Velocity of bitcoin
If central banks and governments wanted to finish off cryptocurrencies, that moment has now passed and each day that they continue to exist, is a challenge to the legitimacy of fiat-based institutions. In the economic life of man, what constitutes value and qualifies as a medium of exchange is a far more plastic concept than anyone living in that age often gives credit for. And contrary to popular opinion, our concept of the various forms that money should take also evolve relatively rapidly. In March, U. Federal Reserve Chairman Jerome Powell, speaking at a virtual panel discussion on digital banking hosted by the Bank for International Settlements, made clear that the central bank was keeping its focus on more traditional investments and added,.
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Velocity of bitcoin
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Record low Bitcoin velocity suggests BTC may ‘move to the downside’
Cryptocurrencies often tend to maintain a publically accessible ledger of all transactions. This open nature of the transactional ledger allows us to gain macroeconomic insight into the USD 1 Trillion crypto economy. We specifically focus on the aspect of wealth distribution within these cryptocurrencies as understanding wealth concentration allows us to highlight potential information security implications associated with wealth concentration.
We also draw a parallel between the crypto economies and real-world economies. To adequately address these two points, we devise a generic econometric analysis schema for cryptocurrencies. Our analysis reports that, despite the heavy emphasis on decentralization in cryptocurrencies, the wealth distribution remains in-line with the real-world economies, with the exception of Dash.
This suggests that the free-market fundamentalism doctrine may be inadequate in countering wealth inequality within a crypto-economic context: Algorithmically driven free-market implementation of these cryptocurrencies may eventually lead to wealth inequality similar to those observed in real-world economies.
Economic freedom is one of the foundational pillars of the crypto-anarchist movement Ludlow, Crypto anarchism is a political ideology that focuses on using cryptographic methods to attain anonymity, freedom of speech, and freedom of trade May, often through a counter-economic environment. A counter-economic environment facilitates financial transactions beyond the purview of a government, leading to freedom of trade London, , where a counter economy includes the free market, the black market, and the underground economy.
These crypto-anarchist objectives are materialized primarily through recent developments in cryptography, privacy-focused distributed networks, and decentralized peer-to-peer currencies Chohan, , where their appeal is as an alternative to traditional financial system in that they embody increased freedom to trade DeVries, The adoption of trade-friendly regulations has been suggested to improve wealth distribution by encouraging the flow of wealth among nations Bank, ; Irwin, This article explores that line of reasoning, evaluating the hypothesis that wealth distribution improves in the absence of restrictive trade regulation, in a cryptocurrencies context, using measures of wealth concentration.
This is a contentious hypothesis because according to the inequality model developed by Boghosian , the free market model adopted by cryptocurrencies is not without limitations in this regard, suggesting that wealth naturally trickles up in a free market economy leading to wealth inequality. In contrast, many cryptocurrency researchers have suggested that blockchain might provide a solution to the issue of wealth inequality in a free market-based economy Chohan, ; van den Hoven et al.
For instance, Othman et al. However, it must be acknowledged that participation in these crypto economies is subjected to many barriers to entry, such as internet access requirement and high transaction fee. Major cryptocurrencies tend to maintain an open distributed ledger of all financial transactions executed to date. This transparent nature of cryptocurrencies can be used to measure wealth concentration in these cryptocurrencies. Thus, this research work assesses the following question:.
Past reports such as Griffin and Shams have suggested that manipulation of exchange rates through wealth concentration is feasible and has been observed in the cryptocurrency market. According to Sai et al. This potential for successfully executing security attacks due to large wealth concentration makes it essential to understand the current state of wealth distribution.
The exact implementation of a cryptocurrency-based financial system can vary significantly in different cryptocurrency implementations. Thus, this fairer wealth distribution hypothesis needs to be assessed for a range of cryptocurrencies to increase the generality of the findings.
This paper will conduct an empirical evaluation of wealth concentration in 8 major cryptocurrencies in two broad categories: Bitcoin-like 6 cryptocurrencies including Bitcoin and Ethereum-like 2 cryptocurrencies including Ethereum. Bitcoin is currently the largest cryptocurrency by market capitalization, with a current valuation of USD Billion CoinMarketCap, Many prominent cryptocurrencies are based on the fundamental design of Bitcoin by forking copying the source code of Bitcoin Neudecker and Hartenstein, We refer to these cryptocurrencies collectively as Bitcoin-like cryptocurrencies.
For our empirical review, we shortlist the top six Bitcoin-like cryptocurrencies including Bitcoin itself based on the market capitalization: Bitcoin, Litecoin, Bitcoin Cash, Dash, ZCash, and DogeCoin.
The second category of cryptocurrencies selected for the analysis is Ethereum-like cryptocurrencies. Ethereum currently has a total market capitalization of USD Billion CoinMarketCap, , is ranked as the second-highest valued crypto asset and allows for transactions to contain transactional logic in the form of Turing complete contracts.
Ethereum is also an interesting case study for wealth inequality analysis as Ethereum has a provision to allow users to write smart contracts to dictate economic behavior over the cryptocurrency in the form of a crypto token 1 Buterin et al. Similar to Bitcoin forks, Ethereum also has several forks; among these, the most prominent example is Ethereum Classic. We review both Ethereum and Ethereum Classic for our study. We also review the current January state of wealth distribution in the top five tokens issued on the Ethereum platform for our analysis.
We conduct an econometric analysis by calculating macroeconomic measures of inequality for these cryptocurrencies and contrasting these measures with traditional economies. We also examine an extrinsic factor, policy changes, to understand if factors outside the cryptocurrencies may influence the wealth distribution in the crypto economies.
We also perform econometric analysis on the top five tokens deployed on the Ethereum platform, which helps us to understand the impact of policy configurability on wealth distribution as these tokens allow programmers to define the economic policies that govern these assets. This methodology considers the volume, velocity, and variety of data generated by different forms of cryptocurrencies. Specifically, it reports on the potential relationship between the type of policy changes and the wealth concentration Section 4.
In addition, based on our reflections on the empirical protocol adopted, the paper proposes a set of reverse engineering techniques that can be used by future researchers in their analysis of wealth concentration to partially circumvent cryptocurrency privacy provisions Section 6.
We also specifically report on how the current state of econometrics analysis in cryptocurrencies is insufficient to capture the economic aspects of these complicated assets Section 6. Economic inequality can be broadly categorized into income and wealth inequality Simpson, Income inequality examines the distribution of income in a country or political union of nations.
The notion of income inequality does not directly translate to crypto economies as the open ledger maintained by these crypto economies only contains information relevant to the wealth determined by units of currencies owned by each participant.
Wealth inequality examines the economic heterogeneity of a country or a political union Cagetti and De Nardi, The exact definition of wealth varies depending on the application area; however, wealth is generally defined in terms of financial assets Hamilton and Hepburn, A financial asset is defined as a non-physical or physical asset that can be used for financial transactions Moles and Terry, Then wealth inequality is measured based on the distribution of these financial assets over a population.
However, calculating wealth inequality is harder than income inequality as individuals can have negative wealth due to financial liabilities such as credit and loans.
Current statistics from Alvaredo et al. A standard method for calculating wealth inequality can be obtained through econometrics. The broad field of econometrics is concerned with applying statistical techniques to economic data to produce empirical evidence for the financial construct under examination Stock and Watson, Such measures of statistical dispersion 2 are commonly used for quantifying the wealth inequality in economies.
In , Max Lorenz developed a graphical way of representing economic inequality through the use of Lorenz curve Gastwirth, The Lorenz curve graphically represents the percentage of wealth accumulated by various portions of the population ordered by the size of their wealth Gastwirth, On the x -axis, we plot the percentage of the population, and on the y -axis, we plot the percentage of wealth.
As an illustrative example, we have plotted the Lorenz curve for Ireland based on the data obtained from CSO, for This line illustrated by the blue line in Figure 1 represent the perfect distribution of wealth.
The area between the line of equality and the Lorenz curve can be used to understand the spread of inequality. An important statistical construct used to numerically describe this spread of wealth is the Gini coefficient.
The Gini coefficient is a numeric value aimed at quantifying the inequality in the distribution Gini, To calculate the Gini value for Ireland in , we use the Lorenz curve. We can calculate the Gini Coefficient as follows:.
Following this approach, we report that the Gini value for Ireland in for wealth distribution is 0. Based on Eq. Similarly, a Gini value of 0 would represent the perfect distribution of wealth in the country, i. Thus, the Gini value calculated for Ireland 0. Thus far, we have discussed the meaning and measurement of wealth inequality in the context of world economies. In the following subsection, we review wealth inequality in a crypto-economic context. Considering cryptocurrencies as financial assets is a topic of much debate in the economic and financial research domain Corbet et al.
This is primarily driven by the argument regarding the intrinsic and extrinsic values associated with the crypto assets. For this article, we focus on the extrinsic value of cryptocurrencies by using their exchange rate to USD as a proxy. The use of USD as a proxy allows us to better draw parallels between crypto economies and traditional world economies. Due to the open ledger nature of cryptocurrencies, it is easy to gain a macroeconomic view of the economy by conducting data analysis over the open ledgers.
Most cryptocurrencies maintain a publically accessible ledger of all transactions in their financial system. This allows us to use data analytics to construct a macro view of these cryptocurrencies. Gini coefficient has been suggested as a useful metric for measuring economic centralization in cryptocurrencies Kondor et al.
Both Bitcoin and Etheruem employ different data structures to maintain records of transactions. Thus the deanonymizing process varies significantly depending on the type of blockchain under analysis. UTXO specifies the value and state 3 of each Bitcoin present in the ecosystem. This list is then used to calculate the balance for the given address. The process of calculating balance is considerably simplified in Ethereum-like cryptocurrencies.
Ethereums transaction data structure contains a balance field that can store and retrieve balance for a given address. Determining the balance of all addresses is fundamental to the calculation of wealth distribution in cryptocurrencies. However, gaining a macro perspective is not sufficient to observe the wealth distribution in these cryptocurrencies. As indicated in Section 1, cryptocurrencies adhere to the crypto-anarchist ideology by employing privacy-preserving policies to maintain anonymity while retaining the freedom to trade.
This is primarily achieved through the use of cryptology in constructing and executing transactions. A macro view of the crypto economy without explicit consideration of this privacy-preserving nature would likely yield an inaccurate measure for wealth distribution as identifying wealth associated with individuals is difficult. That is, major cryptocurrencies, including Bitcoin and Ethereum, provide pseudo-anonymity to the users through cryptographically generated addresses.
Most of these cryptocurrencies also offer provisions for generating a new address for each transaction Gutoski and Stebila, This induces further complexity into the determination of wealth distribution as a single user in a cryptocurrency may have his wealth distributed over multiple addresses.
To avoid skewing the econometric analysis due to many addresses with a very small balance, Srinivasan and Lee propose using a monetary lower bound on balance. For instance, introducing a requirement of a minimum balance of USD for inclusion in Gini calculation can significantly improve accuracy by eliminating several addresses with very low or zero balances.
They justify this choice by arguing that many addresses in these cryptocurrencies are only used once for privacy reasons, and addresses with a low balance are unlikely to see future transactions for example addresses employed for one transaction only. Despite or maybe because of this tweak, it is hard to establish the accuracy of this method. Srinivasan and Lee suggest using an alternate metric to measure wealth, and other forms of distribution in cryptocurrencies.
For example, many prevalent cryptocurrencies are subjected to an honest majority assumption.
Bitcoin price growth and Indonesia's monetary system
However, the latter is valuable because it is issued by a monetary authority and is widely used in an economy. Bitcoin's network is decentralized, and the cryptocurrency is not used much in retail transactions. One can argue that Bitcoin's value is similar to that of precious metals. Both are limited in quantity and have select use cases. Precious metals like gold are used in industrial applications, while Bitcoin's underlying technology, the blockchain , has some applications across the financial services industries.
Most Volatile Cryptos
Where to Watch. The Latest. Follow Us. Where To Watch. What Will They Look Like? Oct 6, pm. The Biden administration is signaling to the crypto community that it's looking into regulating stablecoin issuers like banks, according to a Wall Street Journal report. There are no details yet on what exactly this means for the numerous non-bank entities currently churning out stablecoins, which have become a lynchpin of the crypto ecosystem, but the language does offer a hint of what kind of rules federal regulators may be cooking up. For background, stablecoins are blockchain-based cryptocurrencies that are pegged to the value of an underlying asset, in most cases a fiat currency like the U. Others, like Dai and Wrapped Bitcoin, are pegged to other cryptocurrencies or baskets of cryptocurrencies, while some, like GSX, are backed by commodities such as gold.
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For years blockchain experts have been promising that Bitcoin transactions were just the beginning of what would be possible. And the predictions were right. Blockchain is transforming how we validate transactions across all kind s of important applications from food safety to insurance processing. As bl ockchain technology adoption grew , it was natural to seek applications in Human Capital Management HCM to address the growing concern over data privacy , and fraud.
Crypto Metrics That Every Investor Must Know
Bitcoin price action has come to a critical impasse, either ready to explode to hundreds of thousands of dollars per coin , or about to take a dive from current highs. Momentum indicators have turned red for the first time in months, but bears have failed to take prices much lower. The standoff has volume dropping, and volatility dipping to the lowest levels in months for the characteristically explosive crypto asset. The analogy makes sense. I'm Tony Spilotro. Behind the pseudonym, I'm a global remote work leader with a decade of award-winning content experience and excellence.
Bitcoin Velocity Drop-Off Shows Usage as ‘Reserve Currency’
The Federal Reserve chairman Jerome Powell agreed the inflation would last longer than the government expected. She added that the cash velocity—the rate at which money turns over per year—also dropped, signaling that the market would see deflation instead of inflation in the future. Despite the bursts in cyclical inflation during the last year, velocity is hovering at low levels. If ARK Invest is correct, the next leg will be down. Wood specified that the Artificial Intelligence AI technology would penetrate every sector and industry and transform it in years. She commented that the lack of innovation might result in massive sell-offs of obsolete goods, spurring deflation. It is noteworthy that Mr. As a haven asset class against the growing inflation 5.
Still, it remains very low compared to , according to data shared by CryptoQuant. Bitcoin's velocity allows us to figure out how quickly money is circulating in the economy. It shows if BTC is trending toward being used as a store of value or as a means of payment.
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Kyle Samani. Basically, all token pitches include a line that goes something like this: "There is a fixed supply of tokens. As demand for the token increases, so must the price. This logic fails to take into account the velocity problem. Ticket fraud literally reprinting and selling a ticket multiple times for events is a huge problem.
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