Nanex: visualizing zillions of trades in a half-second

By way of Naked Capitalism, I learned of the video below produced by Nanex, the market data analysis company in Chicago. It runs for just under 6 minutes and shows all the quotes for Johnson & Johnson stock racing among a network of exchanges over just one half second of real time. Watch the whole thing and then remember -- this is just one half second (the clock, bottom middle, goes up in increments of milliseconds). Below the video, some explanation of what you're seeing from Nanex.

We got the idea after realizing, in face to face meetings with them [the CFTC], they didn’t understand market structure or the importance of latency and the consolidated feed. That was several years ago. We still aren’t sure if they get it, or are just playing dumb.

The bottom box (SIP) shows the National Best Bid and Offer. Watch how much it changes in the blink of an eye.

Watch High-Frequency Traders (HFT) at the millisecond level jam thousands of quotes in the stock of Johnson and Johnson (JNJ) through our financial networks on May 2, 2013. Video shows 1/2 second of time. If any of the connections are not running perfectly, High Frequency Traders can profit from the price discrepancies that result. There is no economic justification for this abusive behavior.

Each box represents one exchange. The SIP (CQS in this case) is the box at 6 o’clock. It shows the National Best Bid/Offer. Watch how much it changes in a fraction of a second. The shapes represent quote changes which are the result of a change to the top of the book at each exchange. The time at the bottom of the screen is Eastern Time HH:MM:SS:mmm (mmm = millisecond). We slow time down so you can see what goes on at the millisecond level. A millisecond (ms) is 1/1000th of a second.

Note how every exchange must process every quote from the others — for proper trade through price protection. This complex web of technology must run flawlessly every millisecond of the trading day, or arbitrage (HFT profit) opportunities will appear. It is easy for HFTs to cause delays in one or more of the connections between each exchange.

Model abuse... stop it now!

I think we would benefit from better and more realistic models of systems in economics and finance, better models for imagining and assessing risks, and so on. But it is true that having a better model is one thing, using it another entirely. A commenter on my recent Bloomberg piece on agent-based models pointed me to  this post, which looks at some examples of how risk models in finance (ones this author had helped develop) were repeatedly abused and distorted to suit the needs of higher ups:

For a person like myself, who gets paid to “fix the model,” it’s tempting to do just that, to assume the role of the hero who is going to set everything right with a few brilliant ideas and some excellent training data.

Unfortunately, reality is staring me in the face, and it’s telling me that we don’t need more complicated models.

If I go to the trouble of fixing up a model, say by adding counterparty risk considerations, then I’m implicitly assuming the problem with the existing models is that they’re being used honestly but aren’t mathematically up to the task.

But this is far from the case – most of the really enormous failures of models are explained by people lying. Before I give three examples of “big models failing because someone is lying” phenomenon, let me add one more important thing.

Namely, if we replace okay models with more complicated models, as many people are suggesting we do, without first addressing the lying problem, it will only allow people to lie even more. This is because the complexity of a model itself is an obstacle to understanding its results, and more complex models allow more manipulation.