TipRanks, a US-based financial analyst ranking service, has expanded its offering into the cryptocurrency space with the launch of CoinWatch, which provides investors with historical data and real-time  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 on 1,000+ different virtual coins.

CoinWatch operates as an advanced data aggregation and AI analytics platform for  Cryptocurrencies  Cryptocurrencies By using cryptography, virtual currencies, known as cryptocurrencies, are nearly counterfeit-proof digital currencies that are built on blockchain technology. Comprised of decentralized networks, blockchain technology is not overseen by a central authority.Therefore, cryptocurrencies function in a decentralized nature which theoretically makes them immune to government interference. The term, cryptocurrency derives from the origin of the encryption techniques that are employed to secure the networks which are used to authenticate blockchain technology. Cryptocurrencies can be thought of as systems that accept online payments which are denoted as “tokens.” Tokens are represented as internal ledger entries in blockchain technology while the term crypto is used to depict cryptographic methods and encryption algorithms such as public-private key pairs, various hashing functions, and an elliptical curve. Every cryptocurrency transaction that occurs is logged in a web-based ledger with blockchain technology.These then must be approved by a disparate network of individual nodes (computers that maintain a copy of the ledger). For every new block generated, the block must first be authenticated and confirmed ‘approved’ by each node, which makes forging the transactional history of cryptocurrencies nearly impossible. The World’s First CryptoBitcoin became the first blockchain-based cryptocurrency and to this day is still the most demanded cryptocurrency and the most valued. Bitcoin still contributes the majority of the overall cryptocurrency market volume, though several other cryptos have grown in popularity in recent years.Indeed, out of the wake of Bitcoin, iterations of Bitcoin became prevalent which resulted in a multitude of newly created or cloned cryptocurrencies. Contending cryptocurrencies that emerged after Bitcoin’s success is referred to as ‘altcoins’ and they refer to cryptocurrencies such as Bitcoin, Peercoin, Namecoin, Ethereum, Ripple, Stellar, and Dash. Cryptocurrencies promise a wide range of technological innovations that have yet to be structured into being. Simplified payments between two parties without the need for a middle man is one aspect while leveraging blockchain technology to minimize transaction and processing fees for banks is another. Of course, cryptocurrencies have their disadvantages too. This includes issues of tax evasion, money laundering, and other illicit online activities where anonymity is a dire ingredient in solicitous and fraudulent activities. By using cryptography, virtual currencies, known as cryptocurrencies, are nearly counterfeit-proof digital currencies that are built on blockchain technology. Comprised of decentralized networks, blockchain technology is not overseen by a central authority.Therefore, cryptocurrencies function in a decentralized nature which theoretically makes them immune to government interference. The term, cryptocurrency derives from the origin of the encryption techniques that are employed to secure the networks which are used to authenticate blockchain technology. Cryptocurrencies can be thought of as systems that accept online payments which are denoted as “tokens.” Tokens are represented as internal ledger entries in blockchain technology while the term crypto is used to depict cryptographic methods and encryption algorithms such as public-private key pairs, various hashing functions, and an elliptical curve. Every cryptocurrency transaction that occurs is logged in a web-based ledger with blockchain technology.These then must be approved by a disparate network of individual nodes (computers that maintain a copy of the ledger). For every new block generated, the block must first be authenticated and confirmed ‘approved’ by each node, which makes forging the transactional history of cryptocurrencies nearly impossible. The World’s First CryptoBitcoin became the first blockchain-based cryptocurrency and to this day is still the most demanded cryptocurrency and the most valued. Bitcoin still contributes the majority of the overall cryptocurrency market volume, though several other cryptos have grown in popularity in recent years.Indeed, out of the wake of Bitcoin, iterations of Bitcoin became prevalent which resulted in a multitude of newly created or cloned cryptocurrencies. Contending cryptocurrencies that emerged after Bitcoin’s success is referred to as ‘altcoins’ and they refer to cryptocurrencies such as Bitcoin, Peercoin, Namecoin, Ethereum, Ripple, Stellar, and Dash. Cryptocurrencies promise a wide range of technological innovations that have yet to be structured into being. Simplified payments between two parties without the need for a middle man is one aspect while leveraging blockchain technology to minimize transaction and processing fees for banks is another. Of course, cryptocurrencies have their disadvantages too. This includes issues of tax evasion, money laundering, and other illicit online activities where anonymity is a dire ingredient in solicitous and fraudulent activities. Read this Term, providing the investors community with a complete view of the market. The new tool enables users to make sense of the crypto landscape through a diverse range of comprehensive functions.

The list of key features includes a cryptocurrency exchange converter, alerts, advanced analysis, investment ideas, pricing data, heat maps, social media analytics, sentiment analytics, portfolios performance trackers, and other tools that cover almost all cryptocurrencies.

CoinWatch, which will be rolled out in early Q2, is based on a wide set of advanced natural language processing (NLP) and machine learning tools developed by TipRanks.

The toolkit is also calculating the number of mentions and analyzes millions of news articles on cryptocurrencies in social media to find surges in interest, as well as deliver historical comparisons and analytics.

TipRanks has carved out a niche as a provider of aggregated big financial data – such information is extremely important to a growing base of traders in the US and abroad.

The company has been aggressively expanding the market footprint of its Stock Analysis Tool-Kit, as part of an ongoing effort to provide new research and analysis capabilities to venues. Earlier last year, Nasdaq and Santander both assimilated the service into their respective offerings, giving TipRanks access to its largest client base to date.

Commenting on the new product, Uri Gruenbaum, CEO and Co-founder of TipRanks, said: "out of the hundreds of web-sites around cryptocurrencies, only a few actually provide meaningful and actionable data. We've applied our proven technology and expertise in natural language processing and machine learning to create proprietary datasets, aimed at helping investors make better decisions. We saw the confusion and uncertainty of investors in the cryptocurrencies world and decided that a new technological tool is required to make this world more transparent."