Let’s face it, we are overwhelmed with data. On a daily basis we get bombarded with tweets and Facebook posts of our friends. Then there are news feeds, e-mails, youtube, blogs and so on. Because of this ever expanding amount of new data coming in, most of us have developed internal filters that help us navigate in this jungle. For instance, I rarely notice cat pictures on Facebook anymore. However in certain industries, it is your sole responsibility to dig through this data and make sense of it, otherwise you will not make any money.
One particular industry is the financial trading sector, where your only hope is to act fast on available information. We could go into a very long debate about whether trading is based on luck, skill or internal trading but let us leave that aside for a second and assume that if you get information early enough, it can give you an edge. This edge would be useless if you got the information in its current format: thousands of tweets, blogs, news articles and Facebook posts. The time it would take to dig through it would would be so long that the market would simply adjust by the time you are done. The trick is to read all of this information in a sort of a visualised summary without the need to go into the specifics.
This is what Augify from Sweden is trying to achieve. They call it data science as a service and the premise is that they will allow you to mine through twitter, forums, blogs and other sources for emotions, intentions, sentiment and emerging topics. When it comes to financial trading they will also mine for buy and sell signals as well as talks of larger investments.
As already discussed, data alone would not be enough, you need to make sense of it. They tell us that according to IBM, 2.5 quintillion bytes of data is generated daily and 95% of it is disorganized. Therefore Augify aims to use algorithms to try and deduce what all of this buzz is about. Still, understanding will not help you make actions quickly if you need to read through complicated results. So the startup is going to visualize all of the output in order to help you make the decisions faster.
This is already happening in the Twitter verse, as companies and traders try to decode the emotions of tweets. In late 2010, Johan Bollen together with Huina Mao and Xiaojung Zeng published a study where they linked the emotions derived on Twitter to stock markets and were able to prove a positive correlation between the two. As Bollen put it: “We are in the early stages of a gold rush, If you would have told anyone 10 years ago that this data would be available, they would have called it science-fiction. We know that emotions play a significant role in markets,” According to Bollen this large scale analysis of Tweets is like a “large-scale emotional thermometer for society as a whole.”
However Augify Founder Jay Solomon comments that:
“The new tape is not only Twitter – it’s Twitter plus thousands of other data sources. We need new ways to aggregate, add meaning, and visualize this data in real-time,” he says. “Data Science-as-a-Service is a crucial tool for human understanding as we transition from the Information to the Knowledge Revolution.”
It will be definitely interesting to see how this is going to work out once the startup actually launches. Moreover as technologies like this one become available, we think that they will become the tools of the trade in the industry and hence in the long-run there will not be a competitive edge as all the traders will have access to these insights. In the short run, however it might actually be one of the only ways to truly beat the stock market.
We got in touch with Augify to confirm a few details and they provided us with a little more information. In comparison to potential competitors such as DataSift SNTMNT or Recorded Future they do not analyze just the social media. They also aggregate unstructured data from e-mail, enterprise systems, research repositories and more. Additionally they also try to detect but/sell/subscribe/quit intentions, sentiment, emerging topics and memes. Basically, it is an additional tool that professionals can use to understand conversations about markets using data science and visualization.
They have been developing the software since 2011 and it is already available to hedge funds and financial services firms.
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