Voice Trading Firm Cloud9 Raises $14 Million From Barclays, J.P. Morgan and NEX

Cloud9 Technologies, a Cloud Cloud The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing concepts performing run time series analysis (or trend analysis), and execute trades in real-time.Advantages of Cloud Computing in TradingAn advantage that stems from cloud computing would be that entities don’t need to construct a data center infrastructure themselves.Instead, entities can conduct trials and perform refinements, and should no solutions pan out then the cloud may be shut down while the payment terminated at the same time. This methodology of renting virtual space and time in cloud tends to be far more appealing than the costs, time, and resources required with constructing hardware and software infrastructures.These also happen to be the exact concept used in SaaS with trading related software.While executing trades via the cloud is an important capability to keep intact, most retail traders are drawn to the cloud for the research, backtesting, and analytics advantages that stem from using the cloud. In forex, traders that use Expert Advisors (EAs) and automated trading software are uploading their solutions onto a broker’s cloud account. The cloud is an ecosystem for multiple industries, sectors, and niches. Its versatility has not been peaked while in trading many retail traders are transitioning to cloud computing as a means to reduce expenditures, optimize efficiency, and maximize available resources. The cloud or cloud computing helps provides data and applications that can be accessed from nearly any location in the world so long as a stable Internet connection exists. Categorized into three cloud services, cloud computing is segmented into Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). In terms of trading, the versatility of the cloud service allows retail traders the ability to test out new trading strategies, backtest pre-existing concepts performing run time series analysis (or trend analysis), and execute trades in real-time.Advantages of Cloud Computing in TradingAn advantage that stems from cloud computing would be that entities don’t need to construct a data center infrastructure themselves.Instead, entities can conduct trials and perform refinements, and should no solutions pan out then the cloud may be shut down while the payment terminated at the same time. This methodology of renting virtual space and time in cloud tends to be far more appealing than the costs, time, and resources required with constructing hardware and software infrastructures.These also happen to be the exact concept used in SaaS with trading related software.While executing trades via the cloud is an important capability to keep intact, most retail traders are drawn to the cloud for the research, backtesting, and analytics advantages that stem from using the cloud. In forex, traders that use Expert Advisors (EAs) and automated trading software are uploading their solutions onto a broker’s cloud account. The cloud is an ecosystem for multiple industries, sectors, and niches. Its versatility has not been peaked while in trading many retail traders are transitioning to cloud computing as a means to reduce expenditures, optimize efficiency, and maximize available resources. Read this Term-based voice trading communication provider for financial firms and institutional traders, announced today the closing of a $14 million Series B fundraising with J.P. Morgan, NEX Group, and Barclays.

Cloud9 replaces traditional telephone-based trading hardware, aka turrets, the current mainstay of trader communications technology. Instead, the company’s platform delivers real-time voice communications while adhering to compliance and security standards required by financial professionals. Its service is end-to-end encrypted and supports voice chat as well as integration into 3rd-party apps.

Finance Magnates previously reported on Cloud9 after the firm announced a series A funding round from a consortium of financial institutions to help it expand its cloud-based voice trading communication solutions globally.

The service has over 5,000 institutional users in nearly 30 countries, according to a press release announcing the fundraiser.

“In addition to its investment, Barclays will work with Cloud9 on the acceleration of the Company's adoption across the industry. This follows JPMorgan's earlier decision to onboard more than 2,000 internal traders and salespeople to Cloud9 as its primary tool for voice communication between the bank and its clients globally,” it added.

The industry’s adoption of cloud technology

Cloud9 will use the funding to support innovation, accelerate the development of several products to meet demand by its customer base and expand the service offering into new markets.

Cloud9 connects counterparties across all asset classes via a cloud-based communication platform. The company believes that with increased adoption by the industry, it could save banks up to $1 billion in annual costs related to telecom equipment and services.

The rapid growth of Cloud9 since the company’s launch in 2014 has run in parallel with the industry’s adoption of cloud technology. Cloud9 exploited the opportunity to extend the platform’s benefits into areas such as workflow, compliance and advanced 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.