Ethereum Reaches $500 Billion Market Cap
- ETH touched an all-time high of approximately $4,350 on Wednesday.

Ethereum, the world’s second-most valuable digital currency, spiked nearly 10% in the last 24 hours and reached an all-time high of approximately $4,350.
According to the latest data published by Coinmarketcap, Ethereum now has a market cap of more than $500 billion. ETH becomes only the second cryptocurrency in the world to reach a market value of $500 billion.
Ethereum is now more valuable than the world’s leading investment bank JPMorgan. The total market cap of JPMorgan Chase currently stands at around $480 billion. ETH has been on the rise since the start of 2021. The cryptocurrency crossed the market cap of the Bank of America and PayPal earlier this year.
ETH whale activity has increased during the last few weeks amid a surge in its price. Yesterday, Finance Magnates reported about the movement of 46,793 Ethereum from a digital wallet to cryptocurrency exchange Binance.
“Ethereum top stakeholders have been historically active over the past week, with one 4-hour window on 5 May seeing over 6,300 $100k+ ETH transactions. This explosion in activity beginning on 3 May had much to do with the inevitable rise to $4,200,” on-chain Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term firm Santiment mentioned on Twitter.
The latest price surge in ETH has made Vitalik Buterin, Co-Founder of Ethereum, one of the youngest crypto billionaires after his public Ethereum address crossed 333,520 ETH, which is approximately $1.4 billion in value.
Ethereum Whales and Institutional Inflows
According to the latest data published by Whale Alert, a Blockchain Blockchain Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Read this Term tracking and analytics platform, ETH’s record price has accelerated unknown Ethereum whale transactions. A crypto whale transferred 137,832 ETH to an unknown wallet on 11 May at 19:38 UTC. The total value of the transaction stands at around $560 million. The latest weekly cryptocurrency fund inflows report from CoinShares highlighted a significant jump in Ethereum-related institutional inflows. ETH investment products saw inflows of $60 million last week, which is up by 100% compared to the last week of April 2021.
The market dominance of ETH currently stands at around 19.6%, which is its highest level on record.
Ethereum, the world’s second-most valuable digital currency, spiked nearly 10% in the last 24 hours and reached an all-time high of approximately $4,350.
According to the latest data published by Coinmarketcap, Ethereum now has a market cap of more than $500 billion. ETH becomes only the second cryptocurrency in the world to reach a market value of $500 billion.
Ethereum is now more valuable than the world’s leading investment bank JPMorgan. The total market cap of JPMorgan Chase currently stands at around $480 billion. ETH has been on the rise since the start of 2021. The cryptocurrency crossed the market cap of the Bank of America and PayPal earlier this year.
ETH whale activity has increased during the last few weeks amid a surge in its price. Yesterday, Finance Magnates reported about the movement of 46,793 Ethereum from a digital wallet to cryptocurrency exchange Binance.
“Ethereum top stakeholders have been historically active over the past week, with one 4-hour window on 5 May seeing over 6,300 $100k+ ETH transactions. This explosion in activity beginning on 3 May had much to do with the inevitable rise to $4,200,” on-chain Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term firm Santiment mentioned on Twitter.
The latest price surge in ETH has made Vitalik Buterin, Co-Founder of Ethereum, one of the youngest crypto billionaires after his public Ethereum address crossed 333,520 ETH, which is approximately $1.4 billion in value.
Ethereum Whales and Institutional Inflows
According to the latest data published by Whale Alert, a Blockchain Blockchain Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Read this Term tracking and analytics platform, ETH’s record price has accelerated unknown Ethereum whale transactions. A crypto whale transferred 137,832 ETH to an unknown wallet on 11 May at 19:38 UTC. The total value of the transaction stands at around $560 million. The latest weekly cryptocurrency fund inflows report from CoinShares highlighted a significant jump in Ethereum-related institutional inflows. ETH investment products saw inflows of $60 million last week, which is up by 100% compared to the last week of April 2021.
The market dominance of ETH currently stands at around 19.6%, which is its highest level on record.