Max Bowie: In With the New (But Not Out With the Old)

I’ve been pretty much stumped this year whenever anyone asks me the simple question, “What’s new?” It’s not that there are no new products out there, or even that firms aren’t willing to spend on them. But it’s been much harder than in years past to pin down what’s actually new, and what’s merely an evolution of what has gone before.

One example, as explained by my colleague Jake Thomases on page 16, is the growing use of microwave technologies to transmit market data at lower latency than fiber-optic networks across long distances, and the novel technologies being implemented by providers to ensure their signal is not disrupted by factors such as wind and rain.

But microwaves are arguably just the latest evolution in the race for low latency, where previous evolutions were direct, dedicated fiber-optic routes, and the move by marketplaces and their participants into co-location or independent proximity hosting datacenters. Even these co-lo centers are merely the automated evolution of the old exchange floors, with servers/traders clustered around a matching engine/specialist, all looking to route a trade/get the specialist’s attention fastest.

There is certainly some great innovation underway in the markets right now among the vendors that serve them. For example, New York-based startup Estimize creates crowd-sourced consensus earnings estimates from individuals and analysts, as opposed to from Wall Street firms, which its founder says produces a more accurate estimate—much in the same way that Credit Market Analysis (now owned by S&P Capital IQ) changed the process of evaluating bond prices by polling buy-side clients on what price they expected to pay or receive for assets, rather than aggregating dealer quotes.

Old Dog, New Tricks
Despite its novel approach, Estimize is still producing earnings estimates—a long-established metric—whereas others are using traditional inputs to come up with new types of analytics, such as Calgary, Alberta-based analytics startup Level 3 Data, which analyzes real-time tick data to consolidate volume at each side of the spread, providing a signal of supply and demand, as well as price exhaustion, to help quantitative traders and hedge funds improve returns and minimize risk.

A key challenge for next-generation content providers is to generate data where none already exists.

Why do we need real change to help improve these factors? Consider this: 90 percent of corporate bonds don’t trade every day. And if you’re still relying on last trade prices to value your bonds, you’re way out of date, at a great deal of risk, and not complying with rules governing how you should value securities. Traditional datasets and analytics simply haven’t been able to provide transparency into the real value of these assets.

Hence, a key challenge is to generate data where none already exists. For example, just as energy and commodities data provider Genscape began taking ariel photographs of oil and gas storage facilities and heat-sensitive video of power plants to estimate supply—which traders could use as an input to price energy derivatives based on supply and demand—startup Clipper Data (set up by former Genscape staff) is consolidating publicly available data sources and transmissions to provide information on when a freighter will arrive in a port, and the type and size of its cargo. And it’s not only startups that are coming up with ideas for new content: Thomson Reuters now makes similar shipping information available on the Interactive Map feature of its Eikon desktop.

Of course, as datasets become more sophisticated, firms will need new ways to manage and administer their data. Hence, another area of innovation is being explored by New York-based startup Simplified Financial Information, whose Market Data Analytics tool will monitor data consumption and usage by measuring what content travels where on a firm’s network, rather than relying on reconciling manually-updated inventory lists and entitlement files, to ensure compliance with suppliers’ data contracts.

As the term big data becomes even more ubiquitous than it already is, the ability to integrate and manage these new types of datasets—and the technologies and tools to derive value and signals from them—will become increasingly important for trading and risk management.