“…Baur et al . () reach a similar conclusion based on the frequency and value of transactions being reported in the Blockchain. Fred Ehrsam, a co‐founder of Coinbase, one of the leading digital wallet providers, estimated that 80–95% of transactions in 2013 and 2014 using Coinbase were related to speculation (see Goldman Sachs, ).…”
Section: What Purpose Do Crypto‐currencies Serve?supporting
confidence: 74%
“…Baur et al . (, p. 9) identify 135,000 addresses that had received newly minted coins by 2013, which places an upper limit on the number of miners that have been successful in minting coins.…”
Section: Payment/exchange Mechanismsmentioning
confidence: 99%
“…In contrast, even with recent data from 1 January to 12 October, 2017, Bitcoin was facilitating around 270,000 transactions per day in the world as a whole. 26 Baur et al (2018) attempt to classify users by the frequency and value of transactions undertaken, identifying also miners that receive newly generated bitcoins. According to their classification, 'currency users', those making just small transactions, were making about 5% of transactions by value, falling to less than half that number in 2014.…”
Section: Crypto-currency and The Basic Functions Of Moneymentioning
We introduce the distributed ledger (blockchain) technology of crypto‐currencies. We examine the ‘monetary’ attributes of crypto‐currencies, and describe some of the reasons they have been adopted. The paper discusses the mechanics of Bitcoin – the original crypto‐currency – to illustrate the fundamental elements of decentralized crypto‐currencies. We then provide a high‐level summary of the implications of crypto‐currencies for consumers, financial systems, and for monetary and regulatory authorities. We argue that crypto‐currencies are unlikely to supplant traditional fiat currencies and we anticipate an enduring role for financial intermediaries in facilitating credit.
“…Baur et al . () reach a similar conclusion based on the frequency and value of transactions being reported in the Blockchain. Fred Ehrsam, a co‐founder of Coinbase, one of the leading digital wallet providers, estimated that 80–95% of transactions in 2013 and 2014 using Coinbase were related to speculation (see Goldman Sachs, ).…”
Section: What Purpose Do Crypto‐currencies Serve?supporting
confidence: 74%
“…Baur et al . (, p. 9) identify 135,000 addresses that had received newly minted coins by 2013, which places an upper limit on the number of miners that have been successful in minting coins.…”
Section: Payment/exchange Mechanismsmentioning
confidence: 99%
“…In contrast, even with recent data from 1 January to 12 October, 2017, Bitcoin was facilitating around 270,000 transactions per day in the world as a whole. 26 Baur et al (2018) attempt to classify users by the frequency and value of transactions undertaken, identifying also miners that receive newly generated bitcoins. According to their classification, 'currency users', those making just small transactions, were making about 5% of transactions by value, falling to less than half that number in 2014.…”
Section: Crypto-currency and The Basic Functions Of Moneymentioning
We introduce the distributed ledger (blockchain) technology of crypto‐currencies. We examine the ‘monetary’ attributes of crypto‐currencies, and describe some of the reasons they have been adopted. The paper discusses the mechanics of Bitcoin – the original crypto‐currency – to illustrate the fundamental elements of decentralized crypto‐currencies. We then provide a high‐level summary of the implications of crypto‐currencies for consumers, financial systems, and for monetary and regulatory authorities. We argue that crypto‐currencies are unlikely to supplant traditional fiat currencies and we anticipate an enduring role for financial intermediaries in facilitating credit.
“…of electronic payment in online commerce (Nakamoto, 2008), cryptocurrencies have aroused keen interest since their introduction, mainly as an investment asset (Baur, Hong and Lee, 2018). However, given their volatile nature, the advance of cryptocurrencies as a new investment asset can exert additional risk spillover on existing financial assets and has the potential to raise systemic risk level of the financial market.…”
The advance of cryptocurrencies has sparked wide concern over their interplay with the existing global financial market. This paper analyzes the risk spillover relation between cryptocurrencies and major financial assets, and unravels how cryptocurrencies could influence global financial systemic risk. We find that cryptocurrencies function as a separate risk source from traditional assets. Major legislative, financial and technological events in the cryptocurrency market may affect risk spillover dynamics. Although the overall penetration of cryptocurrencies is not yet deep, introducing cryptocurrency can significantly increase the systemic risk to traditional markets during low risk level episodes.
“…com/eran-eyal-bitcoin-will-rise-above-100000/ (assessed date: February 1, 2018)). The article mentions that some blockchain backers believe Bitcoin can exceed $100,000, while others think that the cryptocurrencies are products of speculation rather than the mediums of exchange [1,2] and Bitcoin is in a bubble period [3]. In order to increase the price discovery function of Bitcoin in the financial market and meet the needs of investors in indirect cryptocurrencies, US financial firms CME and CBOE have launched Bitcoin futures, respectively.…”
We investigate the cross-correlations of return-volume relationship of the Bitcoin market. In particular, we select eight exchange rates whose trading volume accounts for more than 98% market shares to synthesize Bitcoin indexes. The empirical results based on multifractal detrended cross-correlation analysis (MF-DCCA) reveal that (1) the nonlinear dependencies and power-law cross-correlations in return-volume relationship are found; (2) all cross-correlations are multifractal, and there are antipersistent behaviors of cross-correlation for q = 2; (3) the price of small fluctuations is more persistent than that of the volume, while the volume of larger fluctuations is more antipersistent; and (4) the rolling window method shows that the cross-correlations of return-volume are antipersistent in the entire sample period.
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