The Maker Foundation on Thursday proposed a new debt ceiling of $120 million DAI for its loan issuing system after the current ceiling has been hit.
The platform already issued a loan of $100 million worth DAI Stablecoin
Stablecoin
Unlike other cryptocurrencies like Bitcoin and Ethereum, stablecoins are cryptocurrencies that have been designed to keep a stable value. Placing a greater emphasis on stability over volatility can be a huge draw for some investors. Many individuals can be turned off from large swings and uncertainty presented by cryptos relative to other traditional assets.Stablecoins control for this volatility by being pegged to another cryptocurrency, fiat money, or to exchange-traded commodities, including gold, silver, or others. Advantages of StablecoinsOf note, stablecoins redeemable in currency, commodities, or fiat money are also said to be backed, whereas those tied to an algorithm are not considered to be so.There are several advantages of asset backed crypto. First, these coins are stabilized by assets that fluctuate outside of the crypto space, that is. This can help mitigate the financial risk associated with these assets.For example, Bitcoin and altcoins are highly correlated, so that cryptocurrency holders cannot escape periodic price falls. Stablecoins control for this vulnerability, allowing for the diversification of risk in a portfolio.Stablecoins also possess a mechanism for redeeming the asset backing them. This grants an additional level of confidence associated with the coin and are unlikely to drop below the value of the underlying physical asset, due to the effects such as arbitrage.For example, fiat-pegged coins are coins that are tied to a specified amount of fiat currency, usually on a one-to-one ratio (i.e.1 StablecoinX = $1). The companies that issue these currencies must have fiat reserves in the equivalent amount of the stablecoins they have issued.Crypto-pegged stablecoins constitute coins that are tied to a specified amount of another cryptocurrency, such as Bitcoin or Ethereum. Algorithmic stablecoins use supply-and-demand to automatically maintain a stable value.
Unlike other cryptocurrencies like Bitcoin and Ethereum, stablecoins are cryptocurrencies that have been designed to keep a stable value. Placing a greater emphasis on stability over volatility can be a huge draw for some investors. Many individuals can be turned off from large swings and uncertainty presented by cryptos relative to other traditional assets.Stablecoins control for this volatility by being pegged to another cryptocurrency, fiat money, or to exchange-traded commodities, including gold, silver, or others. Advantages of StablecoinsOf note, stablecoins redeemable in currency, commodities, or fiat money are also said to be backed, whereas those tied to an algorithm are not considered to be so.There are several advantages of asset backed crypto. First, these coins are stabilized by assets that fluctuate outside of the crypto space, that is. This can help mitigate the financial risk associated with these assets.For example, Bitcoin and altcoins are highly correlated, so that cryptocurrency holders cannot escape periodic price falls. Stablecoins control for this vulnerability, allowing for the diversification of risk in a portfolio.Stablecoins also possess a mechanism for redeeming the asset backing them. This grants an additional level of confidence associated with the coin and are unlikely to drop below the value of the underlying physical asset, due to the effects such as arbitrage.For example, fiat-pegged coins are coins that are tied to a specified amount of fiat currency, usually on a one-to-one ratio (i.e.1 StablecoinX = $1). The companies that issue these currencies must have fiat reserves in the equivalent amount of the stablecoins they have issued.Crypto-pegged stablecoins constitute coins that are tied to a specified amount of another cryptocurrency, such as Bitcoin or Ethereum. Algorithmic stablecoins use supply-and-demand to automatically maintain a stable value.
Read this Term on Wednesday, which is the currently set debt ceiling. It is now holding over $339 million worth Ethereum as collateral against its loans.
The foundation also proposed a decrease in the stability fee by 0.5 percent.
“The Maker Foundation Interim Risk Team has placed an Executive Vote into the voting system, which will enable the community to vote for a new Dai Stability Fee of 5% and a new Debt Ceiling of 120 million Dai,” the official announcement stated.
“The Executive Vote will continue until the number of votes surpasses the total in favor of the previous Executive Vote. This is a continuous approval vote.”
This is not the first proposal to raise the debt ceiling of DAI as last year, its foundation doubled it from the original 50 million DAI token ceiling to 100 million.
A popular project in DeFi
MakerDAO has become one of the most sought decentralized finance (DeFi) startups. Though the platform issued a hefty amount of loan backed by cryptocurrency, it does not have the data of the key demographic interested in its services due to the decentralized nature of its services, Coindesk reported.
As the issued loans do not have a fixed interest rate, the raising ceiling for loans might require a higher stability fee as well, according to Michael McDonald, creator of DAI 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 site mkr.tools.
Originally, the stability fee for DAI was set at 18 percent but now dropped down to 5.5 percent. The organization now proposed to drag it down further to 5 percent.
Meanwhile, with the popularity of DeFi projects, Nasdaq in September listed an index tracking multiple DeFi projects, including MakerDAO.
The Maker Foundation on Thursday proposed a new debt ceiling of $120 million DAI for its loan issuing system after the current ceiling has been hit.
The platform already issued a loan of $100 million worth DAI Stablecoin
Stablecoin
Unlike other cryptocurrencies like Bitcoin and Ethereum, stablecoins are cryptocurrencies that have been designed to keep a stable value. Placing a greater emphasis on stability over volatility can be a huge draw for some investors. Many individuals can be turned off from large swings and uncertainty presented by cryptos relative to other traditional assets.Stablecoins control for this volatility by being pegged to another cryptocurrency, fiat money, or to exchange-traded commodities, including gold, silver, or others. Advantages of StablecoinsOf note, stablecoins redeemable in currency, commodities, or fiat money are also said to be backed, whereas those tied to an algorithm are not considered to be so.There are several advantages of asset backed crypto. First, these coins are stabilized by assets that fluctuate outside of the crypto space, that is. This can help mitigate the financial risk associated with these assets.For example, Bitcoin and altcoins are highly correlated, so that cryptocurrency holders cannot escape periodic price falls. Stablecoins control for this vulnerability, allowing for the diversification of risk in a portfolio.Stablecoins also possess a mechanism for redeeming the asset backing them. This grants an additional level of confidence associated with the coin and are unlikely to drop below the value of the underlying physical asset, due to the effects such as arbitrage.For example, fiat-pegged coins are coins that are tied to a specified amount of fiat currency, usually on a one-to-one ratio (i.e.1 StablecoinX = $1). The companies that issue these currencies must have fiat reserves in the equivalent amount of the stablecoins they have issued.Crypto-pegged stablecoins constitute coins that are tied to a specified amount of another cryptocurrency, such as Bitcoin or Ethereum. Algorithmic stablecoins use supply-and-demand to automatically maintain a stable value.
Unlike other cryptocurrencies like Bitcoin and Ethereum, stablecoins are cryptocurrencies that have been designed to keep a stable value. Placing a greater emphasis on stability over volatility can be a huge draw for some investors. Many individuals can be turned off from large swings and uncertainty presented by cryptos relative to other traditional assets.Stablecoins control for this volatility by being pegged to another cryptocurrency, fiat money, or to exchange-traded commodities, including gold, silver, or others. Advantages of StablecoinsOf note, stablecoins redeemable in currency, commodities, or fiat money are also said to be backed, whereas those tied to an algorithm are not considered to be so.There are several advantages of asset backed crypto. First, these coins are stabilized by assets that fluctuate outside of the crypto space, that is. This can help mitigate the financial risk associated with these assets.For example, Bitcoin and altcoins are highly correlated, so that cryptocurrency holders cannot escape periodic price falls. Stablecoins control for this vulnerability, allowing for the diversification of risk in a portfolio.Stablecoins also possess a mechanism for redeeming the asset backing them. This grants an additional level of confidence associated with the coin and are unlikely to drop below the value of the underlying physical asset, due to the effects such as arbitrage.For example, fiat-pegged coins are coins that are tied to a specified amount of fiat currency, usually on a one-to-one ratio (i.e.1 StablecoinX = $1). The companies that issue these currencies must have fiat reserves in the equivalent amount of the stablecoins they have issued.Crypto-pegged stablecoins constitute coins that are tied to a specified amount of another cryptocurrency, such as Bitcoin or Ethereum. Algorithmic stablecoins use supply-and-demand to automatically maintain a stable value.
Read this Term on Wednesday, which is the currently set debt ceiling. It is now holding over $339 million worth Ethereum as collateral against its loans.
The foundation also proposed a decrease in the stability fee by 0.5 percent.
“The Maker Foundation Interim Risk Team has placed an Executive Vote into the voting system, which will enable the community to vote for a new Dai Stability Fee of 5% and a new Debt Ceiling of 120 million Dai,” the official announcement stated.
“The Executive Vote will continue until the number of votes surpasses the total in favor of the previous Executive Vote. This is a continuous approval vote.”
This is not the first proposal to raise the debt ceiling of DAI as last year, its foundation doubled it from the original 50 million DAI token ceiling to 100 million.
A popular project in DeFi
MakerDAO has become one of the most sought decentralized finance (DeFi) startups. Though the platform issued a hefty amount of loan backed by cryptocurrency, it does not have the data of the key demographic interested in its services due to the decentralized nature of its services, Coindesk reported.
As the issued loans do not have a fixed interest rate, the raising ceiling for loans might require a higher stability fee as well, according to Michael McDonald, creator of DAI 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 site mkr.tools.
Originally, the stability fee for DAI was set at 18 percent but now dropped down to 5.5 percent. The organization now proposed to drag it down further to 5 percent.
Meanwhile, with the popularity of DeFi projects, Nasdaq in September listed an index tracking multiple DeFi projects, including MakerDAO.