Data Visualization's New Shine

As a single transaction travels in nanoseconds from an electronic trading firm to the market, it makes its way through an internal network, expands to a wider network between sites and eventually to other complex data centers and to the exchange's own infrastructure. Each one of these moving parts provides feedback to the user and leaves a trail of data along the way.

Considering that billions of messages are sent at any single second during the day -- U.S. securities message rates have been growing 30% every six months over the last decade, according to advisory firm TABB Group -- gathering all these bits of data and distilling them is a herculean task for any trading firm.

Wall Street firms that are hunting for alpha, while keeping the regulators happy, are using new data visualization technologies to see which transactions traders should focus on, while their back offices are using visuals to help them sift through millions of data points to make sure each trade is compliant with regulators' demands.

"It's about identifying what's useful and not. And that will change all the time as people are doing different things at any one point in time," Chad Cook, CTO of Lime Brokerage, said during a recent Wall Street & Technology webcast. "It's difficult for humans to process all this information in a way that is effective."

Today, financial executives are accustomed to glancing at reams of data in lists, tables or grids, and gleaning within a few seconds whether there are any anomalies or what is the most valuable information. But if you talk to traders, they will tell you that if you have a list with more than 25 or 26 items on it, you're merely managing things off the list rather than seeing which are valuable, reports Jarlath Forde, creative director at Sapient Global Markets. "Where you start to get value is when you can communicate an insight visually and use a tool to help them prioritize what they're doing," he notes.

Traders can use heat maps to give added meaning to unstructured data such as tweets, helping them decipher instantly, for example, whether an unusually high number of tweets is linked to positive or negative sentiment around a certain stock.

Drilling into a heat map that shows you tweets about Microsoft could show you what these tweets have in common at any point in time, such as the mention of Windows 8, while drilling in further might show you tweets with both that word as well as Surface Pro, Microsoft's new tablet. "So it might tell you the reason the world is interested in Microsoft," says David Polen, head of business development at Fidessa.

Fidessa is using data visualization technology to enable brokers to gain more value from their conversations with clients. Questions the buy side is asking include, "Where should I be trading my stock? Did my broker buy stock in the right venues? How well is my broker representing fragmentation in terms of purchasing stock?" Polen says. Clients want to know when a stock traded and whether it traded on an exchange or in a dark pool, he explains.

"Predictive analytics isn't worth that much. It can show you a lot. But the best way is to make analytics that are simplified," he says, pointing to Fidessa's own Fragmentation Index, which provides a global heat map allowing users to measure, compare and track the fragmentation of liquidity wherever they happen to be in the world.

Data visualization helps people filter down their investment options rather than just creating list-based screeners, adds Sapient's Forde. "One of the things we see is most systems today are highly transactional. They're about the entry of a trade, not about supporting a trader in what to trade in and when to trade it," he says.

Brokers are now using data visualization to help them to determine when to call the buy side, Polen notes. "You don't want to call [clients] every four minutes, but you do want to call them when you can provide good service," he adds. "We analyze when is the moment you should reach out to them. We also invented new analytics predicting the success of the conversation," he explains.

Forde agrees that the sell side wants to know while a client is on the phone how much of an incentive to give him. "I could have looked up how profitable a client is and it would have taken 10 minutes. Now I have him on the phone, and I want to know now. Data visualization is a great tool to do that. I want a visual to see how much flow has been coming from him," he says. "It's additional layering, which traditionally had information in different systems, not connected together."

Traditional tools do not give you fast and easy data discovery or foster the discovery of new trading opportunities, notes Oleg Komissarov, senior VP of enterprise solutions at DataArt, a custom software development firm that recently partnered with Aqumin, a maker of 3-D real-time visual interpretation software.

Standard tables representing two-dimensional data visualization tools such as grids, charts or diagrams and some charts are still ubiquitous. But to understand what numbers mean, traders or investors traditionally dig into every record and look at what each number conveys.

In addition, advances in the open source community with big data tools and systems, such as Hadoop, have brought about a new age in data visualization tools that allow faster and easier data discovery, Komissarov continues. As such, vendors have introduced more dimension than before, with color, shape and even volume indications. The latest tools combine visualization with 3-D shapes, enabling users to make more intuitive and effective decisions in a much shorter period of time.

Aqumin, for example, has created software called AlphaVision, which enables firms to visualize data on a constantly evolving, interactive landscape -- think charts that look like skyscrapers on a landscape that gradually get taller or shorter as data changes in real time. It allows wealth managers, portfolio and risk managers, and even regulators to move things around on the fly and see patterns in disparate sources of public and proprietary market data, according to the company's CEO, Michael J. Zeitlin.

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