact. Post-escalation, we observe indications of increased demand for cryptocurrencies, potentially as a means to circumvent Western sanctions imposed on Russia or to provide aid to Ukraine.
The main purpose of this paper is to investigate whether the cryptocurrency market affects financial stability and economic growth of India. The study used quarterly data on bitcoin, financial stability, inflation rate, real GDP, economic volatility uncertainty, exchange rate, and market volatility index for the period 2015Q1-2021Q4. The robustness of the findings was confirmed by the fully modified OLS (FMOLS) and canonical cointegration regression (CCR). The study results demonstrated that an increase in cryptocurrency investments will affect the financial stability of India significantly. Each 1% increase in the cryptocurrency would reduce the financial stability by 5% approximately. However, there was a marginal effect of cryptocurrency on economic growth. The results also found that exchange rate volatility and inflationary pressure would also deteriorate the financial stability of the country. Furthermore, the results also identified positive and significant cointegration between economic growth and financial stability. Due to most transactions in the economy being done through the financial system, it is paramount for economic growth. Going forward, aggressive monetary policy tightening, volatility in capital flows and exchange rates, deanchoring of inflation expectations, faltering in the economic recovery, disruptions due to global supply chains and climate change will be the major risks to the financial stability and economic growth of India.
Has there been a linkage mechanism between the prices of Bitcoin and traditional wealth preservation investment tools, that is, Bitcoin may serve as an investment substitute when other investment tool markets are sluggish, or can also benefit from it when the overall investment market is hot. The price of Bitcoin exhibits extremely unstable characteristics, as it can double its value dozens of times in a very short period of time or return to its starting point in a single day. The rapid rise and short duration of Bitcoin's price show us its infinite potential. Through research, this paper finds that the price of Bitcoin fluctuates greatly, while the U.S. Dollar Index and the S&P 500 index are basically horizontal, and their volatility is relatively small. Therefore, Bitcoin may be used as a speculative product, and there is a lot of speculative behavior in the market. When the investment attributes of Bitcoin dominate, an increase in economic policy uncertainty will significantly suppress investor sentiment and cause Bitcoin prices to decline. In addition, its impact on the world financial system is also increasing.
Purpose This paper aims to investigate the effects of volatility transmission among Bitcoin and other leading cryptocurrencies, namely, Binance USD, BNB, Cardano, Dogecoin, Ethereum, Polkadot, Polygon, Solana, Tether, USD Coin and XRP. Design/methodology/approach The multivariate BEKK-GARCH model is used with the daily data set from 1 January 2017 to 31 March 2023. The data set is analysed in its entirety and is also the COVID-19 epidemic period. Findings The study reveals that while the volatility of cryptocurrency prices is influenced by their own historical shocks and volatility, there is proof of the effects shock transmission among Bitcoin and other notable cryptocurrencies. Furthermore, the authors identify the spillover effects of volatility among all 11 pairs and provide evidence that conditional correlations with varying time constants are present, and predominantly positive for both the entire and COVID-19 outbreak periods. Practical implications The findings will be helpful to market experts who want to avoid losses in traditional assets. To develop the best risk management and hedging strategies, businesses might use the information to build asset portfolios or personalise payment methods. The use of such data by investors and portfolio managers could aid in the development of investment opportunities, risk insurance plans or hedging strategies for the management of financial portfolios. Originality/value To the best of the authorsâ knowledge, the use of the BEKK-GARCH model for examining the effects of volatility spillover among Bitcoin and the other eleven top cryptocurrencies has not been previously documented.
In view of the need for portfolio diversification, we investigate the interlinkages between a private equity ETF and a set of high-demand asset classes including bonds, equities, crude oil, gold, commodities, currency, Bitcoin, and shipping within a spillover framework. For this objective, we apply the enhanced modification of the Diebold and Yilmaz approach for the period 1 January 2010 to 31 January 2023. The empirical findings indicate a modest degree of connectedness among the investigated markets, whereas volatility spillovers showed acceleration during tumultuous periods. In addition, we assess the capacity of private equities for hedging, for the whole sample period and during COVID-19 infectious disease, in order to suggest investors for potential portfolio restructures. Results demonstrate that the short position in the volatility of private equity ETF can result in strong hedging effectiveness for investors holding long positions in Bitcoin, shipping, bonds, and crude oil. JEL Classification: C32, C58, G11, G15
Yunfei Yang, Jiamei Xiong, Lei Zhao, Xiaomei Wang ¡ 6 authors
Cryptocurrency prices have the characteristic of high volatility, which has a specific resistance to cryptocurrency price prediction. Therefore, the appropriate cryptocurrency price predictive method can help reduce the investment risk of investors. In this study, we proposed a novel prediction method using a fractional grey model (FGM (1,1)) to predict the price of blockchain cryptocurrency. Specifically, this study established the FGM (1,1) through the closing price of three representative blockchain cryptocurrencies (Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC)). It adopted the PSO algorithm to optimize and obtain the optimal order of the model, thereby conducting prediction research on the price of blockchain cryptocurrency. To verify the predictive precision of the FGM (1,1), we mainly took MAPE, MAE, and RMSE as the judging criteria and compared the modelâs predictive precision with the GM (1,1) through experiments. The research results indicate that within the data range studied, the predictive accuracy of the FGM (1,1) in the closing price of BTC, ETH, and LTC has reached a âhighly accurateâ level. Moreover, in contrast to the GM (1,1), the FGM (1,1) outperforms predictive capability in the experiments. This study provides a feasible new method for the price prediction of blockchain cryptocurrency. It has specific references and enlightenment for government departments, investors, and researchers in theory and practice.
Iulia Cioroianu, Shaen Corbet, Charles Larkin, Les Oxley
Using estimated sentiment indices based on CBDC-related social media posts, and testing for the effects of regulatory-related announcements upon blockchain and cryptocurrency-related funds, this research presents two key findings: first, the continued evolution of the pricing structures of digital finance products to respond to such perceived threats constitutes a further evolutionary point in the product's life-cycle. However, secondly, the very fact that returns fall while volatility increases, indicates a largely negative market response to the threat of potential external regulation of cryptocurrencies in the future. The nature of this negative response validates concerns that anonymity continues to be a central attractive feature for cryptocurrency stakeholders, further verifying the necessity for third-party oversight.
Blanka Ĺ krabiÄ PeriÄ, Petar SoriÄ, Ivana JerkoviÄ
This paper aims to examine the behavioural determinants of Bitcoin trading volume within a cross-country framework of 14 world economies plus the Eurozone. We introduce a basic taxonomy of behavioural indicators, distinguishing between consumer confidence, economic policy uncertainty (EPU), and indicators of financial volatility. Our estimations reveal that the Bitcoin trading volume can be predicted more accurately by EPU than by any other class of indicators. Finally, we identify the COVID-19 shock as a catalyst for a psychologically-driven Bitcoin market and find evidence that Bitcoin was a macro hedging instrument in the pandemic. To obtain our results, we conducted a panel Granger causality test, employing the Least Squares Dummy Variables (LSDV) estimator. Contrary to previous research, we found that market fundamentals (industrial production and equity market volume) became significant drivers of Bitcoin trading during the pandemic. This conclusion was preserved when we used the LSDV corrected estimator, which is more suitable for panels with a smaller time dimension. Apart from the practical implications for traders, this paper provides researchers with detailed steps for applying Granger causality testing in panel data settings.