The low-latency data race is often compared to Formula One racing because of its speed and its use of cutting-edge technologies. Yet in F1 qualifying, being first on track is typically the domain of slower teams seeking empty track to set a time before the big players, whereas in finance, being first is everything.
This desire to always be a step ahead of the competition recently landed Thomson Reuters in hot water, when it was revealed that the vendor offered an early look at the University of Michigan’s consumer sentiment survey to high-frequency traders willing to pay a premium. Under a deal with the university, Thomson Reuters can release the results to clients five minutes before the university makes the results available online. However, the vendor also gave an extra two-second head start to HFTs over the rest of its client base.
The practice attracted the attention of the New York Attorney General, who last week announced that the vendor will halt the two-second early release—at least while the AG investigates. In its defense, the vendor says it is “open and transparent about how it releases proprietary data,” and “strongly believes that news and information companies can legally distribute non-governmental data and exclusive news through services provided to fee-paying subscribers” to support better informed trading decisions.
“Financial markets have always been about the fastest access to exclusive and differentiated content. News and information companies have always sought to differentiate themselves by bringing their clients such exclusive news and information, and this is why financial market professionals routinely subscribe to multiple information services,” says a Thomson Reuters spokesperson.
I’m no fan of more advantages for those with the existing advantage of being able to pay for it (remember flash orders?)—especially when HFTs with a two-second advantage could trade away every opportunity before anyone else even sees the data. But isn’t this like publishing breaking news on your premium newswire earlier than posting it to everyone on your website (unlike when the SEC penalized the New York Stock Exchange for unintentionally releasing data via direct feeds before the consolidated US equities feed)?
Thomson Reuters pays a no-doubt hefty fee to the University of Michigan to distribute the data how and when it wants. And it did surprise me that the AG focused on how the two-second early notice disadvantages other traders, rather than on the five-minute advantage over retail investors. Thomson Reuters has a similar agreement to distribute Markit’s European PMI (Purchasing Managers’ Index) data to its desktop and datafeed clients two minutes before Markit’s own general release, which wasn’t mentioned by the AG—though in this case, Thomson Reuters doesn’t have different tiers of release within its own client base.
No doubt the AG’s concern is the volatility that HFTs can bring to the market—after all, the Flash Crash wasn’t caused by a retiree sitting at home in his pajamas placing his monthly online trade—so I give the AG credit for wanting to eliminate any possible market manipulation.
It was market manipulation by banks conspiring to fix lending rates that led to a revamp of the LIBOR benchmark rate, which will next year transfer from the British Bankers Association to NYSE Euronext Rate Services, a company set up specifically to run the benchmark.
One of NERA’s goals is to restore “credibility, trust and integrity in LIBOR as a key global benchmark,” with credibility an important factor across the spectrum of financial data, from ratings to social media sentiment, which is establishing itself as a leading indicator, but is still open to manipulation (remember the Hash Crash?)—something that startup social media sentiment provider MarketProphit aims to solve by rating the success of key groups and individuals.
If these and others can restore credibility to the markets and data sources after the beating of the past few years, now that really would be incredible.
Jesse Lund talks about real uses for DLT in the capital markets, lessons learned while rolling out IBM's blockchain platform, and what’s ahead for 2018, and into 2019.Subscribe to Weekly Wrap emails