An Algorithm in Every Household


It isn't often that people outside the financial industry and the media covering it are familiar with or understand the operations and technology topics that WatersTechnology and Inside Reference Data covers. The most common reaction when telling people what we do is, "So, do you have any good stock tips for me?"

So I never expected to pick up a thought-provoking idea at a family holiday dinner this week. It might be a little afield from data, but it's definitely squarely in the financial operations technology space. And the idea is: if the big investment banks and securities market players are deploying microsecond- or even nanosecond-fast algorithms to conduct trading based on pre-set strategies, what's to stop that from eventually being possible for the retail investor? And if that happens, what does that do to the markets when institutional algorithms have to compete with thousands, hundreds of thousands or maybe even millions of retail investors' algorithms being thrown into the trading mix?

This idea doesn't seem that far-fetched either, when the world has seen computing power get distilled from room-size mainframes to desktop PCs and on down to smartphones—thus making the advances universally available, not just to industry. So assuming there may already be an enterprising Gates, Jobs or Zuckerberg already working on something like this in their garage, another question is once that comes to pass, and the markets are inevitably reshaped by it, what may regulators have to say about it? Would participation of large numbers of latter-day, accelerated and supercharged day-traders create entirely new ways to have a flash crash? Would governments and regulators have the impulse to protect these participants from themselves, or feel that the proverbial average retail investor needs to be protected? Would the self-regulatory arms of the markets (such as Finra in the US) put technology in place fast enough to keep up? And how would real-time market data services, much less reference data, keep up with all the complexities this would add to pricing?

Maybe we're getting ahead of ourselves with some of these questions, but the plausibility of retail availability of algorithmic trading would inevitably raise issues. And to that end, I'd like to also call attention to the Inside Reference Data discussion group that has already been present on LinkedIn, but soon to be tied together with discussions out there on Twitter and elsewhere, to stimulate engagement on industry questions. The group can be found here, and we'll ask for your reaction to this idea in the discussions section.

As a side note, I'd like to welcome Nicholas Hamilton, our new Inside Reference Data reporter based in London, to the publication and website. You may have already seen some of Nicholas' work online, and you will be seeing a lot more in the coming October print issue and in the months ahead.

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