As readers will recall, just after the abbreviated Thanksgiving session, there were some pretty dramatic afterhours fireworks, both in stocks, and in a variety of volatility indices, that of gold (^GVZ)most notably. As the charts below capture, the drop in the futures had offset basically the entire day's upside in the span of milliseconds, leaving many wondering just what had caused this. Luckily, courtesy of the Tabb Group's Paul Rowady we now know that this was yet another glitch borne out of the hyper-technological sophistication of the current marketplace, in which the smallest error can and will propagate through the system uncontrolled resulting in major losses for those who are aligned on the same side as the ponzi. In other words: it was yet another flash crash which luckily did not have a major impact as virtually no volume was being transacted in the market. All this merely means that Ben Bernanke, who is doing everything in his power to boost asset values, has increasingly more variables working against him as the system continues being pushed ever further away from its natural equilibrium, until one day it all just burns down.
These were the charts we posted on November 26:
And here is the explanation for what happened:
The Tale of the Buried Headline
On Friday, Nov. 26, a technical oversight allowed stock and options exchanges operated by BATS Global Markets to extend regular trading beyond the abbreviated holiday session, a session that was officially scheduled to close at 1:00 p.m. EST.
The resulting cascade of problems this oversight caused is both fascinating – for its symbolism of how oddly precarious some of our most mature markets have become – and cautionary for its addition to the growing list of precedents that could be interpreted to foreshadow things to come.
Allowing the regular trading session to continue beyond the scheduled close, BATS inadvertently marked after-hours trades as normal-session trades, which ultimately influenced the closing prices of equities and indexes on that date. That in turn caused options that would have previously expired worthless to be marked in-the-money and therefore exercised.
Since no other exchanges were distributing market data marked as “regular session” after 1 p.m. on Nov. 26, the BATS’ market data was used by market data vendors like Thomson Reuters, Bloomberg and IDC for that day’s closing prices, and the Options Clearing Corporation (OCC) used that data to determine which options were in- and out-of-the-money for the month-end exercise.
For example, while the closing price at 1 p.m. for the SPDR S&P 500 ETF (SPY) was greater than $119, the BATS prices ultimately used by the OCC ended up at less than $119. The impact of this (which was further inadvertently exacerbated by the OCC’s auto-exercise service) was for SPY Nov. 119 calls to expire worthless and the SPY Nov. 119 puts to be in-the-money – when the opposite should have been the case. Eventually a few P&Ls on Monday morning were askew.
Clearly, the scenario of a holiday-abbreviated session falling on the third Friday – expiration Friday – of a month had not properly been considered in all the hours of development for these particular exchanges. And, clearly, market data vendors had insufficient data scrubbing routines in place to test the validity of certain raw market data.
Finally, it is clear that the OCC did not have its own procedures in place to vet certain market data, even if it was coming from the most venerable sources. In short, this was not a data problem. This was a processing problem in which a bunch of folks dropped the ball.
While all the yammering and chattering around this episode suggests that relatively little damage was done, it speaks of the wild world of uncontrollable complexity risk.
So fasten your seat belts because it could get worse before it gets better. The good news: what doesn’t kill us makes us stronger.
Back in the day when I was the CIO for a high-turnover statistical arbitrage fund, I used to feel a perverse sense of good fortune when my team would experience unforeseen “glitches.” Since there was simply no way to anticipate every possible permutation of challenges “in the laboratory,” the only way to come anywhere close to bullet-proofing our systems and processes was to keep our jalopy on the proverbial track for as long as possible and overcome whatever technical or market-oriented challenge came our way – thereby ultimately (and hopefully) evolving our platform to a finely-tuned performance machine.
The same logic can be applied to the aforementioned BATS event as well as the recent Flash Crash. (In the case of the Flash Crash, the regulators bear some responsibility for not “federating” the rule book for an increasingly fragmented marketplace.)
Confidence issues and other grumblings aside, these problems – now that they’re in the rear-view mirror – actually make markets better, stronger healthier and more fault tolerant.
Sure, on one level, any kind of glitch on financial exchanges spooks the bejesus out of an already-traumatized public and serves as catnip for a mainstream media machine conditioned to inflate any and all imperfections in the financial firmament. However, the fact that these events have expanded our collective library of possible scenarios is a net positive for everyone (assuming we learn from them).
Here’s the buried headline: While we should always expect and prepare for the unexpected, the capital markets’ growing dependence on technology to do more, faster and with fewer people represents a recipe for an increasing frequency of surprises.
The quality control requirements for this level of unprecedented complexity defy comprehension, particularly within the largest financial intermediaries and the most fragmented markets. It’s a wonder that more glitches don’t find their way to the light of day.
To begin with, regulators around the world could play a major role in combating complexity risk by simplifying the rule book.
But the truth of the matter is that we simply cannot understand the full spectrum of what could go wrong.
One of our industry’s greatest ironies may be that the most challenging aspect of combating complexity risk is in finding ways to simplify systems, processes and operational infrastructure.
An increasing reliance on technology and automation creates intangible costs (and risks) that are not properly appreciated in our business. Excessive cutting of people in favor technology – or over-automation – incrementally exacerbates these risks because people are the only defense against “what we don’t know.”
Exhibit A: State Street just announced that it will cut 5 percent of its workforce through the end of 2011 as part of an “information technology transformation.”
Mark another point in the win column for complexity risk.