When it comes to deep analysis of the web, there a very few companies which really stand out with their offerings. One of those which are constantly aiming to deliver better tools to its customers is RavenPack. The firm has issued a company announcement presenting the 4th generation of its real-time news analysis service RavenPack News Analytics (RPNA).
The tool provides real-time structured data, gathered from analyzing relevant sources across the web. Publishers of the service include the Dow Jones Newswire, the Wall Street Journal, Direct Regulatory and others.
Catering mainly to quantitative & algorithmic traders, automated market makers, portfolio managers, risk managers and surveillance analysts, the 4th version of the RPNA software delivers advances in the solution’s news analytics and event detection capability
One of the top providers of real-time financial news analysis services, RavenPack, today announced the launch of RavenPack News Analytics (RPNA) 4.0, with significant advances in its news analytics and event detection capabilities, enabling quantitative analysts and data scientists to accelerate the discovery of relationships between news and financial markets.
The rather complex nature of geopolitical news, which has recently been driving markets, is also incorporated into the software with new sentiment indicators and farther reaching event novelty analytics.
The company’s CEO, Armando Gonzalez, explained in the company announcement, “This new version which gives clients the ability to model and test the reaction to macroeconomic and geopolitical news and systematically act upon these developments, in real-time if they so desire.”
He continued explaining, “Version 4.0 nearly doubles the number of market-moving events we detect, capturing more of the nuances in natural language towards a tradable instrument, hence the potential for increased alpha – or more effective surveillance and risk management.”
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Data Analytics Set to Grow Faster and Further
The new version of RPNA analyses news and opinions from around 19,000 online news and social media channels in real-time. The data which the tool provides is raw news analytics for every mention of an entity and a variety of indicators which summarize sentiment and give a heat indicator to media attention at an entity level.
Big data analytics has become an integral part of decision-making processes at hedge funds such as Ray Dalio’s Bridgewater.
Bridgewater’s Co-CEO, Greg Jensen, explained in a conference call last year, “From Twitter and Facebook (and so on) we can capture every time somebody is saying they bought a new car. We could add those up and can compare that to the stats and be really on the pulse of what’s going on with something like auto sales or, similarly, with home sales.”
For the time being, the widely available sentiment analysis tools and macroeconomic data mining efforts are far from the sophisticated “weapons” which big hedge funds are using, however, there is scope for much more developments on this front.
Last year, the McKinsey Global Institute published a study which estimated that in order to enable the analysis of the various sorts of big data, the United States will need 140,000 to 190,000 more workers with “deep analytical” expertise.
Data relating to the physical foreign exchange markets is usually a great indicator of when a sovereign debt crisis is around the corner – just as the lines of people exchanging their local currency and looking to buy safe haven alternatives. Other infamously sophisticated methodologies are used to predict the peaks and bottoms of economic cycles.
The big difference is that big data gathered through social media and other online channels is forward-looking, in contrast to macroeconomic data gathered by the government’s statisticians.