Max Bowie: From High Performance to High Octane
Marketing executives in the financial technology and market data industries love to use imagery of Formula One cars to promote their products. And it’s no surprise: the speed, the performance, the risk, the glitz and glamor. Both industries depend on operating at peak performance to create a winning strategy amid intense competition.
And being a huge F1 fan, I was thrilled to have NBC Sports F1 commentators Steve Matchett and Leigh Diffey as guest speakers and presenters of this year’s Inside Market Data and Inside Reference Data awards to describe the parallels to an audience of our readers.
While the speed of F1 cars is perhaps the most-overused cliché, it’s far from the only one. For example, just as trading firms must carefully monitor factors like value-at-risk and 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 (several of which are reportedly in dire financial straits)—one needs to make continual upgrades and investment to maintain peak performance, which don’t come cheap. Gone are the days of “gentlemen racers” and privateer teams that would turn up for a few races and then depart, as in the 1960s and 1970s.
Another change from that era is safety: Back then, crowds were close to the track and separated from the asphalt only by hay bales; drivers and track marshals were routinely injured or worse. Now, tracks have been upgraded at a cost of billions with large run-off areas to protect spectators and slow an out-of-control car. A padded “collar” around the driver’s cockpit prevents drivers from being thrown from side to side like rag dolls in the event of a crash, while the HANS (Head and Neck Support) device that connects to the rear of drivers’ helmets prevents their heads from being thrown forwards and backwards under the g-force loads of cornering, accelerating, decelerating, and impact. The monocoque “cocoon” in which the driver sits must pass rigorous crash tests, and teams are experimenting with enclosed cockpit devices designed to prevent drivers from being hit by debris.
And in finance, authorities have made similar efforts to protect participants and investors—though like in F1, it usually takes an horrific event (like the pit lane fire that engulfed Jos Verstappen’s Benetton F1 car at Hockenheim in 1994, where Steve Matchett was rear jack operator) to spur protective measures. Both industries are ruled by uncompromising governing bodies that impose strict rules and seem to take pleasure in enforcing them. But whether you think of an F1 driver as the pilot of a wheeled missile or derivatives as “weapons of mass destruction,” you understand why so much regulation is important. And in a trading environment, speed of data and execution is important, though arguably brakes and a steering wheel are more important than top speed alone.
In finance, authorities have made similar efforts to protect participants and investors—though like in F1, it usually takes an horrific event to spur protective measures
Collecting and Processing
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, or to warn the team and driver that a component might be near breaking point.
In fact, one shot inside a pit garage at the recent 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.
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: http://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@waterstechnology.com
More on Emerging Technologies
Waters Wavelength Podcast: Broadridge’s Joseph Lo on GPTs
Joseph Lo, head of enterprise platforms at Broadridge, joins the podcast to discuss AI tools.
Man Group CTO eyes ‘significant impact’ for genAI across the fund
Man Group’s Gary Collier discussed the potential merits of and use cases for generative AI across the business at an event in London hosted by Bloomberg.
BNY Mellon deploys Nvidia DGX SuperPOD, identifies hundreds of AI use cases
BNY Mellon says it is the first bank to deploy Nvidia’s AI datacenter infrastructure, as it joins an increasing number of Wall Street firms that are embracing AI technologies.
This Week: Linedata acquires DreamQuark, Tradeweb, Rimes, Genesis, and more
A summary of some of the latest financial technology news.
Systematic tools gain favor in fixed income
Automation is enabling systematic strategies in fixed income that were previously reserved for equities trading. The tech gap between the two may be closing, but differences remain.
Euronext microwave link aims to cut HFT advantage in Europe
Exchange plans to level playing field between prop firms and banks in cash equities with cutting edge tech.
Why recent failures are a catalyst for DLT’s success
Deutsche Bank’s Mathew Kathayanat and Jie Yi Lee argue that DLT's high-profile failures don't mean the technology is dead. Now that the hype has died down, the path is cleared for more measured decisions about DLT’s applications.
‘Very careful thought’: T+1 will introduce costs, complexities for ETF traders
When the US moves to T+1 at the end of May 2024, firms trading ETFs will need to automate their workflows as much as possible to avoid "settlement misalignment" and additional costs.
Most read
- Deutsche Börse democratizes data with Marketplace offering
- Chris Edmonds takes the reins at ICE Fixed Income and Data Services
- Sell-Side Technology Awards 2024: All the winners