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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 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.
... El objetivo de este trabajo es presentar las aproximaciones teóricas y conceptuales para comprender los determinantes del valor del bitcoin. De acuerdo con Hayes (2017), bitcoin consiste en un sistema de pagos en línea basado en software de código abierto, los cuales se registran en un libro mayor compartido, conocido como blockchain. ...
... TRANSACCIONAL respaldo de seguridad que plantea el modelo está soportado en el concepto de prueba de trabajo, con el que se requiere una cantidad importante de esfuerzo computacional para validar las transacciones encriptadas, lo que dificulta un ataque o vulneración del sistema por parte de usuarios mal intencionados. Sin embargo, la dificultad de la prueba de trabajo ha venido acrecentándose, lo que genera una pérdida de incentivos para los usuarios encargados de validar las transacciones, también conocidos como mineros de criptomonedas (Hayes, 2017). Además, en la actividad de minado se han generado desequilibrios competitivos, de tal manera que el control recae ahora en unos pocos usuarios, que tienen acceso al poder informático necesario para llevar a cabo esta actividad de manera rentable. ...
... Actualmente, la mayoría de granjas de minería están concentradas en países como China 1 , que a su vez goza de ventajas naturales, debido al clima frio en diferentes regiones, para mantener los servidores con bajas temperaturas. Independientemente de lo anterior, existen también motivaciones subjetivas para llevar a cabo la minería de bitcoin, más allá de los componentes objetivos, pues los tomadores de decisiones pueden operar sin importar el costo, cuando hay suficiente potencial especulativo al alza (Hayes, 2017). Así las cosas, las propiedades especulativas y el dinero de bitcoin, como medio de intercambio y reserva potencial de valor, agregan una porción subjetiva a cualquier intento objetivo de formar un valor intrínseca (Hayes, 2017). ...
El propósito de este estudio es analizar los inductores de valoración de Bitcoin y los determinantes de su adopción como mecanismo transaccional. El trabajo está sustentado en un análisis de las características de la tecnología Blockchain, como un factor intrínseco que tiene incidencia en la valoración de la criptomoneda. Además, se extiende este análisis para incorporar otros factores que influyen en su valoración; identificando tres categorías como son las fuerzas de mercado, el atractivo y nivel de adopción del Bitcoin, y factores macro-financieros. Con fundamento en este marco de referencia, se identifica que el valor del Bitcoin tiene un componente especulativo y un valor de utilidad como medio de cambio. A partir de lo anterior, se propone como estrategia metodología el desarrollo de una revisión de literatura; con la finalidad de identificar los factores que pueden favorecer la adopción del Bitcoin como un instrumento transaccional y aquellos que representan retos a superar. Los resultados permiten evidenciar que el principal desafío de Bitcoin tiene que ver con la confianza de los usuarios potenciales en el modelo Blockchain.
... Similarly, Krištoufek (2015) also found that hash rate and Bitcoin price correlate positively. Hayes (2017) proposed the cost of production model and stated that the higher cost of production, the higher the Bitcoin price would be. Aoyagi and Hattori (2019) also claimed that the Bitcoin hash rate Granger-causes Bitcoin prices in the short-term horizon. ...
... Although Hayes (2017) found a positive relationship between mining cost and Bitcoin price, the relationship between mining cost and cryptocurrency return remains to be determined. According to the holding period return formula, when the cryptocurrency mining cost increases, its current price will also rise, resulting in a lower return. ...
... In terms of the factors related to the properties of cryptocurrencies, there are two strands of literature, where the first group focuses on the network effects (Cong, Li, & Wang, 2021;Liu & Tsyvinski, 2021;Pagnotta & Buraschi, 2018), and the second group studies the cost of production of cryptocurrencies (Cong, He, & Li, 2021;Hayes, 2017;Sockin & Xiong, 2023). In Liu and Tsyvinski's (2021) study, they specifically emphasize the importance of network effects in capturing user adoption of cryptocurrencies. ...
... According to Jorgenson (1963), a firm's desired capital stock depends on its output and output price. Therefore, factors such as the amount of cryptocurrency produced by the miner (who produces the block, but the actual output obtained consists of all the cryptocurrencies contained in the block) and cryptocurrency market prices are likely to affect the size of the miner's computing power Hayes, 2017;Kjaerland et al., 2018;Lewenberg et al., 2015;Marthinsen & Gordon, 2022;Pagnotta & Buraschi, 2018;Wei et al., 2020). Thus, we proposed the following research questions: RQ1: What are the effects of cryptocurrency price and output volume on the scale of miners' computing power? ...
... Third, extant studies on cryptocurrency output volume impacts on the mining industry primarily focus on scenarios where the blockchain no longer issues new cryptocurrencies and the only cryptocurrencies included in the block are the user transaction fees (Carlsten et al., 2016;Hayes, 2017;Huberman et al., 2021). ...
... A substantial body of literature has examined the impact of factors related to miners' profits (such as cryptocurrency prices, cryptocurrency output volume, and mining costs) on the size of miners' hashrate in terms of production inputs. For instance, researchers have investigated the impact of factors such as cryptocurrency prices (e.g., Hayes, 2017;Pagnotta & Buraschi, 2018;Wei et al., 2020) and cryptocurrency output volumes (e.g., Easley et al., 2019;Lewenberg et al., 2015) on the size of miners' hashrate. However, these studies focused primarily on the entire blockchain network's computing power, examining its impact on the overall hashrate. ...
Blockchains use the Proof-of-Work (PoW) consensus mechanism to ensure security. However, if a few large miners increasingly control most of the computing power (hashrate) on the blockchain, the blockchain may become inoperable. To investigate whether this concern materializes, we examine the impact of miners’ revenue (i.e., cryptocurrency price and cryptocurrency output volume) on computing power using dynamic panel analysis, instrumental variables, and various robustness tests on miners’ panel data in the Bitcoin blockchain from 2011 to 2024. We found that cryptocurrency prices and output volumes exert a positive effect on all miners’ computing power, with a notably stronger effect observed among smaller-scale miners. The cryptocurrency price has a more positive impact on small miners, whereas the volume of cryptocurrency output has a more positive impact on large miners. Although the decrease in cryptocurrency output caused by the deflationary cryptocurrency issuance mechanism inhibits miners’ computing power expansion, the scale of large miners is more stable than that of small miners in a fluctuating cryptocurrency market. Therefore, there is a risk of large miners monopolizing the blockchain.
... Presenting main material. In Hayes paper [1], makes several key assumptions to estimate the primary factors influencing the price of Bitcoin. Here is a more detailed explanation of these assumptions and the framework he builds: ...
... where we set ρ = 1000 GH/s as in Hayes [1]. The CPM offers a simple but effective framework for estimating the cost of production price. ...
... They utilized Autoregressive Distributed Lag (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models for their estimations. Contrary to Hayes' findings [1,2], Kjaerland [5] discovered that the Bitcoin network's hashrate did not significantly impact the market price of Bitcoin. The only exception was during Bitcoin's exponential growth in 2017, suggesting that the Bitcoin price likely influences the hashrate rather than the other way around. ...
This study delves into the dynamics of Bitcoin's hashrate and its correlation with network metrics, aiming to illuminate the underlying factors shaping Bitcoin's ecosystem. Employing a multi-metric analysis, the research examines Bitcoin price, public interest, and total daily transactions alongside hashrate data. Findings reveal nuanced relationships between these variables, with traditional metrics like hashrate showing inconsistent correlations with public interest over long-term trends. However, short-term analyses unveil potential predictive capabilities, especially when integrating additional factors like Bitcoin price and daily transactions. A novel metric, termed the 'popularity coefficient,' is introduced, derived from averaging daily values of price, interest, and transactions, offering a more holistic understanding of Bitcoin's popularity dynamics. The practical implications of this research lie in enhancing our ability to predict short-term fluctuations in Bitcoin's network dynamics, thereby informing decision-making processes within the cryptocurrency ecosystem.
... Studies have also attempted to identify key factors driving cryptocurrency price behavior and return formation. Fundamentally, transaction volumes, adoption rates, and usage statistics are found to significantly influence cryptocurrency prices in the short as well as long run (Hayes, 2017;Cheah & Fry, 2015). Liquidity measures like average trade size are seen improving bitcoin price discovery (Wei, 2018). ...
... Liquidity measures like average trade size are seen improving bitcoin price discovery (Wei, 2018). However, the model fits incorporating only transactional fundamentals can be quite low (Hayes, 2017). This indicates additional non-fundamental speculative and behavioral factors at play. ...
The creation of cryptocurrencies has signified many consequences for financial markets of the traditional kind and their effectiveness. This research seeks to explore the effects of cryptocurrencies on a number of the other traditional markets in aspects of price discovery, volatility, interdependence, and information transmission. Event study analysis of everyday price changes and using multivariate cointegration analysis to cryptocurrencies and the evidence is that the cryptocurrencies are inefficient as characterized by irrational behavior, bubbles, and erratically fluctuating volatilities. However, they affect a range of currency, commodity, and stock market indexes by showing return and volatility spillover effects suggesting information flowing from one market to another. Alnet, cryptocurrency markets seem inefficient on their own but over time enhance the efficiency of linked traditional markets through participation and connectivity of global financial systems. The study contributes valuable insights into the evolving nature of financial markets in the digital era through discussions on market structure, behavioral factors, and policy implications.
... Moreover, what Blockchain offers to its users is "decentralized money transferred directly from one holder to another" thus avoiding traditional bank intermediation, making the process less costly, timeconsuming, or bureaucratic, [11]. To further enhance security in each CC, [12] stated "The more aggregate computational power employed in mining for a CC, the higher the value" Simply adding more transactional details to the DLT grants higher trackability and security to Blockchain transactions. ...
... These people could be part of the financial system by owning digital wallets and thus avoiding the inefficiency of banking processes, which is common in locations with high levels of financial exclusion. In this situation, the use of CCs is the "access to financial services to the un-and under-banked, allow for extremely low-cost money transfers and remittances across state borders", [12]. Kenya is the best example of financial inclusion through CCs and could be a lighthouse for all developing countries seeking to promote disruptive financial inclusion at low fees. ...
In the past decade, the emergence of Blockchain has questioned certain financial institutions. Cryptocurrency upsurge was aimed at conducting financial transactions with more efficiency while being safer, easier, faster, and cheaper. Thus, over-intermediation in finance has been highlighted by Blockchain emergence. Here, a SWOT will be carried out to examine Blockchain and cryptocurrencies, their monetary role, their impact on a financial system based on banking intermediation, and their influence on the future of central banking. About the United States, this paper concludes that cryptocurrencies will eventually spread as a method of payment, which could lead them to be the new form of money under some assumptions. The eventual adoption of blockchain technology by central banks through the introduction of official digital currencies could favor the creation of a more inclusive financial system in the future.
... Marginal cost serves as a practical metric for valuation, particularly for Bitcoin, where computational resources are quantifiable. Hayes (2015Hayes ( , 2017Hayes ( , 2019 [157]- [159] developed a cost-of-production model for Bitcoin valuation, 31 which has extended to address halving effect 32 [161], [162] and analyze other tokens [158]. ...
... Marginal cost serves as a practical metric for valuation, particularly for Bitcoin, where computational resources are quantifiable. Hayes (2015Hayes ( , 2017Hayes ( , 2019 [157]- [159] developed a cost-of-production model for Bitcoin valuation, 31 which has extended to address halving effect 32 [161], [162] and analyze other tokens [158]. ...
This paper surveys products and studies on cryptoeconomics and tokenomics from an economic perspective, as these terms are still (i) ill-defined and (ii) disconnected from economic disciplines. We first suggest that they can be novel when integrated; we then conduct a literature review and case study following consensus-building for decentralization and token value for autonomy. Integration requires simultaneous consideration of strategic behavior, spamming, Sybil attacks, free-riding, marginal cost, marginal utility and stabilizers. This survey is the first systematization of knowledge on cryptoeconomics and tokenomics, aiming to bridge the contexts of economics and blockchain.
... While the mining machines form the fixed costs, the electricity use forms the variable cost [22]. As such, cost minimization entails that cryptocurrency mining activities are taken to economies with cheaper electricity costs. ...
... Turby [1] noted that Bitcoin mining is an inefficient use of scarce energy resources at a point where every economy wishes to reduce and control energy use and move to clean energy but his paper explores the chances of promoting environmentally sustainable development of applications for Blockchain technology without affecting the sector adversely and mitigate energy consumption by the blockchain technologies. Hayes [22] highlighted that electricity cost is the major cost of cryptocurrency production and that Bitcoin price can be characterized by its cost of production i.e. electricity demand for mining Bitcoin. Bitcoin's electricity demand per annum is estimated to be 45.8 TWh (synonymous with the electricity demand for Jordan and Sri Lanka) while emitting carbon ranging from 22.0 to 22.9 MtCO 2 [55]. ...
Active cryptocurrency mining and trading comes with heavy electricity demand and increased emissions. Thus, cryptocurrency mining is prohibited in most economies. Consequently, miners relocate to regions or economies without these prohibitions and/or with relatively lower electricity rates. As such, presenting a nexus between the cryptocurrency and electricity markets, even at the global level. This article investigates the different forms of relationships existing between these markets. The conditional asymmetric volatility model with the Wald, nonparametric and parametric Granger causality tests are employed. The results confirm the existence of both unidirectional and bidirectional lead-lag return relationships between the cryptocurrency and electricity markets. Cryptocurrency returns drive electricity demand. This finding is homogeneous both on a global and strata (homogeneous groupings) basis. Also, the electricity market spills over significant volatilities to the cryptocurrency markets without feedback, nonetheless. Result-based policies are recommended towards green finance, decarbonization, and emission mitigations through the demand for electricity by the cryptocurrency markets. They include the use of clean and renewable electricity sources and technologies for cryptocurrency market activities.
... Thus, the central inquiry of this paper is: to what degree, and in what manner, does social media influence the Cosmos blockchain ecosystem and its financial performance? This exploration encompasses a review of the current state of research in this domain (Bonneau et al. 2015;Hayes 2019), an investigation into the repercussions of social media on Cosmos' financial metrics (Antonopoulos & Wood 2018), and a discourse on potential trajectories and perspectives for future research (Cosmos Network 2023). ...
... Data Science Journal DOI: 10.5334/dsj-2024-008 Therefore, the focal question of this paper is: To what extent, and in what ways, does social media exert influence on the financial performance and general dynamics of the Cosmos blockchain ecosystem? Our investigation will include a synthesis of the extant literature in this field (Bonneau et al. 2015;Hayes 2019), an empirical analysis of the impact of social media on Cosmos' financial indicators (Antonopoulos & Wood 2018), and a contemplative discussion on potential directions for future scholarly inquiry (Cosmos Network 2023). ...
The proliferation of blockchain technology heralds transformative impacts across various sectors, offering decentralization, transparency, and enhanced security. This paper explores the unique case of Cosmos, a scalable blockchain ecosystem designed to address the challenges of isolation and interoperability among existing blockchains. With its implementation of Tendermint consensus and the Inter-Blockchain Communication protocol, Cosmos stands out in facilitating seamless cross-blockchain interactions. The ATOM token serves a dual role as the network’s currency and a governance tool, empowering stakeholders in decision-making processes. Significantly, this study investigates the intricate relationship between Cosmos and social media platforms, examining how online sentiment influences voting on governance proposals, with a detailed analysis of two specific proposals. Furthermore, the paper delves into Cosmos’ integral role in the burgeoning Decentralized Finance sector, underscoring how its modular architecture fosters financial innovation. In the broader context, there are numerous PoS (Proof of Stake) networks. Cosmos, one of the foundational and longstanding projects, exemplifies a classic blockchain economic model, making it an ideal subject for this analysis. Finally, the paper assesses Cosmos’ contribution to the overarching Web3 vision, asserting its significance as a foundational element for a decentralized, user-oriented digital framework. Our findings illuminate Cosmos’ multifaceted impact, from technological innovation to reshaping societal structures, reaffirming blockchain’s potential in redefining modern paradigms. JEL Classification Codes: M31; M15; C58; L17 MSC 2010 Subject Classification Codes: 00A06; 37M10; 62M10; 91B84; 91B82
... One strand of the literature focuses on estimating the fundamental value of cryptocurrencies. For Cheah and Fry (2015), this value is zero, but other studies show that cryptocurrencies have a fundamental value (Dwyer, 2015) that depends on several factors, such as: (1) The cost of production (mining) (Garcia et al., 2014;Corbet et al., 2018;Gurkaynak, 2017;Hayes, 2019;Pagnotta and Buraschi, 2018;Bhambhwani et al., 2019); (2) The market size (Fantazzini et al., 2017); (3) The users and their behavior, more precisely the The Journal of Risk Finance network of users in a decentralized way (Abadi and Brunnermeier, 2018;Pagnotta and Buraschi, 2018;Bhambhwani et al., 2019;Wheatley et al., 2019;Sockin and Xiong, 2023); (4) Transaction fees (Easley et al., 2019;Biais et al., 2023); (5) Other financial and economic aspects such as returns, volatility, liquidity (Corbet et al., 2018), exchange rates, and trading volumes (Kristoufek, 2019). Some empirical studies find evidence of bubbles in the cryptocurrency market by assuming that the fundamental value of cryptocurrencies is strictly positive (Corbet et al., 2018). ...
Purpose
This paper examines the relationship between the degree of information asymmetry among investors and the occurrence of bubbles in cryptocurrency markets.
Design/methodology/approach
The study applies the Philipps, Shi and Yu (PSY) methodology to identify bubbles in 74 cryptocurrencies from July 2014 to April 2021.
Findings
The findings indicate that there is a negative relationship between the degree of information asymmetry among investors and the number and duration of bubbles across cryptocurrencies.
Originality/value
This finding supports the riding-bubble argument of Asako et al. (2020), which suggests that when the information asymmetry among investors is high, rational investors are less certain about what irrational, inexperienced investors might decide. This strategic uncertainty leads rational investors to close out their positions more quickly, resulting in a shorter duration of the bubble and a reduced propensity for new bubbles to emerge. The study’s findings hold regardless of the proxies used to measure information asymmetry and noise trading, cryptocurrency characteristics and regression model specifications.
... Kripto para birimlerindeki değerleme belirsizliği ve kısıtlı arbitraj olanakları nedeniyle davranışsal finans ve yatırımcı duyarlılığı açısından hisse senetlerine benzer tepkiler verebileceğini varsayan yaklaşımlar bulunmaktadır (Huang vd., 2024: 123). Bunun yanı sıra kripto para birimlerinin değerlerinin piyasadaki duygulardan ziyade düzenleyici algoritmalardan etkilendiği için hisse senedi gibi geleneksel varlık değerleme modellerinden farklılaştığı iddia edilmiştir (Hayes, 2017(Hayes, : 1319(Hayes, -1320. Kripto para piyasalarındaki duygu göstergelerinin birçoğu yatırımcı davranışlarını hesaba katmadan esas olarak işlem hacmi ve volatiliteyi yansıtmaktadır. ...
This paper investigates the short and long-term relationship between Bitcoin returns and the Crypto Fear and Greed Index, which represents investor sentiment in cryptocurrency markets, and the direction and intensity of this relationship. The paper analyzed daily data sets for the period 01.02.2018-07.09.2022 were analyzed with the A-ARDL (Augmented Autoregressive Distributed Lag) method. In the study, where financial stress and VIX Fear indices were used as control variables, it was found that investor sentiment positively and significantly affected Bitcoin returns in the short and long term. Accordingly, it was determined that the increase in the feeling of greed (fear) positively (negatively) affected Bitcoin returns. It can be stated that this finding is compatible with behavioral finance and investor sentiment theories.
... Specifically focussing on the transactions market and the associated supply and demand curves, some previous research have served as a starting point for our study. This is the case of the original analysis linking transaction fees, block size and system security (Houy, 2014), the introduction of the block space supply curve and the mempool demand curve (Rizun, 2015), the models for calculating the marginal cost of production in Bitcoin (Hayes, 2017), further back-tests of the production cost (Gottschalk, 2022;Hayes, 2019;Kim, T., 2017) and empirical econometric approaches to this market (Huang et al., 2017;Ilk et al., 2021;Jalan et al., 2022;Tsang & Yang, 2021). ...
Blockchain transactions market is expected to gain momentum in the coming years, in a context with gradual transition to fee-regime in many cryptocurrencies, the expansion of blockchain technology to different business areas and the requirement for high transaction throughput in new blockchain-based applications. In this context, the economic assessment of the supply and demand curves defining the transactions market is key to recognize its potential weaknesses, but also to minimize risks and to improve operational efficiency when designing or upgrading blockchain-based applications. The research covers a gap by conducting an empirical analysis of these curves in Bitcoin, based on an extensive dataset spanning two time periods in 2021 and 2023 selected as having different levels of Mempool congestion. The empirical findings support the understanding of why Bitcoin transaction fees are subject to high volatility and how the protocol evolutions made to date have shifted the supply curve. The demand curve, although relatively elastic around the equilibrium price, turns out to be extremely dynamic. On the other hand, the inelasticity of the supply curve, described by an exponential distribution, explains the sharp variations in transaction fees observed under demand shocks. The results bring to light the importance of the transactions market layout as an element of control over the intrinsic problems associated with an imperfect competition, whereas additional sustainability and security aspects beyond pure economic considerations are to be taken into account in the design of this market.
... As previously stated, Bitcoin's rising popularity and acceptance among businesses increases its perceived validity and utility as a financial asset. This, together with the emergence of marketplaces and derivative markets, highlights the importance of merchant acceptance in enabling greater adoption and value generation for digital currencies such as Bitcoin (Hayes, 2017). The availability of merchants and businesses that accept digital currency as a form of payment can significantly impact user adoption. ...
... A growing body of work studies the dynamics of cryptocurrency markets specifically. Observational data analyses, with sometimes conflicting results, have been used to examine competition between cryptocurrencies for market volume [28]; to compute the fundamental value of cryptocurrencies [40]; to investigate the efficiency of bitcoin markets [79,63]; to confirm the presence of speculative behavior in bitcoin markets [58,20]; to provide evidence for non-fundamentals-driven trading behavior in altcoin markets [26]; and to document how factors such as fundamental value [52,14] or online search and discussion activity [51,30] are related to cryptocurrency prices. A recent study closely related in spirit to our own provided observational evidence of market manipulation in USD-BTC markets [29]. ...
As cryptocurrencies gain popularity and credibility, marketplaces for cryptocurrencies are growing in importance. Understanding the dynamics of these markets can help to assess how viable the cryptocurrnency ecosystem is and how design choices affect market behavior. One existential threat to cryptocurrencies is dramatic fluctuations in traders' willingness to buy or sell. Using a novel experimental methodology, we conducted an online experiment to study how susceptible traders in these markets are to peer influence from trading behavior. We created bots that executed over one hundred thousand trades costing less than a penny each in 217 cryptocurrencies over the course of six months. We find that individual "buy" actions led to short-term increases in subsequent buy-side activity hundreds of times the size of our interventions. From a design perspective, we note that the design choices of the exchange we study may have promoted this and other peer influence effects, which highlights the potential social and economic impact of HCI in the design of digital institutions.
... DLT's are already being employed in diverse business applications and have matured significantly since the inception of the first established network of this kind, Bitcoin [1]. This is the first and most popular digital currency and payment system employed on a DLT platform [2] and was the first of its kind to eliminate the need for a single entity that accounts for and controls a currency [3]. Its success has led to a market capitalisation that peaked USD 1.43 tn in March 2024 and the subsequent emergence of numerous alternative digital currencies (also known as cryptocurrencies or cryptoassets) such as LiteCoin, Ethereum, Ripple, and Bitcoin Cash. ...
The latest advancements in distributed ledger technology (DLT) and payment architectures such as the UK’s New Payments Architecture present opportunities for leveraging the hidden informational value and intelligence within payments. In this paper, we present Smart Money, an infrastructure capability for a central bank digital currency (CBDC) which enables real-time value-added tax split payments, oversight, controlled access, and smart policy implementation. This capability is implemented as a prototype called Making Tax Smart (MTS), which utilises the open-source R3 Corda DLT framework. The results presented herein confirm that it is feasible to build an MTS capability which is scalable and co-exists with the current payment systems. Smart Money CBDC has the potential to mobilise payments data, transforming the role of money from a blunt instrument to a government policy sensor and actuator without disrupting the existing money system. DLT, smart contracts, and programmable money have a crucial role to play with benefits for government departments, the economy, and society as a whole.
... As cryptocurrency continues to gain traction, its attractiveness stems from its potential use not only as a medium of exchange but also as a speculative asset and mining opportunity (Hayes, 2017). Cryptocurrencies such as Bitcoin have even been found to act as a hedge against market volatility (Bouri et al., 2021). ...
In the age of digital payments, cryptocurrencies have gained significant attention as an alternative investment option. However, security risks such as phishing, hacking, and fraudulent exchanges present challenges for investors. This study aims to assess the level of awareness among the general public in Malaysia regarding cryptocurrency security risks. A quantitative research method was employed, using a survey questionnaire distributed to 150 Malaysian citizens via social media platforms. The questionnaire explored respondents' knowledge of cryptocurrencies, awareness of security risks, and protective measures such as security programs, two-factor authentication (2FA), and education. The results of the regression analysis show that the installation of security programs, 2FA, and public education are all significant predictors of increased awareness of cryptocurrency security risks, with a combined R² value of 0.523. This suggests that 52.3% of the variance in awareness is explained by these factors. The study concludes that strengthening security measures and providing education can significantly improve public understanding of cryptocurrency risks, leading to safer investment practices. The implications of these findings highlight the need for targeted education and security initiatives to enhance public confidence in cryptocurrency, making digital currency investments more secure
... Bu süreç merkezi bir otorite olmadan işlemlerin dağıtılmış olarak doğrulanması ile gerçekleşmektedir (Mukhopadhyay vd., 2016). Bitcoin, güvenli şifreleme ile blok zinciri olarak bilinen paylaşılan bir defter teknolojisini kullanan merkezi olmayan, dağıtılmış ağlar aracılığıyla çevrimiçi olarak var olan dijital para ve ödeme sistemlerinden olan kripto para birimlerinden en popüler olanıdır (Hayes, 2017).Bitcoin'in geliştirilmesi ve 2009 yılında blok zincirinin benimsenmesi ile, benzer kriptografi teknolojisi kullanan ancak farklı algoritmalar kullanan altcoinler ortaya çıkmaya başlamıştır (Kuo Chuen, Guo ve Wang, 2017). CoinMarketCap'e göre, Nisan 2024 itibari dünya genelinde 56,65 milyar ABD doları hacmi ve 2,58 trilyon ABD doları piyasa değerine sahip 9500'den fazla kripto para birimi işlem görmektedir. ...
A bibliometric analysis was conducted for 6175 publications with the keyword "cryptocurrency" scanned in the Web of Science database. Then, social network analysis was applied to the data obtained and the relationships between authors, publications and keywords were visualized. When the publications by years are analyzed, the first publication on cryptocurrency was realized in 2014 and publications continue to increase today. Of the studies on cryptocurrency, 42% were conducted in the field of computer science and 11% in the field of finance. Shean Corbet was found to be the author with the strongest connection to cryptocurrency with 37 publications and 1929 citations. It was determined that 62% of the studies used between 4 and 6 keywords, and the keywords cryptocurrency, blockchain, Bitcoin, Ethereum and volatility were frequently used together. It was seen that the keywords used were divided into 255 clusters.
... Зерттеулердің авторлары инвесторлардың жабық ұтымдылығы идеясының негізін ұсынды, бұл белгісіздік жағдайында инвесторлардың шешім қабылдау процесі эвристика, табыну, перспектива және танысу сияқты қарапайым ережелердің әсерінен болатынын білдіреді [10]. Бұл ережелер көптеген жағдайларда өте пайдалы болып шығады және сәтті болжамдар береді. ...
The relevance of the research topic is due to the fact that many crypto investors are attracted by the high liquidity of cryptocurrencies, low transaction costs and ease of transactions via the Internet. In contrast from Fiat currencies, corporate stocks, and bonds, cryptocurrencies do not have an underlying value. demand therefore market cost to a greater extent depends on how wellknown and popular this cryptocurrency is. Also, the price of cryptocurrencies is influenced by market sentiment, namely the thoughts, feelings and emotions of investors regarding the asset. With the help of traditional asset valuation models, it is impossible to qualitatively explain the latest changes in the price of cryptocurrencies. However, some financial models point to that cryptocurrency is currently overvalued. Apparently, the hypothesis of financial instability is better than any of the verified economic theories suitable to explain recent changesin prices of cryptoassets. The theory suggests that because the cryptocurrency market is moving against the macroeconomic fundamentals of the economy, emotions are a major factor. determining demand on a given market. In this article, the authors examined the influence of behavioral financial factors on investment decisions in the cryptocurrency market. Multiple regression analysis was used to examine this effect. The purpose of the article is to study the development of cryptocurrency in Kazakhstan and assess the impact of events on the value of cryptocurrency. Based on this goal, the authors put forward the following tasks: to analyze and evaluate the use of cryptocurrencies in the modern economy; explore the features of cryptocurrency pricing.
... DLT's are already being employed in diverse business applications and have matured significantly since the inception of the first established network of this kind, Bitcoin [1]. This is the first and most popular digital currency and payment system employed on a DLT platform [2] and was the first of its kind to eliminate the need for a single entity that accounts for and controls a currency [3]. Its success has led to a market capitalisation that peaked $1tn in April 2021 and the subsequent emergence of numerous alternative digital currencies (also known as cryptocurrencies or cryptoassets) such as LiteCoin, Ethereum, Ripple and Bitcoin Cash. ...
The latest advancements in Distributed Ledger Technology (DLT), and payment architectures such as the UK's New Payments Architecture, present opportunities for leveraging the hidden informational value and intelligence within payments. In this paper, we present Smart Money, an infrastructure capability for a Central Bank Digital Currency (CBDC) which enables real-time Value Added Tax split payments, oversight, controlled access and smart policy implementation. This capability is implemented as a prototype, called Making Tax Smart (MTS), which is based on the open source R3 Corda framework. The results presented herein confirm that it is feasible to build a MTS capability which is scalable and co-exists with the current payment systems. Smart Money CBDC has the potential to mobilise payments data in order to transform the role of money from a blunt instrument to a government policy sensor and actuator without disrupting the existing money system. DLT, smart contracts and programmable money have a crucial role to play with benefits for government departments, the economy and society as a whole.
... The mechanism for selling cryptocurrencies operates similarly to the sale of virtual currencies used as a business field through speculation to obtain price differences. Traders profit from selling cryptocurrencies purchased when the value is low and reselling when the price rises since the value fluctuates every second (Hayes, 2017;Azizah & Irfan, 2020 Indonesia is predominantly made up of Muslims and almost all events are based exclusively on contracts related to halal quality. Therefore, these activities are regulated and warned to be accessible to the entire population. ...
Cryptocurrency is a growing fintech trend frequently encountered in various moderneconomic activities. Therefore, this research aimed to provide knowledge and understanding of cryptocurrency, particularly from the perspective of Islamic finance and economics using secondary data obtained from literature. As a digital financial transaction system, cryptocurrency fundamentally uses relatively new technology. However, the legal nature still needs further examination without constituting a form of violation. In Indonesia, the government has yet to adopt a definitive stance on the presence of cryptocurrency, thereby permitting its usage. The results showed that cryptocurrency investment includes substantially greater risk compared to others due to the inherent challenge of predicting the value. From the perspective of Islamic finance and economics, the transactions are considered to lack clarity in terms of quality and quantity, containing elements of uncertainty (gharar). Moreover, the concept of Bitcoin as a transaction tool is forbidden (haram) by the Indonesian Ulama Council since the project contains uncertainty and does not comply with the existing regulations. The implications of the research emphasize the necessity ofavoiding dubious activities, such as cryptocurrency, as well as transactions leading to higher harm (madharat) compared to benefits, particularly from the perspective of Islamic finance and economics.
... In a certain interpretation, the creation of cryptocurrency is a stage of evolution of monetary forms that corresponds to modern economic processes of "spreading networking" (Hayes, A. S., 2017). At the same time, the possibility of the emergence and provision of cryptocurrency circulation testifies to the profound transformations that have arisen with the advent of information and network technologies not only in economic activity but also in human life. ...
In the conditions of a steady surplus of up-to-date information, institutional and value-based tools for reducing the uncertainty of economic activity fade into the background, the paternity that progresses as a result of a combination of the short-term temporal paradigm, historically and institutionally inherent in the Western business traditions and becomes an important structural element, with the fundamental innovation of the information-network economy, the actual manifestation of which is the production of excess information and the creation of conditions for reproduction of uncertainty at the higher level. Cryptocurrencies emphasize the crisis of the banking institutions of financial intermediation as a result of the trust destruction as a natural result of the dominance of the financial component in the system of complementary interaction between financial intermediaries and subjects of the real economy sector, which in turn led to the crisis of financial intermediation and led to the desire of financial services consumers for operating activity without any mediation. Nowadays, the first cases of blockchain technology influence on the processes of reformatting the basic principles of human society development - information asymmetry and trust, which can testify to the depth of the modern transformation transition, are observed. An indirect development effect regarding information-network economy is the intensification of households` credit activity and the development of financial-oriented patterns of behavior, which indicate a prevailing focus on short-term prospects in economic and social activity, an increase in the value of self-interest over the interests of family and immediate surroundings, and a reduction in the impact of long-term hierarchical responsibility (in the generations context) on financial decision-making processes. A striking result of these patterns is an increase in household debt, which leads to a narrowing of economic freedom. Financial culture is gradually losing its role as a basic factor in the development of financial patterns of behavior, that in turn influences financial decision-making process, meanwhile the factors of economic and social conditions, banking marketing tools using client databases are updated.
This study investigates the very unpredictable character of the cryptocurrency market, attributing its volatility to variables such as news events, market sentiment, and price deception. The study focuses on the Indian environment and explores people’s attitudes and experiences with cryptocurrencies, utilising a questionnaire to collect data on knowledge, trust, understanding, and other key investing characteristics. The report assesses the impact of various media, communication platforms, YouTubers, statistics, and investment advisors on cryptocurrency trading habits and price volatility. The primary goal is to obtain a more nuanced knowledge of Indian investors’ motivations for investing in cryptocurrencies and their propensity to utilise them for diverse purposes. This study hopes to help businesses, policymakers, and investors make informed decisions in the volatile cryptocurrency ecosystem by explaining customer motives and concerns. Finally, the study aims to contribute to constructing an enhanced, accountable, and long-lasting digital currency system that aligns with the values and expectations of customers and audiences.
In this research work, we developed a mathematical model of a digital currency market, involving daily closing price as a function of time. We proposed the Artificial Neural Network (ANN) model. We observed that our ANN model was able to predict the daily closing price of Bitcoin and also make six weeks forecast to a reasonable degree of accuracy. We equally observe that the time dependent ANN model can actually give digital currency traders and investors a clue on when to trade off their digital assets with minimum risk. We therefore, recommend that ANN model should be incorporated into digital currency trading platforms as a signal tool to enable digital currency traders take more informed and less risky trading decisions. From our findings, we would advise traders who wish to employ ANN model to consider a smaller time frame say a few weeks’ time interval for their predictions. We observed also that ANN models have limitations when it comes to manual computation or implementation in Microsoft Excel, especially when dealing with very large input values. This is because of the saturation characteristic of our ANN inner layer activation function (viz; tanh function) which can lead to identical output values for different input values, making it difficult to replicate the ANN model's behavior. Furthermore, ANN models often involve complex interactions between multiple neurons, layers, and activation functions, which can be challenging to replicate manually.
In this research work, we developed a predictive model for digital currency prices, involving daily closing price as a function of time. We used the Geometric Brownian motion stochastic differential equation which was solved using inbuild functions in Microsoft Excel. While we used the Bitcoin as our case study, our model was able to predict the daily closing prices of Bitcoin to a reasonable degree of accuracy. We equally observe that the time dependent Geometric Brownian motion stochastic differential equation cannot give digital currency traders and investors a clue on when to trade off their digital assets. Thus, it become very risky using our model to make well informed trading decisions. We therefore, recommend that for minimum risk, trades and investors in digital currencies should consider a combination of other signal tools to take more informed and less risky trading decisions.
The rapid adoption and growing prominence of Bitcoin and other cryptocurrencies have sparked significant interest and debate among economists, policymakers, and financial analysts. In Sub-Saharan Africa, where traditional financial systems often face challenges such as limited access to banking services, high transaction costs, and volatile currencies, Bitcoin presents both opportunities and risks. Understanding the interplay between Bitcoin and key monetary indicators such as monetary aggregates, exchange rates, and interest rates can provide valuable insights for policymakers and stakeholders in these economies. This study therefore seeks to investigate the nexus between monetary indicators and Bitcoin in selected Sub-Saharan African countries using a Panel ARDL (Autoregressive Distributed Lag) approach. The analysis focuses on understanding the dynamic relationship between key monetary variables, such as monetary aggregates, exchange rates, interest rates, and Bitcoin prices, from 2010 quarter three to 2022 quarter four. The findings reveal several significant relationships between monetary indicators and Bitcoin across the selected Sub-Saharan African countries. In the short run of the Panel Ardl monetary aggregates exhibit a positive relationship with Bitcoin prices, indicating that changes in the money supply may influence the demand for cryptocurrencies. Conversely, both exchange rates and interest rates show a negative relationship with Bitcoin prices in the short run, suggesting that currency depreciation and higher borrowing costs may reduce demand for Bitcoin. In the long run, the relationship between monetary aggregates and Bitcoin remains positive, emphasizing the potential influence of money supply on cryptocurrency markets over time. However, the significance of exchange rates diminishes, indicating a less pronounced impact in the longer term. Interestingly, interest rates continue to exhibit a significant negative relationship with Bitcoin prices in the long run, highlighting the persistent effect of borrowing costs on cryptocurrency demand. These results have important implications for policymakers, investors, and researchers interested in the intersection of monetary policy and cryptocurrency markets in Sub-Saharan Africa. Policymakers may consider the impact of monetary policy decisions on cryptocurrency adoption and market dynamics, while investors can use these insights to inform their investment strategies.
The world of cash and money is evolving right in front of our eyes. Digitized
resources and innovative monetary channels, tools, and frameworks are establishing
new norms for monetary exchange and shaping alternative capital channels. Rather
than depending on conventional monetary organizations that confirm and ensure your
exchanges, cryptographic money exchanges are checked by the client's PCs signed
into the money's organization. Because the currency is guaranteed and encoded,
expanding the cash supply at a predetermined algorithmic rate becomes impossible.
All clients know about the algorithmic rate. Like this, since every calculation has a
rooftop limit, no digital currency can be delivered or "mined" past that. However,
there are more than 1000 digital currencies in the market. A significant improvement
in several online customers has started computerized express thoughts and made every
other business endeavor wonder Cryptocurrency to works of art with the financial
activities like shopping, advancing and supplanting. Digital money refers to tangible
and intangible items exchanged electronically in various applications and
organizations, such as online social games, virtual universes, and shared
organizations. In recent years, the use of virtual money has expanded to include a
wide range of contexts. In this paper, we will discuss the benefits and challenges
cryptocurrency is facing in INDIA are.
Many technologies enter our lives with the great advancement in information technology. These technological developments affect and change our life directly. According to affection of our life, cryptocurrency is the most popular technology. This technology, which is a relatively mixture of currency and cryptology, is used all over the world with increasing acceleration. So, cryptocurrency technology is still used to make payments without banks and is considered as virtual currency. Besides of this opportunity, cryptocurrency has few challenges. Most dangerous and critical challenge for environment is energy consumption in mining of cryptocurrency. Blockchain is the technology which is used in mining process and it consumes more and more energy. According to this critical challenge, Ethereum which is one of the popular cryptocurrencies, was used in an experimental study to analyze energy consumption. Experiment examined the data from Mar 30, 2017 to Dec 30, 2019. These data were compared with another popular cryptocurrency which is bitcoin in order to find the better one for environment. In this study, the data from 196 GPUs were examined and electricity consumption and gain were analyzed. Totally, 3 different types of GPU brands were used, and the brand of the units, the power consumed, and the electricity unit price in the country where it was tested were analyzed respectively.
The rise of fintech, or the combination of digital financial services and technology,
represents a turning point in the evolution of financial institutions in an ever-changing financial environment. This Thesis explores the operational aspects and regulatory frameworks in the European Union. Fintechs are able to effectively provide services across the EU market due to the modern EU legislation, the passporting mechanism, in particular. These services involve complex cross-border and interregional operations, which are associated with risks and connected to KPIs.
Chapter 1 presents the systematic literature review to determine the lacuna in the issue of KPIs formation for financial institutions. The genesis of fintech is also explored, with specific emphasis on the regional dimensions. The taxonomy of fintech is presented. The region of research application is identified. Special attention is paid to the operations of the European Central Bank (ECB) as a financial regulator in the EU region.
Chapter 2 reviews and analyses the impact of EU regional and national policies on
financial institutions. The conditions for the functioning of fintech are compared, highlighting the regional peculiarities. The taxonomy of digital financial products and their representation in different EU regions is presented. The comparative analysis between e-money products and crypto-based assets demonstrates their characteristics and operating environment. The taxonomy and life cycle of digital assets are shown. It also identifies the pricing components for digital and cryptocurrencies.
Chapter 3 determines the KPIs and KRIs for financial institutions. This is done on the
basis of the expert panel's estimates. The currently limited use of appropriate KPIS is discussed. In addition, the development of financial services in smart cities is shown and the regional aspect of fintech functioning in smart cities is specified. The opportunities for smart cities to use fintech and financial services as part of the sharing economy are also identified. In this chapter, two statistical models are presented. The PLS-SEM analysis is used to evaluate the relationships between the risks of internal processes and KPIs (Model 1) and the risk of compliance with regional legislation and KPIs (Model 2).
At the end of the study, conclusions are drawn and recommendations formulated.
Globalization and the changes that have affected the world economy conditioned the development of new models of thinking, investing, trading and payment methods in the world economy. End of XX and beginning of the XXI century was marked by rapid technological progress, which has not bypassed any economic sector, and all households have experienced the change. Cryptocurrencies represents a new model of trade and payments, but also a way for making some form of earnings. It is a form of property that is used as a digital asset exchange using cryptographic algorithms for "mining" new values, but also as a way of ensuring the security of transactions in a given syste. It's still early for assessments. The future might show what kind of impact would this kind of payment have, however, we believe that no cryptocurrencies will be recognized as a legitimate competitor in sovereign currencies.
The efficient market hypothesis encounters scrutiny from behavioral finance insights, highlighting the pronounced influence of investor emotions on market dynamics, a phenomenon especially evident in the tumultuous cryptocurrency markets. This investigation utilizes the autoregressive distributed lag (ARDL) model and the error correction model (ECM) to examine the impact of the Bitcoin Sentiment Index (BSI), also known as the Crypto Fear & Greed Index (CFGI), on Bitcoin returns, leveraging monthly data spanning from 2016 to 2021. The ARDL analysis identifies a positive and statistically significant correlation between BSI and Bitcoin returns, indicating that strong sentiment may beneficially affect Bitcoin’s long-term returns. Concurrently, the ECM analysis reveals that fluctuations in the BSI positively influence the changes in Bitcoin returns in the short term. The error correction term demonstrates a significantly negative value, signifying an expedient adjustment toward long-term equilibrium following transient disturbances. These findings remain robust upon the integration of additional macroeconomic control variables. Unlike prior studies centered on singular sentiment indicators or limited temporal analyses, this research employs an extensive sentiment measure over an extended duration. The integrated application of ARDL and ECM methodologies facilitates a thorough and rigorous examination of short-term fluctuations alongside long-term equilibrium dynamics.
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.