No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
Cryptocurrency Value Formation: An empirical study leading to a cost of production model for valuing Bitcoin
Abstract
This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all Bitcoins in existence represent approximately $7 billion, and more than $60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.
... Finally, the crypto industry as a whole is known for its price fluctuations and trading volumes. With the growing interest in cryptocurrencies and their importance in the financial sector, extensive research and forecasting of cryptocurrencies' volatility dynamics is needed [3]. ...
... In essence, the results said that there is potential predictability within the cryptocurrency trading process. Their findings were consistent with which earlier research in 2017 (Hayes et al [3]) that demonstrated the impact of external factors on cryptocurrency predictability. ...
... The impact of the three factors on cryptocurrency value was studied by Hayes et al [3] using cross-sectional data from 66 of the most commonly used cryptocurrencies. The factors are competition levels in the producers' network, production rates of the unit, and the algorithm difficulty used to mine crypto-monetary activity. ...
... As inputs, our DNN admits a comprehensive range of factors previously found to drive Bitcoin prices in different currencies, such as (i) fundamental factors advocated by monetary economics (e.g., its usage in trade, money supply, or price level), (ii) factors driving investors' interest in/attention to the crypto-currency (e.g., speculation or Bitcoin's role as safe haven); and (iii) exchange rate hedging motives (see Kristoufek 2015;Liu and Tsyvinski 2018;McNally et al. 2018;Jang and Lee 2017), together with (iv) novel supply-side factors for both Bitcoin and ASIC mining chips producers, related to for-profit mining decisions, but excluding those employed in the construction of the upper and lower limits. Aggregated at the yearly frequency, we found Bitcoin mining energy consumption, ranging between 5.2 and 56.8 TWh in 2017, between 25.1 and 93.3 TWh in 2018 and between 27.1 and 91.1 TWh in 2019 according to Hayes' (2017) upper and lower bounds. Obtaining mean point estimates of daily power consumption within those economically meaningful limits provides substantial gains in accuracy relative to recent contributions in the literature, while externally validating our ML approach. ...
... Obtaining mean point estimates of daily power consumption within those economically meaningful limits provides substantial gains in accuracy relative to recent contributions in the literature, while externally validating our ML approach. 4 Crucially, our novel approach also enables the construction of prediction intervals (PIs) around the estimated carbon footprint of Bitcoin mining, substantially narrowing down the associated uncertainty, currently measured by the difference between the carbon footprint of Hayes' (2017) upper and lower bounds, capturing the difference between the expected marginal revenue and the marginal cost of Bitcoin network operating miners. When aggregated at a yearly frequency, the corresponding CO 2 estimates (and associated 0.95 PIs) are, for the year 2017, 2.77 [1.98, 3.56] MtCO 2 e; for 2018, 16.08 [14.19, 17.97] MtCO 2 e; and, for 2019, 14.99 [13.25, 16.73] MtCO 2 e. ...
... As an example, "A hashrate of 14 terahashes per second (TH/s) can either come from a single Antminer S9 running on just 1372 W, or more than half a million PlayStation-3 devices running on 40 MW (as a single PlayStation-3 device has a hashrate of 21 megahashes per second and a power use of 60 W)" (De Vries 2018). To estimate a realistic level of daily electricity consumption to produce Bitcoins based on a feed-forward neural network, we first calculated a lower and an upper limit (Hayes 2017) within which our mean predicted electricity consumption must "travel" between the 1 January 2017 and the 1 January 2020. The lower limit corresponds to the lowest marginal cost for mining Bitcoins and is defined by a scenario in which all miners use the most efficient available hardware. ...
Building on an economic model of rational Bitcoin mining, we measured the carbon footprint of Bitcoin mining power consumption using feed-forward neural networks. We found associated carbon footprints of 2.77, 16.08 and 14.99 MtCO2e for 2017, 2018 and 2019 based on a novel bottom-up approach, which (i) conform with recent estimates, (ii) lie within the economic model bounds while (iii) delivering much narrower prediction intervals and yet (iv) raise alarming concerns, given recent evidence (e.g., from climate–weather integrated models). We demonstrate how machine learning methods can contribute to not-for-profit pressing societal issues, such as global warming, where data complexity and availability can be overcome.
... However, the immutable nature of smart contract code is a double-edged sword providing user guarantees yet at the cost of inability to fix code deployed that may have software bugs within (of which ramifications are further discussed herein). The most popular instances of public blockchains that provide cryptocurrencies -which have become a novel financial asset class with increasingly large market valuation [5]. The definition of cryptocurrencies varies among jurisdictions. ...
... The definition of cryptocurrencies varies among jurisdictions. At EU level, as part of the most recent EU regulatory proposals, "digital representations of value or rights which may be transferred and stored electronically, using distributed ledger technology" are referred as crypto-assets 5 . In this article we use the terms crypto-assets and cryptocurrencies inter changeably. ...
Blockchain technology has taken off rapidly in the last decade, as blockchain-based applications have expanded across sectors and acquired substantial global user support. This rise has been accelerated in the domain of cryptocurrencies, as one of blockchains' most famous (or infamous) applications. This relatively novel type of a financial asset class with increasingly large market valuation has sparked the interest of regulators and law makers. As a means of fostering fintech innovation, the EU has stated its support for adoption and development of blockchain and cryptocurrencies in the European Economic Area. Nevertheless, cryptocurrencies lie at the top of a potentially dangerous feedback loop mediated by market valuation. Cyber-attacks targeting cryptocurrencies (and the underlying blockchain technology) have been on the rise, costing users and businesses millions of euros. From a European Union regulatory standpoint, high cyber security resilience is a precondition for sustainable innovation in an increasingly digitalized financial sector, where protecting users and businesses is a priority. In this paper, we discuss aspects of blockchains' technical vulnerabilities and related cyber-attacks in order to develop a deeper understanding of the extent and efficiency of possible regulatory remedies concerning crypto-assets in the EU. We present a regulatory overview of the emerging fields of cyber risk and blockchain in Europe and illustrate a techno-regulatory gap which requires further attention. We underline the difficulty of assigning traditional cyber regulatory measures due to certain technical characteristics related to blockchains. We maintain how the relationship between cyber law and technology may evolve in the near future, as decentralized technologies and the cyber risks that go with them, continue to develop rapidly. By providing an interdisciplinary perspective of cyber security in the blockchain domain, we aim to bridge the gap that exists between legal and technical research, supporting policy makers in their regulatory decisions concerning crypto-assets, decentralized technologies and associated cyber risks.
... One of the most significant works in terms of assessing the fair value of bitcoin and cryptocurrencies built on its source code is the work of A. S. Hayes [9], in which the author demonstrated that the value of the marginal cost of mining can be used as an estimate of the fundamental value. ...
... In the period after the collapse of the bubble in the cryptocurrency market and before the start of the recession in the financial markets 9 Hereinafter, it is calculated analytically depending on how many percent is one standard deviation of the value compared to the mean. Table 7). ...
The cryptocurrency market debate resumed in 2020 with renewed vigour as the price of Bitcoin surpassed late 2017 highs. This study aims to analyse possible factors of Bitcoin’s pricing at various cryptocurrency market development stages — before the 2017 price bubble, after and during the COVID-19 pandemic. The main method of analysis is a generalized autoregressive conditional heteroskedasticity model with conditional generalized error distribution (GARCHGED). Two groups of indicators are used as possible factors related to the Bitcoin dynamics. The first group consists of various quantitative indicators directly related to Bitcoin (the so-called internal factors) — the volume of exchange trade, the volume of transactions in the Bitcoin blockchain, the number of new and active wallets, hash rate, the sum of fees paid in the blockchain, as well as the dynamics of Google Trends search queries. The second group is the return on various financial assets — stock and bond indexes, commodities, and currency markets. The results of the analysis demonstrate the absence of a stable correlation between any of the factors under consideration and Bitcoin returns in all the periods that we focus on. In the period before the 2017 price bubble, the internal factors and Bitcoin returns showed generally co-directional dynamics, but the situation changed in 2018. In early 2021, the correlation between Bitcoin and traditional financial assets returns has increased significantly. We can conclude that Bitcoin is becoming a popular means of diversification as a high-risk asset, which, however, follows the pattern of a speculative bubble at the beginning of 2021. The increased demand for the need to invest in Bitcoin using various exchange-traded instruments (ETFs for cryptocurrencies) may soon lead to a further increase in the price of this cryptocurrency if such instruments are registered on the exchange.
... Empirical findings using the novel ARDL reveal the volume of trading all cryptocurrencies has significant positive effect on energy consumption in both short and long run-with long-term consequence on the environment and energy sector (Schinckus et al. 2020). It is reported that the reduction in production cost drivers of cryptocurrencies that improves energy efficiency of mining hardware, have cheaper worldwide electricity prices, and lower mining difficulty could indirectly have a negative impact on the price of cryptocurrencies (Hayes 2017). A study suggests the average mining efficiency was 500 W per GH/s throughout 2010-2013 (Garcia et al. 2014). ...
... A study suggests the average mining efficiency was 500 W per GH/s throughout 2010-2013 (Garcia et al. 2014). However, another study recorded the average mining energy efficiency across different mining networks around 0.40 W per GH/s (Hayes 2017). The study argued that cryptocurrency mining consumes significant amount of energy for proof-of-work to add new blocks to the chain. ...
When bitcoin (BTC), the first pioneering cryptocurrency was released in 2009, it was considered an apolitical currency. Besides, the possible effect of BTC and other cryptocurrencies on either financial markets or transactions has been widely discussed. However, the environmental effects of cryptocurrency demand have been ignored. Here, this study examines the nexus between cryptocurrencies and environmental degradation by employing standard and asymmetric causality methods. The Toda-Yamamoto and bootstrap-augmented Toda-Yamamoto test results reveal Bitcoin and Ethereum (ETH) excluding Ripple (XRP) have causal effects on environmental degradation. The Fourier-augmented Toda-Yamamoto test results show causal effects running from Bitcoin and Ripple to environmental degradation, whereas no causal effect runs from Ethereum to environmental degradation. The asymmetric causality shows causal effects from the positive shock of Bitcoin demand, negative shocks of Ripple and Ethereum demands to positive shocks of environmental degradation. Further discussions and policy implications are provided in the relevant sections of this study.
... Our theoretical framework and taxonomy of digital products can also shed light on the empirical side of the literature. Some empirical studies have attempted to gain insights into the nature of Bitcoin by analysing its price and transaction patterns, in some cases also establishing a comparison across a range of asset classes (as in Hayes 2017, Abbatemarco et al. 2018, Baur et al. 2018, Gronwald 2019, Baldan and Zen 2020, White et al. 2020. These empirical works aim to provide clues about the properties of Bitcoin by identifying common pricing patterns relative to a vast array of commodities, assets, and securities. ...
... The profits accruing to digital miners are in fact redistributions of value-added originated in productive activities located elsewhere in the global economy. Hayes (2017Hayes ( , 2018 proposes that Bitcoin's value corresponds to its marginal cost of production, where the main input for the cost is electricity, and hence that the origin of Bitcoin's value lies mostly in the energy sector. Since the value of a commodity is determined by the direct and indirect labour time socially necessary to reproduce it, our approach based on the labour theory of value is in line with Hayes in this regard. ...
The paper demonstrates that Bitcoin is not money but rather a digital commodity that has value but no value-added. We show that both the production of and the speculation with Bitcoin draw from the existing global pool of value-added. By extending the Classical Political Economy approach and the New Interpretation of the labour theory of value to the domain of digital commodities, the paper argues that Bitcoin mining is an automated reproduction process that requires no direct (living) labour and thus creates no new value. Bitcoin, in this regard, is not 'digital gold'. Between sectors, Bitcoin mining redistributes wealth and value-added already in existence, while Bitcoin miners with more computational power compete to appropriate the mining profits within the blockchain. The Bitcoin blockchain then creates rivalry in both the ownership and the use of the digital commodity through non-legal means. Our approach can be further expanded to the larger domain of automated digital commodities that are reproducible without the expenditure of direct, living labour.
... According to Kristoufek (2014), the formation of Bitcoin prices cannot be explained by standard economic theories, such as the discounted cash flow model, purchasing power parity, or uncovered interest rate parity, as there are several features of foreign currency supply and demand. Therefore, the most extensive research was carried out on possible internal and external factors affecting the price of cryptocurrencies, particularly the most famous Bitcoin cryptocurrency (Panagiotidis et al. 2019;Poyser 2017;Kavvadias 2017;Letra 2016;Hayes 2015;Kristoufek 2014;. Panagiotidis et al. (2019) concluded that uncertainty in economic policy and stock market volatility are among the most important variables between 41 examined potential drivers of Bitcoin returns. ...
... The author concludes that the variables affecting the Bitcoin price are the number of Twitter messages having a positive impact on the value of 0.136169; Google searches having a negative impact of 0.02546441, and the total number of Bitcoins in circulation that also has a negative impact on the value of 0.00000738. Production costs have three main drivers (Hayes 2015) that affect the Bitcoin price, namely: mining difficulties, production unit rate, and cryptographic algorithm power with an emphasis on electricity cost. All the factors that reduce production costs negatively affect the Bitcoin price. ...
The results of empirical analyses confirm that analysed unsystematic factors, the Stock-to-Flow index (S2F), and information on the Bitcoin (BTC) are directly correlated with BTC values. These results are expected and in line with the economic theory; however, this research paper aimed to investigate the impact of unsystematic factors on the value of decentralised virtual cryptocurrency BTC. Its aim was also to analyse the reasons for significant oscillations of market values in relation to the S2F and S2FX model and thus confirm the reliability of these models in the estimation of BTC value. The research further confirms the strong influence of non-technical information directly linked with the BTC. The limitations of this paper are the lack of possibilities for examining the impact of non-technical information affecting the Bitcoin price deviation regarding the S2F model. In addition to all mentioned limitations, the research results indicate the relevance of the S2F and S2FX models and show a strong impact of (half) the information on the value of cryptocurrencies.
... Subsequently, Hayes [32] hypothesized a connection between Bitcoin's price and its cost of production (i.e., the cost related to the mining process). The findings demonstrated that adding the hash rate to predictive models could explain up to 80% of the variance in Bitcoin's price. ...
... Total amount of computing power [12], [32] Proliferation of End Users ...
... Cryptocurrencies are not issued by central authorities; therefore, their value mostly comes from the scale of participation within the market. Still, value formation and fluctuations of cryptocurrencies are hotly debated topics in the literature (Aysan et al. 2019(Aysan et al. , 2020(Aysan et al. , 2021a(Aysan et al. , 2021bHayes 2017;Nadler and Guo 2020;Akyildirim et al. 2021). Bitcoin is the most commonly used cryptocurrency among the various cryptocurrencies in the market. ...
Bitcoin, as the first decentralized cryptocurrency, pioneers the cryptocurrency markets, both in terms of market capitalization and scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.
... For the foundation of our analysis, we follow various studies by extracting the daily prices of CCs from the website coinmarketcap.com (Fry and Cheah 2016;Hayes 2017;Brauneis and Mestel 2018;Caporale et al. 2018;Gandal et al. 2018;Glas 2019). To depict the CC market as a whole, we aim to include as many CCs in our analysis as possible. ...
Cryptocurrencies (CCs) have become increasingly interesting for institutional investors’ strategic asset allocation and will therefore be a fixed component of professional portfolios in the future. However, this asset class differs from established assets primarily in that it has a higher standard deviation and tail risk. The question then arises whether CCs with similar statistical key figures exist. On this basis, a core market incorporating CCs with comparable properties enables the implementation of a tracking error approach. A prerequisite for this is the segmentation of the CC market into a core and a satellite, with the latter comprising the accumulation of the residual CCs remaining in the complement. Using a concrete example, we segment the CC market into these components based on modern methods from image/pattern recognition.
... We conducted an extensive and holistic review of the literature, from extracting data from peerreviewed scientific publications (Pathirana et al. 2019, Hayes 2017) and mining machine stores websites, to thoroughly investigating mining hardware efficiencies. By assuming that mining hardware converts electricity into hashing computation at the highest possible rate, mining hardware efficiencies can be calculated by taking the ratio of power consumption data to the corresponding hashrate it produces. ...
A decentralized blockchain is a distributed ledger that is often used as a platform for exchanging goods and services. This ledger is maintained by a network of nodes that obeys a set of rules, called a consensus protocol, which helps to resolve inconsistencies among local copies of a blockchain. In this paper, we build a mathematical framework for the consensus protocol designer that specifies (a) the measurement of a resource which nodes strategically invest in and compete for in order to win the right to build new blocks in the blockchain; and (b) a payoff function for their efforts. Thus the equilibrium of an associated stochastic differential game can be implemented by selecting nodes in proportion to this specified resource and penalizing dishonest nodes by its loss. This associated, induced game can be further analyzed by using mean field games. The problem can be broken down into two coupled PDEs, where an individual node's optimal control path is solved using a Hamilton-Jacobi-Bellman equation, where the evolution of states distribution is characterized by a Fokker-Planck equation. We develop numerical methods to compute the mean field equilibrium for both steady states at the infinite time horizon and evolutionary dynamics. As an example, we show how the mean field equilibrium can be applied to the Bitcoin blockchain mechanism design. We demonstrate that a blockchain can be viewed as a mechanism that operates in a decentralized setup and propagates properties of the mean field equilibrium over time, such as the underlying security of the blockchain.
... On the other hand, from a purely internal approach and using a least squares regression model, Hayes (2016), suggested that the driving factors for Bitcoin's price were mainly internal; miners' competition level, unit output, and the proof-of-work difficulty. ...
... The rise in the value of cryptocurrencies in the digital asset market has promoted a number of studies aimed at investigating the dynamics of that market along with listing the major influence of channels. Research interests in cryptocurrency markets concentrate on the following issues: (1) accounting and value formation (Bouoiyour et al. 2016;Blau 2017;Hayes 2017;Urquhart 2017;Zhu et al. 2017;Sovbetov 2018;Bolt and Van Oordt 2019;Zimmerman 2020), (2) speculative bubbles, herding behavior, and lotterylike demand (Godsiff 2015;Poyser 2018;Grobys and Junttila 2021); and (3) forecasting cryptocurrency returns, volume, and price (Azari 2019;Bohte and Rossini 2019;Derbentsev et al. 2019;Nasir et al. 2019;Cohen 2020;Mudassir et al. 2020). In addition, other studies focus on the volatility issue in the case of the relationship between the cryptocurrency market and gold and energy instruments (Huynh et al. 2020a, b;Huynh et al. 2020a, b;Thampanya et al. 2020). ...
This study investigates the dynamic mechanism of financial markets on volatility spillovers across eight major cryptocurrency returns, namely Bitcoin, Ethereum, Stellar, Ripple, Tether, Cardano, Litecoin, and Eos from November 17, 2019, to January 25, 2021. The study captures the financial behavior of investors during the COVID-19 pandemic as a result of national lockdowns and slowdown of production. Three different methods, namely, EGARCH, DCC-GARCH, and wavelet, are used to understand whether cryptocurrency markets have been exposed to extreme volatility. While GARCH family models provide information about asset returns at given time scales, wavelets capture that information across different frequencies without losing inputs from the time horizon. The overall results show that three cryptocurrency markets (i.e., Bitcoin, Ethereum, and Litecoin) are highly volatile and mutually dependent over the sample period. This result means that any kind of shock in one market leads investors to act in the same direction in the other market and thus indirectly causes volatility spillovers in those markets. The results also imply that the volatility spillover across cryptocurrency markets was more influential in the second lockdown that started at the beginning of November 2020. Finally, to calculate the financial risk, two methods—namely, value-at-risk (VaR) and conditional value-at-risk (CVaR)—are used, along with two additional stock indices (the Shanghai Composite Index and S&P 500). Regardless of the confidence level investigated, the selected crypto assets, with the exception of the USDT were found to have substantially greater downside risk than SSE and S&P 500.
... Our findings match the results obtained by Hayes [2017], who applied a similar model to estimate the GHG impact of Bitcoin. ...
We introduce a model of greenhouse gas emissions due to on-chain activity on Ethereum, focusing on cryptoart. We also estimate the impact of individual transactions on the environment, both before and after the London hard fork. We find that with the current fee mechanism, spending one dollar on transaction fees corresponds to emitting at least the equivalent of 1.151 kilograms of CO2. We also describe several techniques to reduce cryptoart emissions, both in the short and long term.
... 2016; Cong et al. 2021;Hayes, 2017;Huhtinen, 2014;Kristoufek, 2015;Li & Wang, 2017;Liu et al., 2020;Liu & Tsyvinski, 2021), production factors (e.g., Chen et al., 2021;Hayes, 2019;Georgoula et al., 2015;Li & Wang, 2017;Liu & Tsyvinski, 2021;Poyser, 2019;Sockin & Xiong, 2021), trade volume (e.g., Aalborg et al., 2019;Balcilar et al., 2017;Bouri et al., 2021;Cheah et al., 2020;Figà-Talamanca & Patacca, 2019;Mai et al., 2018;Makarov & Schoar, 2020), supply and demand forces (e.g., Buchholz et al., 2012;Ciaian et al., 2016;De La Horra et al., 2019;Huhtinen, 2014;Goczek & Skliarov, 2019;Gronwald, 2015;Kancs et al., 2019;Kristoufek, 2015;Li & Wang, 2017;Polasik et al., 2015), price swings (e.g., Aalborg et al., 2019;Ahmed, 2020;Ahmed & Al Mafrachi, 2021;Cheah et al., 2020;De La Horra et al., 2019;Sovbetov, 2018), and return momentum (e.g., Cheah et al., 2020;Cheng et al., 2019;Liu et al., 2020;Liu & Tsyvinski, 2021;Nguyen et al., 2020). The second category epitomizes the growing international attention to, and recognition of, Bitcoin and the likes, which is generally measured by social media networks and web analytic tools, such as Reddit (e.g., Bukovina & Marticek, 2016;Chen et al., 2019;Phillips & Gorse, 2017, Twitter (e.g., Chen et al., 2021;Garcia & Schweitzer, 2015;Georgoula et al., 2015;Hu et al., 2019;Kaminski, 2014;Kraaijeveld & De Smedt, 2020;Li & Wang, 2017;Liu & Tsyvinski, 2021;Sabalionis et al., 2021;Shen et al., 2019), crypto forum posts (e.g., Guégan & Renault, 2021;Kim et al., 2017;Mai et al., 2018), Wikipedia search queries (e.g., Ciaian et al., 2016;Cretarola et al., 2020;Georgoula et al., 2015;Kim et al., 2017;Kristoufek, 2013;Kristoufek, 2015;Panagiotidis et al., 2019), and Google trends (e.g., Chen et al., 2021;Cretarola et al., 2020;Dastgir et al., 2019;Figà-Talamanca & Patacca, 2019;Garcia & Schweitzer, 2015;Georgoula et al., 2015;Kristoufek, 2013;Kristoufek, 2015;Li & Wang, 2017). ...
There is a growing stream of empirical research that endeavors to identify the influential variables contributing to the price formation of cryptocurrencies and, in particular, Bitcoin. However, results of those studies generally remain inconsistent in terms of not only the true combination of factors that affect Bitcoin prices, but also the nature of effects (positive vs. negative) that each individual factor has on the price behavior. The present study investigates the robustness of a wide variety of candidate determinants that have been the focus of attention in relevant literature. Our inquiry relies on the extreme bounds analysis (EBA), which is a type of large-scale sensitivity analysis capable of addressing model uncertainty issues. The findings suggest that crypto market forces of supply and demand, public interest, and economic policy uncertainty are the only variables robust to all possible variations in the conditioning information set. Our evidence argues in favor of the predominance of cryptocurrency-related determinants over global macroeconomic and financial ones in explaining Bitcoin price movements.
... Considering the time domain, the total connectedness intensifies during the COVID-19 outbreak period, indicating the sensitivity of return connectedness in the cryptocurrency markets to exogenous shocks, even though such shocks might be the aftermath or a reaction to the pandemic situation in the form of new waves of quantitative easing. These findings add to previous studies indicating that cryptocurrencies are mostly sensitive to factors related to the Bitcoin and cryptocurrency markets in general, such as Bitcoin popularity (Kristoufek and Scalas, 2015), hashing difficulty (Hayes, 2017) and cyber-criminality . Accordingly, our results contradict the wide strand of literature arguing that Bitcoin and other leading cryptocurrencies are independent of the global financial system and thus are immune to shocks related to the global economy (Baur et al., 2018). ...
... Source: Comply Advantage, https://complyadvantage.com/blog/cryptocurrency-regulations-around-world/ Since Bitcoin's genesis block was mined in early January 2009 (e.g.Hayes, 2017), 18,800,762 bitcoins have been mined and entered circulation (89.53% of a fixed maximum supply of 21 million bitcoins).Over the past decade (especially since 2013), as Bitcoin has set new price records, both the number of its wallet users and the size of its blockchain have grown exponentially. For example, Bitcoin wallet users have increased from a mere 10,000 in 2012 to 75.5 million as of August 15, 2021. ...
Since its debut in January 2009 as the first successful cryptocurrency, Bitcoin has been associated with both extreme volatility and illicit activities (i.e. the black market website Silk Road) linked to terrorism-financing, money-laundering, illegal drugs and human trafficking. But this time is different and Bitcoin has more reasons to reach an unmatched price of $100,000 and $1,000,000 afterwards if governments of advanced nations along with that of China stops running headlong into backlash to the alpha Bitcoin and its prodigies (altcoins). Aside from the regulatory uncertainty, Bitcoin must improve design related flaws of its blockchain; as such, electric-intensive mining process; low scalability (i.e. block size limit of 1 megabyte and frequency block creation time of 10 minutes); proof-of-work - PoW (i.e. high latency, very costly and inefficient way of using resources); low transaction processing speed (i.e. between 3.3 and 7 transactions per second, compared with Ethereum’s 25, Ripple’s 1,500, OES’ 3,000, and Visa’s 25,000); and low security (i.e. the majority of mining is controlled by a handful of mining pools known as bitcoin cartels, which can rewrite an alternative financial history if 51% of the computing power is controlled by them). During the past decade (since 2013), the price of bitcoin has witnessed erotic price movements; when bitcoin passed the $1,000 mark (first bubble), the price rose from $196 in October 2013 to $1,155 in November 2013 and then plunged back to $227 in January 2015; company executives, hedge fund managers, media figures, and some celebrities have said the following about Bitcoin; “it is worse than tulip bulb”, “avoid Bitcoin like a plague”, “unlike stocks and bonds, has nothing to offer”, “will make central banks lose control”, “very iffy”, “Ponzi scheme”, “an unfounded fad (or even a pyramid scheme)”, “does not meet functions of money such as medium of exchange, store of value, and unit of account”, “a lot of froth and fraud.” Bitcoin phenomenon is nothing like the dot.com bubble or the 17th century Dutch tulipmania; while Bitcoin is still around and stronger than before, the antecedents that it is often compared with ceased to exist. Similar criticism keeps emerging every time Bitcoin breaks new price records, i.e. $20,089 on 17 December 2017, $32,052 on 3 January 2021, $40,846 on 6 February 2021, $50,341 on 16 February 2021, $61,221 on 14 March 2021, and finally $64,863 on 14 April 2021 (dropped to $28,893 on June 22, 2021). Conventional money will not disappear anytime soon, but at the same time, Bitcoin will continue to forge ahead unabated regardless of ongoing efforts to kill it off.
... Akademik çalışmalarda öncelikle Bitcoin ve diğer digital paraların para olma fonksiyonları incelenmiştir. Glaser vd.(2014), Yermack (2015), Hayes (2017)bu amaçla yapılalan öncü çalışmalardan bazılarıdır. Bitcoin'in 2009 yılında hayatımıza girmesi, piyasasının oluşması ve alınır satılır hale gelmesinden sonra özellikle de 2010 yıllarından itibaren yeterli verinin oluşmaya başlamasıyla birlikte Bitcoin getirileri üzerine istatistiksel çalışmalar yapılmaya başlandığını görmekteyiz. ...
... Szerszą grupę kryptowalut, pod kątem czynników kształtujących ich ceny, bada również Hayes (2017). Na podstawie analizy 66 z nich autor wskazuje 3 główne czynniki wpływające na ich ceny: poziom konkurencji w sieci między górnikami, czas potrzebny do stworzenia jednostki kryptowaluty oraz poziom skomplikowania algorytmu służącego do kopania kryptowalut. ...
Stworzenie bitcoina, powstanie kolejnych kryptowalut i innych rodzajów tokenów oraz pojawienie się pośredników umożliwiających obrót nimi dały początek nowemu rynkowi. Jest on wykorzystywany w celach inwestycyjnych i podlega dynamicznemu rozwojowi. Architektura rynku kryptowalut i pozostałych tokenów staje się coraz bardziej złożona, a on sam pozostaje nadal nie do końca rozpoznany. Istnieje więc potrzeba spojrzenia na niego z wielu perspektyw, określenia ogólnych zasad funkcjonowania i pogłębienia zrozumienia jego działania, do czego przyczyniają się rozważania zawarte w tej monografii. Co istotne, przedstawione treści wskazują zarówno zalety, jak i mankamenty analizowanego rynku. Czytelnik dowie się z książki: czym są kryptowaluty i pozostałe tokeny; czy kryptowaluty i pozostałe tokeny stanowią nową klasę aktywów i czy są kolejnym rodzajem inwestycji alternatywnych; w jaki sposób funkcjonuje rynek kryptowalut i pozostałych tokenów; jakimi cechami charakteryzuje się rynek kryptowalut i pozostałych tokenów i jakie jest znaczenie tych cech dla jego uczestników i instytucji regulacyjnych. Książka stanowi interesującą lekturę dla naukowców i studentów chcących zająć się tematyką kryptowalut, pozostałych tokenów oraz tworzonego przez nie rynku. Może być podstawą do dalszych analiz naukowych czy wsparciem dydaktyki z zakresu finansów cyfrowych. Zainteresuje również praktyków rynkowych, osoby współtworzące regulacje rynku finansowego, a także pasjonatów inwestycji i innowacji finansowych.
... They are based on decentralized, distributed networks, including a standard data transfer technology called the blockchain. The network data transfer relies on security data encryption (Hayes, 2017(Hayes, , pp.1308(Hayes, -1321. Cryptocurrencies are generally based on hash functions. ...
In recent times, firms or businesses in the Hotel and Tourism industry
across the globe have suffered setback financially in terms of patronage and
turnover. This is out rightly attributed to the emergence of the invincible enemy
– the COVID-19 pandemic. The upper echelon of organization, thus have a
role to play in reviving this sector. Against this backdrop, this study examined
the impact CEO gender and educational background on the financial
performance of hotels in Nigeria. This study sampled three listed hotel in the
Nigeria Stock Exchange from 2017 to 2020. Ordinary least squares regression
was employed to empirically ascertain the relationship between variables of
the study. The study found that CEO gender has no significant impact on the
financial performance of Hotels in Nigeria. Secondly, the study found that
CEO educational background has positive and significant impact on the
financial performance of Hotels in Nigeria. The study recommends that CEO
with hotel and tourism educational background should be appointed in hotels
in Nigeria to improve the financial performance.
... Compared to traditional financial assets, investing in cryptocurrencies does not appear safe (Chuen et al., 2017). Its valuation is highly dependent on many factors such as mining costs (Hayes, 2017), network structure and market effects (Kondor et al., 2014) and peer influence of traders (Krafft et al., 2018), inhibiting the transparency of its valuation as a currency (Yermack, 2015). Moreover, the cryptocurrency market is often considered volatile and prone to the occurrence of bubbles in the price dynamics, specifically in the case of Bitcoin (Gerlach et al., 2018). ...
The emergence of cryptocurrency markets has drastically changed how online transactions are conducted and provide a new investment opportunity. This study contributes to the literature on directional cryptocurrency price returns prediction by expanding the set of meaningful features extracted from textual data with sentiment analysis and comparing their usefulness across multiple data sources. In contrast to previous studies, we use fine-grained topic-sentiment features. More specifically, aspect-based sentiment analysis models, JST and TS-LDA, are implemented to incorporate joint topical-sentiment features and the degree of text subjectivity. We collected, and make available, a dataset, which consists of data scraped from Reddit, Bitcointalk and CryptoCompare sources, to demonstrate that proposed features lead to interpretable topics and an improvement in predictive performance.
... Second, the appreciation or depreciation of fiat currencies will also affect cryptocurrencies. For example, when the U.S. dollar appreciates or depreciates, the price of cryptocurrencies paid in U.S. dollars will also increase or decrease [13]. ...
... Cryptocurrencies are not issued by central authorities; therefore, their value mostly comes from the scale of participation within the market. Still, value formation and fluctuations of cryptocurrencies are hotly debated topics in the literature (Aysan et al. , 2020(Aysan et al. , 2019Hayes, 2017;Nadler & Guo, 2020, Akyildirim et al. 2021. Bitcoin is the most commonly used cryptocurrency among the various cryptocurrencies in the market. ...
Blockchain is a path-breaking paradigm, and cryptocurrencies are one of the main application areas of Blockchain technology. Bitcoin leads the cryptocurrency markets, both in terms of market capitalization and in scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.
... From a data set of five one-year maximum losses, we draw statistical statements about the five-year maximum loss and provide specific guidance on how to use the results in a risk report. First, we extract daily CC prices from the website coinmarketcap.com, as recently done by several other authors (Fry and Cheah, 2016;Hayes, 2017;Brauneis and Mestel, 2018;Caporale et al., 2018;Gandal et al., 2018;Glas, 2019). To capture the CC market as a whole, we use a complete market snapshot provided by Coinmarketcap at a certain reference date for data collection. ...
Regulatory authorities require some institutional investors to carry out a worst-case risk assessment and a worst-case risk forecast. In many cases, the amount of (ex post) available data is low, and long-term time ranges must be covered ex ante in the risk report. Both of these factors make a risk assessment appear impossible at first glance. Based on the statistical distribution of the extreme value, we present a method of conducting a risk assessment for very small samples and, in the extreme case, for a single data point. The proposed risk assessment method is demonstrated using an example of cryptocurrency returns.
... Variation in financial assets prices is driven by number of macroeconomic variables and investors' psychology, as supported by a number of studies since the 1980s (Flammer 2020;Kumar and Anandarao 2019;Hayes 2017). Though the efficient market hypothesis (EMH) asserts that prices of assets are entirely reflected by existing information, contrary to the EMH theory, accurately predicting the prices of financial assets is not possible due to the importance of investor sentiment (the news-based impact). ...
The current study investigates the connectedness between US COVID-19 news, Dowes Jones Index (DJI), green bonds, gold, and bitcoin prices for the period 22 January 2020–3 August 2021. The study has employed wavelet coherency, the continuous wavelet transform, and the wavelet-based Granger causality methods to obtain the dependence result. The continuous wavelet transform (CWT) analysis reveals that the United States equity market prices are extremely sensitive with regard to spreading coronavirus (USCOVID-19) news and changes in the oil price. Green bonds, gold, and bitcoin have minimal connectedness with the equity market, which might lead to the hedge and safe haven role of these assets during the COVID-19 crisis period. Lastly, very strong comovement was found between bitcoin and gold during the entire sample. The results of the present study offer a number of fresh and noticeable policy implications for international investors and asset managers.
... From a data set of five one-year maximum losses, we draw statistical statements about the five-year maximum loss and provide specific guidance on how to use the results in a risk report. First, we extract daily CC prices from the website coinmarketcap.com, as recently done by several other authors (Fry and Cheah, 2016;Hayes, 2017;Brauneis and Mestel, 2018;Caporale et al., 2018;Gandal et al., 2018;Glas, 2019). To capture the CC market as a whole, we use a complete market snapshot provided by Coinmarketcap at a certain reference date for data collection. ...
... Economic commentators have argued that Bitcoin cannot even be considered money as it has no 'value' (as opposed to gold, which can be used for other purposes) (Yermack, 2013;Torpey, 2017). But this has been challenged by Hayes (2017Hayes ( , 2018, who shows that the marginal cost of production is related to prices and argues that Bitcoin has intrinsic value through the intangible computational labour expended in the mining process. Ingham, too, dismisses cryptocurrencies, as they do 'what money should not do: that is, introduce uncertainty into transactions' (Ingham, 2020: 114). ...
Money has been a polarising and unresolved socio-economic issue for more than 300 years. In this article, we explore how the state became increasingly involved in money and, through the words of prominent monetary theorists, identify the problem of the state in money. We analyse Bitcoin to see if it is a solution to this problem but move on to contend that the political dimension needs to be the focus of theory in the 21st century and that control of the supply of money, and the power that it gives, is the root of contention.
We apply the (Phillips et al., 2015a,b) methodology to date-stamp bubbles in the Ethereum blockchain. Our analysis of the drivers of fundamental value suggests that the explosive behavior documented in ether prices does not constitute speculative bubbles but reflects the abrupt rally of demand for the use of the Ethereum Virtual Machine tied to the development of the decentralized application (dApp) ecosystem.
Health literacy is a discrete form of literacy and becoming an increasingly important aspect for social, economic, and health development. It is already seen as a crucial tool for the prevention of non-communicable disease with investments in education and communication. However, there is not enough knowledge on health literacy’s impact on communicable diseases. Today with the rapid development of coronavirus disease 2019 (COVID-19), a communicable disease, there has been a need for people to acquire and apply health information. (Paakkari & Okan, 2020) Health communication intended to educate people has become widely available. However, there is also a lot of misinformation, thus forcing individuals to filter and be health literate.
This investigation created successful models for predicting the number of COVID-19 cases from data regarding the United States Census Bureau, Internal Revenue Service (IRS), Centers of Medicare and Medicaid Services, and National Science Board. The successful execution of these machine learning models builds an association between health literacy and COVID-19, under the assumption that states with high COVID-19 cases associate with areas of lower health literacy. These models can be deployed for further analysis of state health care costs and policy challenges.
Since a mysterious creator under the alias Satoshi Nakamoto (a pseudonym) launched first successful cryptocurrency in January 2009, he (or could be she) also opened the door for never-ending criticism, claims, arguments, plethora of articles, and media frenzy all contemplating what Bitcoin is. This paper concludes that Bitcoin is not a currency to be used for everyday transactions like all fiat currencies. Furthermore, Bitcoin is not a stable cryptocurrency and it is useless (and impractical) of arguing how Bitcoin meets or fails basic functions of money; to make it clear, Bitcoin satisfies all three functions of money (not to the extent of fiat currencies, nonetheless it does); store of value, unit of account, and medium of exchange. As discussed in this article, our proposal of Bitcoin as a supranational central bank reserve currency not only will put an end to debates and the frequently asked old question of "what is Bitcoin?", it will also make Bitcoin's design flaws disappear instantly. Under the new Bitcoin standard (Gold 2.0), inefficiencies become trivial because Bitcoin is capable of easily handling the volume of operations among central banks. Bitcoin's extensively discussed weaknesses become no issue; high latency (a block of transactions is validated every 10 minutes), low processing speed (3-7 transactions per second), huge power cost (mining of 1 bitcoin requires 1,825 kWh of electricity, equivalent to 63 days of power usage by a U.S. household), and low scalability (the maximum number of bitcoins is fixed at 21 million). Key elements of the proposed new Bitcoin Standard include: Bitcoin will be a supranational reserve currency used by central banks only; ownership, trade, and other uses of bitcoins by citizens and various entities will be prohibited; the fixed supply of bitcoins (21 million) will remain unchanged; every country's financial authority will switch to central bank digital coins (CBDC); CBDCs will be defined in bitcoin by a corresponding exchange rate for each country; 100% of CBDCs will be 100% backed by bitcoins; any increase in the digital money supply by a central bank will require additional bitcoins; and the value of each bitcoin will be raised to a price level to cover 100% of the total money in circulation (approximately $75 trillion).
The cryptocurrency markets are perceived as being dominated by Bitcoin leading the overall system dynamics. Although the previous empirical evidence points towards strong connections among selected cryptocurrencies or, from the other side, weak dependence between Bitcoin and traditional financial assets, a focused study on the dynamics of return and volatility connectedness among a wider range of cryptocurrencies is lacking, and more so, one directed towards the very first actual critical period of the global economy coinciding with relevant crypto-markets. Using data for the 10 most capitalized cryptocurrencies between 1st October 2017 and 5th January 2021, we examine how cryptocurrencies interact and whether they have a clear leader, with a special focus on differences with respect to investment horizons and how the relationship structure evolves in time. We uncover a structural change in the connectedness evolving in 2020 as the market restructures in reaction to the unprecedented monetary injections as a counter to the COVID-19-induced economic standstill. The structural change is shown not only for cryptocurrencies considered separately but also when we jointly examine them with traditional assets.
The possibility of including financial instruments, such as equity, debt, derivative and market-based funds, in a portfolio varies with their market sensitivity. Cryptocurrency (crypto) has been of recent origin and interest to investors and policymakers. The study has attempted to explore opportunities for Indian and international investors in equity and crypto markets. Bivariate analysis between the crypto index and Indian market indices revealed few causal linkages between crypto and other indices. Standard VAR and Granger causality have been used for exploring the association between the variables. DCC-GARCH has been applied for checking further on volatility spillover and the relationship between indices. Granger results indicate the presence of linkages between crypto and energy, media, and oil & gas indices. However, spillover results have shown an absence of such linkages in the short run but a significant presence in the long run except for a few indices.
Despite the crucial role of thermal coal in generating the electricity used for cryptocurrency mining, the volatility linkage between the cryptocurrency and thermal coal markets is yet to be studied. We investigate the time-varying volatility connectedness between the two markets using their realized variances and semi-variances. Employing a multivariate Heterogeneous Autoregressive model, which accounts for both long memory and structural breaks in realized volatility time series, we find that China's thermal coal futures market is significantly dependent on the cryptocurrency market's volatility while the impact of the energy market on the cryptocurrency market is inconsequential. Moreover, the connectedness is asymmetrical in the sense that the bad volatility connectedness is greater than the good volatility connectedness. Finally, the determinants of the dynamic connectedness highlight the role of the production channel in fuelling the volatility transmission between these two markets.
Purpose
Bitcoin has emerged as a phenomenal asset earning abnormal profits. However, the factors with predictability power over its price are not widely studied. Therefore, this study aims to explore the factors that determine bitcoin prices. The analysis explores the determinants belonging to four categories – macro economic, financial, technical and fundamental factors.
Design/methodology/approach
The study employs random effects regression on the panel data of five countries. Then Granger causality test is applied on the time series of all the variables. Lastly, diagnostic tests are conducted to confirm the findings to be robust and reliable.
Findings
The findings suggest that oil price, bitcoin supply, trading volume and market capitalization significantly impact the price of bitcoin in the long run. In short run, bitcoin returns are only caused by oil price and market capitalization. Interestingly, bitcoin returns influence its attractiveness to investors, market capitalization, S&P 500 returns and trading volume, in the short run.
Practical implications
The technical analysis is found to be redundant in the short run. In the long run, technical as well as fundamental analysis are useful. The bitcoin is found to be a good diversification tool as it has no linkages with the stock markets and gold market. It is also an inflationary hedger owing its limited supply.
Originality/value
The studies on cryptocurrency market have not conducted the analysis across countries. This study captures the cross-sectional effects along with time effects. The study also includes 17 variables belonging to four categories.
Humboweyne dam structure is a dam that located north east in Hargeisa city of Somaliland
(unrecognized sovereign state in the Horn of Africa.), The dam is built for keeping the flood
water from hills which used to go directly into the sea without the benefits. The main aims of
this study are to identify the possible impacts of sedimentation on the Humbo-weyne reservoir
and measuring the technique to assess and to choose the suitable management strategy to control
the sedimentation based the two technical reports from Hargeisa Water Agency.
Humbo-weyne dam structure project funded by United Arab of Emirates UAE, starting time of
the project was 28-12-2015 and the completion time was April 24, 2017 The Reservoir capacity
design of the dam was 500,000 m3
. The main purposes of project were water supply and
livestock demand [3]. After two year of completion time the Sustainability of Humboweeyne
reservoir was severely threatened by sedimentation resulting from design errors, deforestation
of the catchment, climate change effects and natural geomorphologic processes of the
Humboweeyne catchment. the reservoir began to loss of water-storage capacity due to
Sediments from the floods which eventually leads the reduction reliability of the project
purposes.
Cryptocurrency is actually approved an additional kind of resource which can be exchanged simply by traders in many ways akin to some other equity within the funds marketplace. Nevertheless, because it is the latest, the particular components which you can use intended for selling price motion conjecture are nonetheless bare. Consist of funds aspects like dispenses plus forex, price tag movements predection could be depended around the specialized in addition to basic evaluation associated with Effective Marketplace Speculation (EMH). This particular cardstock would be to evaluation the use of the particular complex technical analysis associated with EMH to find cryptocurrency exploration. Technique: This particular papers might evaluation the latest document the past 5 decades within the thickness regarding specialized research equipment (Moving Typical (MA), Comparable Strenght List (RSI), and even change candlestick patterns) within forecasting assets' cost modifications together with have a shot at putting it on to verify if the particular equipment are furthermore frequent within forecasting typically the cryptocurrency value activity. Locating: MUM guage is really a very reliable indication when compared with RSI plus change candlestick designs are likewise trustworthy signals to cryptocurrency cost modification. Yet, additional examine should be performed about how imperative evaluation involving EMH impact cyptocurrency selling price modify.
The production of energy by using renewable energy sources are going depth of the earth.
Production energy by using a traditional blade wind has many advantages and disadvantages one of them, the cost of the capital and maintenance cost and friction loss represents a negative point. At the present, a new approach of capturing wind energy by using bladeless windmill find a low-priced and safe replacement to conventional windmills. Vortex-Bladeless is new concept of a wind turbine without blades called vorticity wind turbine which uses the VIV. The vortex design aims to eliminate and reduce many of the existing problems in conventional generators and represents a new paradigm of wind energy. Vortex can be able to operate efficiently at lower wind speeds, so runtime increases. The purpose of this is study to provide a basic comparison between the conventional wind turbine and vortex paradigm in harvesting wind energy.
The production of energy by using renewable energy sources are going depth of the earth. Production energy by using a traditional blade wind has many advantages and disadvantages one of them, the cost of the capital and maintenance cost and friction loss represents a negative point. At the present, a new approach of capturing wind energy by using bladeless windmill find a low-priced and safe replacement to conventional windmills. Vortex-Bladeless is new concept of a wind turbine without blades called vorticity wind turbine which uses the VIV. The vortex design aims to eliminate and reduce many of the existing problems in conventional generators and represents a new paradigm of wind energy. Vortex can be able to operate efficiently at lower wind speeds, so runtime increases. The purpose of this is study to provide a basic comparison between the conventional wind turbine and vortex paradigm in harvesting wind energy.
Following the rampant increase in Bitcoin prices, there has been a proliferation of cryptocurrencies, which have become a major way of doing business across national boundaries. This paper investigates the link between cryptocurrency markets and drug trafficking activities. More specifically, we explore the impact of the announcement of 24 major drug busts on the systematic risk and return of the world cryptocurrency market. We deploy an event study methodology to estimate the abnormal returns associated with drug trafficking activities in the cryptocurrency market. We find that the relationship between the two is quite strong in the case of some cryptocurrencies, albeit weaker in others. However, we show that drug bust news tends to create uncertainty, and accordingly impart risk into cryptocurrency markets. This study confirms the predictions of convenience theories of crime as to the relative attractiveness of cryptocurrencies to criminals, and the extent to which not only general, but also their own future interests, sacrificed readily on the altar of accessibility. We highlight how when social and regulatory foundations are weak, criminal behaviour may overwhelm virtual spaces, marginalizing more orthodox businesses, no matter how altruistic the intentions of their founders.
Purpose
This paper aims to empirically investigate the extent to which interdependence in markets may be driven by COVID-19 effects.
Design/methodology/approach
The current global COVID-19 pandemic is adversely affecting the oil market (West Texas Intermediate) and crypto-assets markets.
Findings
The authors find that the dependence structure changes significantly after the global pandemic, providing valuable information on how the COVID-19 crisis affects interdependencies. The results also prove that the performance of digital gold seems to be better compared to stablecoin.
Originality/value
The authors fit copulas to pairs of before and after returns, analyze the observed changes in the dependence structure and discuss asymmetries on propagation of crisis. The authors also use the findings to construct portfolios possessing desirable expected behavior.
This paper investigates the directional causal relationship and information transmission among the returns of West Texas Intermediate (WTI), Brent, major cryptocurrencies, and stablecoins by drawing on daily data from July 2019 to July 2020. Applying effective transfer entropy, a non-parametric statistic, the results show that the direction of the causal relationship and the nature of information spillovers changed after the COVID-19 pandemic. More precisely, our findings reveal that WTI and Brent are leading the prices of Bitcoin and Bitcoin Cash. Conversely, Bitcoin futures and stablecoins (TrueUSD and USD Coin) are leading WTI and Brent prices. In addition, the stablecoin Tether became a leader against Brent prices after the pandemic, although it is still following WTI prices. Moreover, Ethereum and USD coin preserved their position as leaders against Brent prices. Interestingly, our results also reveal that Ethereum, Litecoin, and Ripple preserved their position as leaders of WTI prices. The change in the nature of directional causality and the spillover effect after the COVID-19 crisis provide valuable information for practitioners, investors, and policymakers on how the ongoing pandemic influences the connection and network correlation among the energy, cryptocurrency, and stablecoin markets.
Cryptocurrency, operated through blockchain technology, is a new
form of digital currency which is used as a medium of exchange. It is
used in many countries but Bangladesh Bank, the central bank of
Bangladesh, halts a ban on its use and/or trading considering its
negative aspects. So, the perception towards virtual currency in
Bangladesh remains under shadow. Hence, the study investigates the
perception of a total 155 persons (having sound knowledge in this
new technology e.g., central bankers, bankers and finance and
accounting graduates) behind the intended use of cryptocurrency using
structural equation modelling. The study has four observed variables
(perceived ease of use, perceived usefulness, trust and perceived risk)
and one latent variable (behavioral intention to use cryptocurrency).
Finally, the result demonstrates that perceived usefulness and trust
have a significant impact, but perceived ease of use and perceived
risk have no significant impact on the intention to use cryptocurrency.
The paper enlightens the unexplored perception of the people of
Bangladesh towards cryptocurrency. The findings recommend that the
Bangladesh Bank may reconsider its decision regarding fintech
innovation considering cryptocurrency’s positivity and minimize the
dilemma keeping the deleterious sides under strict monitoring.
Keywords: Bangladesh Bank, Block chain, Cryptocurrency, Perceived
Ease of Use, Perceived Usefulness
JEL Classification: C51, C59, D40, G12
Our objective in this paper is to explore the impact of 21 terrorist attacks on the risk and return of cryptocurrencies. This is motivated by the rapid increase in Bitcoin and other cryptocurrency prices in conjunction with uncertainty about cryptocurrency fundamental value and how this value is determined. Using daily cryptocurrency returns and the event study methodology, we estimate cryptocurrency abnormal returns around terrorist activities. Asset pricing models are fitted with interaction variables to identify the impact of individual attacks. ARCH models are used to determine changes in systematic risk. Our findings indicate that terrorist attacks positively contribute to the returns of cryptocurrencies whilst the attacks also result in short-term risk-shifting behavior for different cryptocurrencies.
This study attempts to analyze comprehensive data for the cryptocurrency market. In detail, this paper gathers all pertinent market currency data, on-chain data, and technical analysis to predict investor sentiment. In this research, we analyze the most effective tools to predict the market price of cryptocurrencies, from 2016 to 2021 and to determine the market price trend and its forecasts, through complete historical data in on-chain and crypto-currency market price. The methodology and tools used to analyze this crypto assets, provide a more effective understanding, through on-chain metrics indicators, with increase results in the accuracy on forecasting the crypto-currency prices in the future. Back tests are examined as evidence of the reliability of these indicators such as cryptographic portfolio sizes, sales, purchases and increase of relevant economic activity of the blockchain network to anticipate the crypto market prices rises.
This paper analyses existing literature about the economic effects of cryptocurrency using bibliometric methods. 1850 articles are collected from ”Web of Science core database” from 2013 to 2020. We explore research hotspots and development trends through descriptive statistical analysis, keyword co-occurrence and literature co-citation network analysis. We find that literature of computer sciences and interdisciplinary fields mainly research the technologies’ effects on the economic phenomenon, the technique progress in overcoming the negative economic effects of cryptocurrency, and appeal to establish a new payment system based on the underlying technologies. In comparison, the literature of economic field is concerned about the economic outcomes of cryptocurrency. Especially with the occurrence of various altcoins and the steady progress of legal digital currency in some countries, scholars have paid more attention to the investment properties of cryptocurrency. Based on these findings, this paper holds that the macroeconomic effects of cryptocurrency, the influence mechanism of cryptocurrency and legal digital currency will become research hotspots in the future.
Over recent years, interest has been growing in Bitcoin, an innovation which has the potential to play an important role in e-commerce and beyond. The aim of our paper is to provide a comprehensive empirical study of the payment and investment features of Bitcoin and their implications for the conduct of e-commerce. Since network externality theory suggests that the value of a network and its take-up are interlinked, we investigate both adoption and price formation. We discover that Bitcoin returns are driven primarily by its popularity, the sentiment expressed in newspaper reports on the cryptocurrency, and total number of transactions. The paper also reports on the first global survey of merchants who have adopted this technology and model the share of sales paid for with this alternative currency, using both ordinary and Tobit regressions. Our analysis examines how country, customer and company-specific characteristics interact with the proportion of sales attributed to Bitcoin. We find that company features, use of other payment methods, customers’ knowledge about Bitcoin, as well as the size of both the official and unofficial economy are significant determinants. The results presented allow a better understanding of the practical and theoretical ramifications of this innovation.
The present paper seeks to effectively address the following question: What Bitcoin looks like? To do so, we regress Bitcoin price on different variables (potential Bitcoin fundamentals recorded in the literature) by applying an ARDL Bounds Testing approach for daily data covering the period from December 2010 to June 2014. Our findings highlight the speculative behavior of Bitcoin. This virtual currency may be also used for economic reasons. However, there is any sign of being a safe haven. By considering the Chinese trading bankruptcy, the contribution of speculation (proxied by investors’ attractiveness to Bitcoin) remains dominant, indicating the robustness of our results.
What is the role of social interactions in the creation of price bubbles?
Answering this question requires obtaining collective behavioural traces
generated by the activity of a large number of actors. Digital currencies offer
a unique possibility to measure socio-economic signals from such digital
traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has
experienced periods of rapid increase in exchange rates (price) followed by
sharp decline; we hypothesise that these fluctuations are largely driven by the
interplay between different social phenomena. We thus quantify four
socio-economic signals about Bitcoin from large data sets: price on on-line
exchanges, volume of word-of-mouth communication in on-line social media,
volume of information search, and user base growth. By using vector
autoregression, we identify two positive feedback loops that lead to price
bubbles in the absence of exogenous stimuli: one driven by word of mouth, and
the other by new Bitcoin adopters. We also observe that spikes in information
search, presumably linked to external events, precede drastic price declines.
Understanding the interplay between the socio-economic signals we measured can
lead to applications beyond cryptocurrencies to other phenomena which leave
digital footprints, such as on-line social network usage.
Designed to compete with fiat currencies, bitcoin proposes it is a
crypto-currency alternative. Bitcoin makes a number of false claims, including:
bitcoin can be a reserve currency for banking; hoarding equals saving, and that
we should believe bitcoin can expand by deflation to become a global
transactional currency supply. Bitcoin's developers combine technical
implementation proficiency with ignorance of currency and banking fundamentals.
This has resulted in a failed attempt to change finance. A set of
recommendations to change finance are provided in the Afterword:
Investment/venture banking for the masses; Venture banking to bring back what
investment banks once were; Open-outcry exchange for all CDS contracts;
Attempting to develop CDS type contracts on investments in startup and existing
enterprises; and Improving the connection between startup tech/ideas, business
organization and investment.
We analyze how network effects affect competition in the nascent cryptocurrency market. We do so by examining the changes over time in exchange rate data among cryptocurrencies. Specifically, we look at two aspects: (1) competition among different currencies, and (2) competition among exchanges where those currencies are traded. Our data suggest that the winner-take-all effect is dominant early in the market. During this period, when Bitcoin becomes more valuable against the U.S. dollar, it also becomes more valuable against other cryptocurrencies. This trend is reversed in the later period. The data in the later period are consistent with the use of cryptocurrencies as financial assets (popularized by Bitcoin), and not consistent with "winner-take-all" dynamics.
Though Bitcoin currently enjoys a healthy niche, the aspirations of many in the project are grander: to supplant the existing regime of fiat currencies with cryptocurrencies, and to do so outside of normal political channels. Its primary practical obstacle is its purchasing power volatility, arising from a rigid money stock in the face of wide swings in demand. Nevertheless, the historical example of gold, another (much more successful) money commodity with a more or less rigid supply, illuminates the institutional prerequisites for purchasing power stability, economic efficiency, and sustained growth – namely a market of financial intermediaries whose liabilities denominated in the base money themselves circulate as media of exchange. This paper discusses potential benefits and hurdles to establishing financial intermediation in cryptocurrency, as well as the possibility of managing the money supply to create a stable purchasing power cryptocurrency without the need for intermediation at all. Such schemes ultimately require an existing market of intermediaries in order to provide any benefits, the emergence of which governments are for the moment well-positioned to prevent.
Over recent years, interest has been growing in Bitcoin, an innovation which has the potential to play an important role in e-commerce and beyond. The aim of our paper is to provide a comprehensive empirical study of the payment and investment features of Bitcoin and their implications for the conduct of e-commerce. Since network externality theory suggests that the value of a network and its take-up are interlinked, we investigate both adoption and price formation. We discover that Bitcoin returns are driven primarily by its popularity, the sentiment expressed in newspaper reports on the cryptocurrency, and total number of transactions. The paper also reports on the first global survey of merchants who have adopted this technology and model the share of sales paid for with this alternative currency, using both ordinary and Tobit regressions. Our analysis examines how country, customer and company-specific characteristics interact with the proportion of sales attributed to Bitcoin. We find that company features, use of other payment methods, customers’ knowledge about Bitcoin, as well as the size of both the official and unofficial economy are significant determinants. The results presented allow a better understanding of the practical and theoretical ramifications of this innovation.
A bona fide currency functions as a medium of exchange, a store of value, and a unit of account, but bitcoin largely fails to satisfy these criteria. Bitcoin has achieved only scant consumer transaction volume, with an average well below one daily transaction for the few merchants who accept it. Its volatility is greatly higher than the volatilities of widely used currencies, imposing large short-term risk upon users. Bitcoin’s daily exchange rates exhibit virtually zero correlation with widely used currencies and with gold, making bitcoin useless for risk management and exceedingly difficult for its owners to hedge. Bitcoin prices of consumer goods require many decimal places with leading zeros, which is disconcerting to retail market participants. Bitcoin faces daily hacking and theft risks, lacks access to a banking system with deposit insurance, and it is not used to denominate consumer credit or loan contracts. Bitcoin appears to behave more like a speculative investment than a currency.
The question "what is Bitcoin" allows for many answers depending on the
objectives aimed at when providing such answers. The question addressed in this
paper is to determine a top-level classification, or type, for Bitcoin. We will
classify Bitcoin as a system of type money-like informational commodity (MLIC).
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
Bitcoin: a first assessment
- David Woo
Woo, David, et al. Bitcoin: a first assessment. FX and Rates (2013).
The Moneyness of Bitcoin, <www.mises.org>
- Nikolay Gertchev
Gertchev, Nikolay, 2013. The Moneyness of Bitcoin, <www.mises.org>.
Economics of Competing Crypto Currencies: Monetary Policy, Miner Reward and Historical Evolution
- Yiteng Zhang
- Guangyan Song
Zhang, Yiteng, Song, Guangyan, 2014. Economics of Competing Crypto Currencies: Monetary Policy, Miner Reward and Historical Evolution.
Further reading
Why Bitcoins Have Value, and Why Governments Are Sceptical Available at cryptolibrary.org
- T Jenssen
Jenssen, T., 2014. Why Bitcoins Have Value, and Why Governments Are Sceptical Available at cryptolibrary.org.
The false premises and promises of Bitcoin. arXiv preprint arXiv:1312
- Brian P Hanley
Hanley, Brian P. The false premises and promises of Bitcoin. arXiv preprint arXiv:1312.2048
(2013).
Principles of microeconomics
- K E Case
- R C Fair
Case, K. E., & Fair, R. C. (2006). Principles of microeconomics. Pearson Education.
Bitcoin: A First Assessment FX and Rates
- David Woo
Woo, David et al, 2013. Bitcoin: A First Assessment FX and Rates.