Ethereum Whales Transfer 100,000 ETH in 24 Hours
- Several large Ethereum transactions are being reported across different crypto exchanges.

Ethereum, the world’s second-largest cryptocurrency, reached an all-time high of $1,470 today after a massive rally. ETH whales are transferring a significant amount to digital exchanges and unknown wallets. A total of 5 ETH transactions involving nearly 100,000 Ethereum were highlighted in the last 24 hours.
According to the 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 tracker and 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 company, unknown Ethereum whales transferred more than 46,000 ETH in two separate transactions from crypto exchange Binance to unknown wallets.
The tracker showed that 9,000 Ethereum were transferred from Crypto.com to an unidentified wallet. Another transfer involving 25,450 ETH was recorded when an unidentified user transferred the cryptocurrency worth nearly $35 million to another unknown crypto wallet. The movement of 19,000 ETH was also reported to an unidentified wallet.
The total value of the mentioned transactions stands at around $140 million. Over the weekend, a significant transaction was recorded when 57,625 Ethereum were transferred from Bitfinex to an unknown wallet. The price of Ethereum jumped nearly 100% since the start of 2021. The recent transfers from major crypto exchanges indicate that ETH whales are planning to accumulate the cryptocurrency to create a potential supply shortage of the world’s second-largest crypto asset.
Ethereum’s Outflow
The outflow of Ethereum from major digital exchanges has been evident for the last few days as a massive amount of ETH has already left cryptocurrency exchanges. According to a crypto analytic company, Glassnode, ETH accumulation is on the rise as the Ethereum balance on prominent exchanges fell 4.5% since last week. Apart from Ethereum, other crypto-assets like TRX and LINK were involved in prominent transactions. One of the key reasons behind the recent moves is a significant rise in the price of Altcoins. Furthermore, Ethereum, Polkadot, Cardano, Stellar, Litecoin, Chainlink and Bitcoin Cash, all are up in double-digits since last week, compared to a 10% drop in BTC price. Crypto whales are accumulating digital assets to diminish supply.
Ethereum, the world’s second-largest cryptocurrency, reached an all-time high of $1,470 today after a massive rally. ETH whales are transferring a significant amount to digital exchanges and unknown wallets. A total of 5 ETH transactions involving nearly 100,000 Ethereum were highlighted in the last 24 hours.
According to the 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 tracker and 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 company, unknown Ethereum whales transferred more than 46,000 ETH in two separate transactions from crypto exchange Binance to unknown wallets.
The tracker showed that 9,000 Ethereum were transferred from Crypto.com to an unidentified wallet. Another transfer involving 25,450 ETH was recorded when an unidentified user transferred the cryptocurrency worth nearly $35 million to another unknown crypto wallet. The movement of 19,000 ETH was also reported to an unidentified wallet.
The total value of the mentioned transactions stands at around $140 million. Over the weekend, a significant transaction was recorded when 57,625 Ethereum were transferred from Bitfinex to an unknown wallet. The price of Ethereum jumped nearly 100% since the start of 2021. The recent transfers from major crypto exchanges indicate that ETH whales are planning to accumulate the cryptocurrency to create a potential supply shortage of the world’s second-largest crypto asset.
Ethereum’s Outflow
The outflow of Ethereum from major digital exchanges has been evident for the last few days as a massive amount of ETH has already left cryptocurrency exchanges. According to a crypto analytic company, Glassnode, ETH accumulation is on the rise as the Ethereum balance on prominent exchanges fell 4.5% since last week. Apart from Ethereum, other crypto-assets like TRX and LINK were involved in prominent transactions. One of the key reasons behind the recent moves is a significant rise in the price of Altcoins. Furthermore, Ethereum, Polkadot, Cardano, Stellar, Litecoin, Chainlink and Bitcoin Cash, all are up in double-digits since last week, compared to a 10% drop in BTC price. Crypto whales are accumulating digital assets to diminish supply.