XRP, the world’s 7th largest cryptocurrency, has seen immense  Volatility  Volatility In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets. In finance, volatility refers to the amount of change in the rate of a financial instrument, such as commodities, currencies, stocks, over a given time period. Essentially, volatility describes the nature of an instrument’s fluctuation; a highly volatile security equates to large fluctuations in price, and a low volatile security equates to timid fluctuations in price. Volatility is an important statistical indicator used by financial traders to assist them in developing trading systems. Traders can be successful in both low and high volatile environments, but the strategies employed are often different depending upon volatility. Why Too Much Volatility is a ProblemIn the FX space, lower volatile currency pairs offer less surprises, and are suited to position traders.High volatile pairs are attractive for many day traders, due to quick and strong movements, offering the potential for higher profits, although the risk associated with such volatile pairs are many. Overall, a look at previous volatility tells us how likely price will fluctuate in the future, although it has nothing to do with direction.All a trader can gather from this is the understanding that the probability of a volatile pair to increase or decrease an X amount in a Y period of time, is more than the probability of a non-volatile pair. Another important factor is, volatility can and does change over time, and there can be periods when even highly volatile instruments show signs of flatness, with price not really making headway in either direction. Too little volatility is just as problematic for markets as too much, we uncertainty in excess can create panic and problems of liquidity. This was evident during Black Swan events or other crisis that have historically roiled currency and equity markets. Read this Term in the last 24 hours as its price jumped by nearly 10% within 1 hour during the Asian trading session on Friday 10 September.

According to the latest data posted by Coinmarketcap, XRP jumped from $1.10 to as high as $1.23 today. However, the price saw a pullback and dropped to the price level of $1.13. At the time of writing, the cryptocurrency was trading near $1.14 with a market cap of over $52 billion.

One of the major reasons behind XRP's price rise is its address activity. The total number of active addresses has increased sharply in the last few days. “XRP just enjoyed another 10% burst, minor pullback, and now another leg up at the time of this writing. A continued great leading metric for XRP is address activity. When unique addresses suddenly spike a price rise usually follows in the mid-term,” the crypto  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 platform, Santiment mentioned.

XRP Whale Activity

In addition to the rising address movement, XRP whale activity has jumped significantly in the last few days. Today, a prominent crypto wallet moved 83.2 million XRP to an unknown wallet. The total value of the transfer currently stands at around $94 million. The mentioned transfer was executed at 5:03 UTC. In a separate transaction, the XRP whale account moved over 10 million coins worth more than $13 million from crypto exchange Upbit to Bittrex on Friday 10 September at 1:42 UTC.

Yesterday, digital asset Solana (SOL), a competitor of Ethereum, crossed the market cap of $60 billion and became more valuable than XRP. Following an all-time high, SOL saw a major correction and dropped by more than 10%. On the other hand, XRP’s demand surged during the same period. The difference between the market cap of Solana and XRP now stands at around $3 billion.

The overall market cap of digital currencies has remained stable in the last 24 hours near $2.1 trillion.