Geosensory Data: The Next Big Innovation in Finance
Big Data in Banking [Source: http://www.youtube.com/watch?v=6TgW5LYOcpo]
As an organization that enables enterprises around the world to realize their goals, we're never at a loss to explain the power of Big Data. Whether it's in retail, healthcare, or even banking, the more a company knows about its customers, the more it's able to make lasting connections with them.
I'm reminded about just how powerful Big Data has become by reading a profile about a handful of MIT graduates who were intent on creating a hedge fund. Now for those of you who don't follow the world of alternative asset management, hedge funds haven't exactly had the easiest last few years in the wake of the global economic crisis. It's gotten more challenging for hedge fund managers to allocate capital in such a way that it creates a "hedge" against more traditional investments.
So when MIT classmates Michael Chang, Sean Chang, and Zeid Barakat decided to found a firm called Flyberry Capital, they had a certain level of difficulty in attracting seed capital to get their hedge fund off the ground. All that changed when discerning investors began to see how Flyberry was distinguishing itself in the alternative asset management space: They dedicated themselves to parsing enormous amounts of data. The term used to describe some of what the firm studies is "geo-sensory information;" that is, huge buckets of data that relate to weather patterns, earthquakes, forecasts, and the like.
The battle for investment capital is an intense one, to be sure. Every hedge fund markets itself as distinct from the crowd because of its methodology and mission. But the one thing they all have in common is a natural reliance on good, actionable data. I found the story of how Flyberry distinguished itself to be an inspirational one. A typhoon that hits an area of the world that produces lots of a certain raw material is going to matter to investors. But so does negative sentiment across social media about how poorly companies in that weather pattern were prepared for the typhoon. Then there's data that is the opposite of the once-in-a-century weather event. Earnings calls, for instance, are potential gold mines if a company has acted in a certain way time and again against particular earnings targets. So a firm that utilizes Big Data can essentially get into the practice of predicting future actions. Modeling is what can set any company apart from its peers.
The story of this interesting hedge fund also calls attention to diversity of data. You hear a lot these days about a company taking a huge data set and parsing it many different ways. But the next phase of Big Data is rewarding those who take many different sources of data and compare them to detect patterns.
For some years now, the most formidable investment firms have used latency as an advantage. That's a fancy way of saying how quickly they could make trades taking advantage of arbitrage opportunities in the market. When a split second can mean the difference of making $5 million dollars, the firms with the most powerful trading capabilities are the ones that win out.
Investors have pushed those latencies to the limits. Some have even set up their computer servers within a mile or two of the big stock exchanges so that they can save additional microseconds. Where they've done everything technologically feasible with the element of time, investors are still only at the beginnings of what they can do with the element of information. Especially when you consider the fact that a good chunk of what they analyze consists of sentiments that are expressed a number of ways across social media.
Whether it is relatively liquid investments such as currency futures, index futures, or commodities, today's financiers want to get the stories behind what makes people buy and sell, and what makes companies profitable. By combining data sets across the board and devising ways to analyze that information, the savviest investors are creating an entirely new data paradigm.