In the week following the North American Financial Information Summit, I would typically use this column to discuss some of the key takeaways from the conference panels and presentations: how user firms are trying to work more closely with their suppliers; how data scientists are pushing innovation in our industry; how the name of the game is no longer raw speed but stability; or how chief data officers feel that they no longer have to sit at the “kids’ table” compared to the rest of a company’s board of directors. Yes, that’s what I’d typically do.
But this time, because I’m a huge Formula One racing fan and because we were finally (after several years of battling the F1 race calendar) able to secure NBC Sports F1 commentator Steve Matchett plus his colleague Leigh Diffey as guest speakers and presenters of this year’s Inside Market Data and Inside Reference Data Awards, I’m going to talk about F1 instead, and its parallels to the world of financial market data.
The similarities between these two industries have struck me for some time, which is why I was so keen for Matchett to present at the awards: because—as someone whose previous career was as an engineer with the Benetton F1 team (and was rear jack operator during a horrendous 1994 pit-lane fire) he could illustrate some of these similarities.
For example, just as trading firms must carefully monitor factors like value-at-risk and must deposit margin with marketplaces, prospective F1 teams must pay millions of dollars to the sport’s governing body before they are allowed to compete, as a guarantee that they have the serious funding required to see them through a season in the sport. And like in finance, to do more than just compete—which will cost at least a $20 million endeavor for even the most penny-pinching team—one needs to make continual upgrades and investment to maintain peak performance, which don’t come cheap. Gone are the “gentlemen racers” and privateer teams that would turn up for a few races then depart, as in the ’60s and ’70s.
Another change from that era is safety: Back then, crowds were separated from the track by hay bales; drivers and track marshals were routinely injured or worse. Now, large run-off areas protect spectators and are specifically designed to slow an out-of-control car. A padded “collar” around the driver’s cockpit prevents a driver being thrown from side to side like a rag doll in the event of a crash, while the HANS (Head and Neck Support) device connects to drivers’ helmets and prevents their heads being thrown forwards and backwards like rag dolls under the g-force loads of an impact. The monocoque in which the driver sits must pass rigorous crash tests, and teams are experimenting with enclosed cockpit devices designed to prevent drivers being hit by debris.
Like finance, F1 is ruled by an uncompromising governing body that imposes strict rules and seems to take pleasure in enforcing them. But when you think of an F1 driver as the pilot of a wheeled missile, you understand why rules are so important. And in trading, speed of data and execution is important, though arguably brakes and a steering wheel are more important than top speed alone.
And last but certainly not least is the sheer volume of data that the F1 teams collect and process in real-time: timing data, information from sensors on the cars, which the teams collect and send from whatever track they’re at around the world to the teams’ home bases (mostly in the UK) for analysis, the results of which are then sent back to the trackside to be incorporated into race strategy. In fact, one shot inside a pit garage at the Spanish Grand Prix showed half a dozen or so members of one team intently watching banks of data monitors for some anomaly or opportunity. I couldn’t help think of a trading floor. And I couldn’t help think that there must be much that these industries can learn from one another. So perhaps our awards helped convert some more fans to F1, and perhaps it will inspire market data professionals to think about some of their challenges in a different way.
Anthony and James look at developments pertaining to the Consolidated Audit Trail and wonder if big-tech companies could challenge traditional asset managers.Subscribe to Weekly Wrap emails
- Bloomberg’s Chat Gambit: The Feint Before a Knockout?
- Waters Wavelength Podcast Episode 96: CAT Concerns & Big Tech Takes Aim at Asset Managers
- Gardening, Uber & Culture: Takeaways from this year's WatersTechnology Innovation Summit
- Systematic Internalizer Ranks Swell Ahead of Mifid II
- EU Gets Tough on ‘Research’ Unbundling