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Regulators grappling with market data: a case study

Published in Automated Trader Magazine Issue 29 Q2 2013

Regulators and trading firms have at least one thing in common: they both find grappling with the torrent of data generated in today's markets a tall order. The CFTC is just beginning to wrestle with the flow of swaps data, while the Securities and Exchange Commission has a head start on the equities side. It has deployed MIDAS, the Market Information Data Analytics System, developed by Tradeworx. Automated Trader met Gregg Berman, senior advisor to the Director at the SEC's Division of Trading & Markets, to find out how the regulator hopes to develop the MIDAS touch.

(Editor's note: Automated Trader subscribers can also access a wide-ranging interview with the CEO of Tradeworx, the company that supplied MIDAS here.)

AT: Could you describe what you're doing with this new system?

Gregg: First of all, what is the system? The system collects and gives us an analytical platform for the prop feeds that come from the equity exchanges. Each of the equity exchanges produces its own proprietary feed and that contains full depth-of-book quotes. Some of them contain lots of detailed information, quote IDs and other fields that we can use to construct and analyse how quote traffic is moving, tying into trades. We also get the Opera feed, which is the options market. We get Tape A, Tape B, Tape C, which are the public consolidated tapes.

AT: So you have it for every equity platform?

Gregg: If it's public equity data, we get it. It's only the public feed, so we don't get any information on dark pool activity except for trades that occur in dark pools which are required to go to the public already.

Before this, we would have been able to see the data that would have come from the … consolidated tape that gives you best bid/best offer from each exchange and all the trades that happen. That's readily available, but it's still a large volume of data and we didn't necessarily have systems that were good at processing and analysing that information.

We did not even attempt to access on a regular basis the prop feeds, where you had the full depth of all the cancels, all the modifications, et cetera that were going on at the individual exchanges - and that was the detail that we wanted.

AT: Maybe describe the kind of analysis you want to do?

Gregg: So, there are three categories of analysis. The first category, and the one I think that people tend to think about first, would be forensic analysis, looking at events that have happened and understanding them a lot better than we do. The Flash Crash was analysed the entire day, the entire market. But there are also one-off events that happen that we need to drill down, we need to look at the order books, we need to look at how the trading works, to better understand exactly what happened.

AT: Is that where you'll get into situations with individual firms?

Gregg: You don't have firm identifiers. This is all public information, so these feeds do not contain information on the parties. So in order for us to get information on the parties on a regular basis, we're going to have to wait for the consolidated audit trail, which is a new rule that we have to produce a market-wide repository of all trades, all orders, including dark pools, including the customer IDs - that will take years to develop.

But even if we don't have the IDs of participants, we can still do a lot more than we can do today.

AT: Does that mean you have no visibility as to whether activity is by one firm or different firms?

Gregg: No attribution. You might try to glean something statistically, by looking at when the quotes came in. So if a bunch of buys come in that are tagged within the same microsecond, it's unlikely that those orders are from two participants, just because the probability that they come in from a hundred different participants at the same microsecond is small. You might be able to infer some things in the data, in the same way that an asset manager or a hedge fund might be able to infer it themselves. That's the art of trading, trying to figure out what other people are trying to do.

Regulators grappling with market data: a case study

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