RavenPack Extends Big Data Capabilities to Traditional Investors
- Normal investors will now be able to utilize the same big data tools as hedge funds and large asset managers.
RavenPack, has unveiled its new offering for investors, focusing on trading signals derived from Big Data Big Data Big data refers to the collection of data that is too complex and too large for processing by standard database tools. There is no specific quantity of data, which is set as a minimum level to be considered Big data. Image the data collected on global credit card transactions. Many governments used Big data analysis to study the recent pandemic spread. The term Big data was first introduced in 1980 by Charles Tilly.The term Big data was primarily used in computer science, statistics, and econome Big data refers to the collection of data that is too complex and too large for processing by standard database tools. There is no specific quantity of data, which is set as a minimum level to be considered Big data. Image the data collected on global credit card transactions. Many governments used Big data analysis to study the recent pandemic spread. The term Big data was first introduced in 1980 by Charles Tilly.The term Big data was primarily used in computer science, statistics, and econome Read this Term. The new service harnesses big data technology from a wide spectrum of mediums, including web, news, social media, regulatory filings, and others.
The new offering caters to investors of all calibers with such capabilities previously only utilized by quantitative hedge fund and asset managers. With RavenPack’s latest launch however, traditional investors will be able to utilize the same tools, garnering the same sort of access to big data as the industry’s leaders.
Armando Gonzalez, CEO of RavenPack, commented: “The ability to build custom signals on the RavenPack platform is a game-changer for discretionary and fundamental investors who value logic and facts. Until now, our core tools and techniques have only been available to the largest quantitative hedge funds and investment banks. Creating signals from big data sources is now simple and intuitive - and accessible for most financial professionals.”
The launch is important as it relies on RavenPack’s big data technology without the need to rely on data scientists or others. The ability to cultivate and process thousands of data sets in real time was previously an attribute available to mainly hedge funds. By utilizing RavenPack’s new offering, the process is greatly simplified and streamlined, quickly disseminating social media and news outlets.
Armando Gonzalez
Investor reliance on big data is one of the most key trends in 2017 as financial venues, asset managers, and private investors alike are all looking to gain access to sentiment indicators and data set processing. Today’s launch helps cater to this demand, aiming to help interpret business and macroeconomic trends as well as improving trading performance.
In particular, RavenPack’s new big data offering will allow discretionary and fundamental investors a range of new utilities. This includes the construction of trading signals via a simplified user interface while also allowing investors to easily utilize plug big data into more traditional strategies.
Additionally, the new offering features capabilities that help identify market trends and patterns visually by charting sentiment indicators improved pricing data. Users can also download signals into traditional tools used by analysts and traders including Excel, R, Python, and Matlab.
RavenPack, has unveiled its new offering for investors, focusing on trading signals derived from Big Data Big Data Big data refers to the collection of data that is too complex and too large for processing by standard database tools. There is no specific quantity of data, which is set as a minimum level to be considered Big data. Image the data collected on global credit card transactions. Many governments used Big data analysis to study the recent pandemic spread. The term Big data was first introduced in 1980 by Charles Tilly.The term Big data was primarily used in computer science, statistics, and econome Big data refers to the collection of data that is too complex and too large for processing by standard database tools. There is no specific quantity of data, which is set as a minimum level to be considered Big data. Image the data collected on global credit card transactions. Many governments used Big data analysis to study the recent pandemic spread. The term Big data was first introduced in 1980 by Charles Tilly.The term Big data was primarily used in computer science, statistics, and econome Read this Term. The new service harnesses big data technology from a wide spectrum of mediums, including web, news, social media, regulatory filings, and others.
The new offering caters to investors of all calibers with such capabilities previously only utilized by quantitative hedge fund and asset managers. With RavenPack’s latest launch however, traditional investors will be able to utilize the same tools, garnering the same sort of access to big data as the industry’s leaders.
Armando Gonzalez, CEO of RavenPack, commented: “The ability to build custom signals on the RavenPack platform is a game-changer for discretionary and fundamental investors who value logic and facts. Until now, our core tools and techniques have only been available to the largest quantitative hedge funds and investment banks. Creating signals from big data sources is now simple and intuitive - and accessible for most financial professionals.”
The launch is important as it relies on RavenPack’s big data technology without the need to rely on data scientists or others. The ability to cultivate and process thousands of data sets in real time was previously an attribute available to mainly hedge funds. By utilizing RavenPack’s new offering, the process is greatly simplified and streamlined, quickly disseminating social media and news outlets.
Armando Gonzalez
Investor reliance on big data is one of the most key trends in 2017 as financial venues, asset managers, and private investors alike are all looking to gain access to sentiment indicators and data set processing. Today’s launch helps cater to this demand, aiming to help interpret business and macroeconomic trends as well as improving trading performance.
In particular, RavenPack’s new big data offering will allow discretionary and fundamental investors a range of new utilities. This includes the construction of trading signals via a simplified user interface while also allowing investors to easily utilize plug big data into more traditional strategies.
Additionally, the new offering features capabilities that help identify market trends and patterns visually by charting sentiment indicators improved pricing data. Users can also download signals into traditional tools used by analysts and traders including Excel, R, Python, and Matlab.