Sometime around 2009 or 2010 when my wife and I were contemplating moving up in the world from our pre-war one bedroom apartment with sagging floors and leaky ceilings across the East River from Manhattan, I looked at a map of Astoria, New York, and noticed a roughly triangular area bordered by the N and Q subway lines on the west, the R and M subway lines on the south and east, and Broadway in the north. I dubbed it the “Golden Triangle,” and predicted that property falling within those boundaries would soon go through the roof. It did, but alas, even then the prices were already too high for me to get in on that boom.
But there’s another Golden Triangle, where two of the corners lie across Manhattan’s other river, The Hudson, in Secaucus and Carteret, NJ. This triangle covers the main cash US Treasury platforms hosted in NJ and CME Group’s datacenter in Aurora, Illinois, where the CyrusOne facility it uses to host its treasury futures trading platform is located. Traders wanting to trade cash Treasuries against their derivatives need to be present in all three sites, and have high-performance connectivity between them. The vendors who provide this connectivity are constantly striving to deliver their clients an edge by reducing latency across their routes. In this case, microwave connectivity provider McKay Brothers has lowered the latency between the two New Jersey-based datacenters.
For a long time, latency in fixed income trading has been limited to firms’ execution requirements—i.e., eliminating undue delays between placing a trade and it being executed. However, firms are now becoming more concerned about the performance of fixed income data from start to finish, as evidenced by the customer demand that has driven ticker plant vendor Redline Trading Solutions to build low-latency support for Nasdaq’s eSpeed market late last year, and Icap’s Brokertec platform in recent weeks.
But not all fixed income instruments are as liquid as US Treasuries, and often rely on evaluated prices as a proxy for actual trades. For example, when ICE Data Services rolled out Interactive Data’s BestEx data service in Europe, the vendor found there wasn’t sufficient data to follow the same methods used in the US, and instead created a formula based on the correlation of differences between trades and its Continuous Evaluated Pricing service to create a sufficiently reliable proxy to triangulate the market.
Another famous triangle is that formed by the intersection of Broadway and Seventh Avenue in Manhattan at Times Square, overlooked by Thomson Reuters’ iconic headquarters. However, the vendor has announced that with the opening of a new Toronto Technology Center in downtown Toronto, the key management roles of chief executive Jim Smith and chief financial officer Stephane Bello will move to Toronto next year, shifting the headquarters to Canada, original home of Thomson Corp., prior to its merger with Reuters. Officials say the new center will create 400 tech jobs over the next two years, ultimately creating 1,500 new jobs in addition to the vendor’s existing 1,200 staff in the city, including other management roles that will be relocated to Toronto.
You may well wonder what impact this will have on Thomson Reuters’ stock price. And if that’s how you think, then you could do worse than check out Qineqt, a new company providing highly granular correlation between companies and industry sectors, by looking for “catalyst events”—such as moving one’s corporate headquarters, perhaps. For example, the vendor analyzes each individual property held by a real estate investment trust, bringing more transparency to these assets, much as the credit crunch brought loan-level data into focus as important data, rather than looking just at a bundle of loans that might contain some of dubious quality.
Any fool like me can draw lines on a map and call it a Golden Triangle. But only granular data can determine which individual property will be the next luxury lofts, and which is a tumbledown tenement.
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