Opening Cross: The New Wave of New Wave of New Data

Even the sources of these items has changed. In the mere decade since Twitter was founded in March 2006, it has gone from being scoffed at by decision-makers in financial markets to becoming a key source of company disclosures, breaking news, and opinions that either move markets or are a leading indicator of price movements.

And investors are looking for new types of datasets, such as ESG (Environmental, social and governance) factor-based indexes and “green” investments. Again, these investments were once-scoffed at by those raking in returns from so-called “sin index” investments. But as investors seek more socially responsible investments, asset managers, exchange-traded fund sponsors and index providers have found there’s a lot of green to be made from “green” investments—with the added benefit that ESG-conscious companies are less likely to be hit with fines for polluting or bad corporate governance/illicit activity, with the reputational damage that goes along with it.

Of course, one of the biggest changes to affect data over the past 31 years is the speed at which data is disseminated. From being a factor that went largely unmeasured during the days of Big Board displays and green screens to being something where firms fight over fractions of seconds today—and yes, firms literally fight over it, demanding shorter cables than their rivals within datacenters—the latency of data has become a major determining factor in its usefulness, versus what constitutes stale data.

So I’m very pleased to announce that the guest speakers at this year’s Inside Market Data and Inside Reference Data Awards know a thing or two about speed: Handing out awards on the evening of May 18, following our North American Financial Information Summit in New York will be two members of NBC Sports Network’s Formula One commentary team—Steve Matchett and Leigh Diffey. If you’re already an F1 fan, you’ll probably already know Matchett either as a commentator or as a former engineer with the Benetton F1 team during its heyday while Michael Schumacher drove for the team, while Diffey has commentated sports as diverse as superbikes, Indy cars, and rowing. And if you’re an F1 fan who works in market data, then you’re probably as in awe as I am of the speed and precision with which teams capture data from cars during a race, transmit it from wherever they are in the world to their team base (for most of the teams, in the UK), where they analyze the data in real time and send it back to the racetrack to make strategic race decisions. 

In the capital markets, trading algorithms perform similar tasks for all manner of purposes—to execute trades, for monitoring and optimizing execution cost and quality, or for deciding what marketplace to route an order to, and even over which network and port. These compute-intensive F1 analytics do the equivalent of all this, and also do it in the context of the other 21 cars on track—each potentially on their own strategy, which could interfere with anyone else’s. In my opinion, financial markets and F1 are two high-performance industries that could learn from each other about the art of racecraft—whether you’re racing for a trade or for a checkered flag—and I hope you’ll take the opportunity to join us to hear Matchett and Diffey share their stories, and to cheer the winners.