Posted by Dan Hubscher
Algorithms and high frequency trading have been blamed for everything from the credit crisis to the May 6th flash crash and high speed market abuse, and have attracted unwanted interest from regulators on both sides of the pond. But questions remain whether these tools are really computer models gone wild or whether they are the spoiled children of reckless parents - regulation.
According to Dictionary.com, the definition of reckless is to be utterly unconcerned about the consequences of an action. One could argue that the Regulation National Market System was designed without regard to some of the consequences down the line. Blaming the wild children, algorithms, is to ignore that the parents - RegNMS - were somewhat reckless in designing the system.
In a blog on the TABB Forum on January 24th, Steve Wunsch of Wunsch Auction Associates explained that the system was working the way it had been designed.
"What really went wrong in the stock market on May 6? Prices aside, all of the plumbing was working fine. Not only were there no fat fingers, rogue algos, manipulators or terrorists at work, there were no significant breakdowns of order routing systems or data systems or any other elements of the stock trading infrastructure," wrote Wunsch.
Meanwhile, the National Commission on the Causes of the Financial and Economic Crisis in the United States released its report (Jan. 27th) and HFT was not mentioned at all. Nor were algorithms, as such, but 'computer models' were vindicated. The report said: "The crisis was the result of human action and inaction, not of Mother Nature or computer models gone haywire."
And it criticized regulators for not doing their jobs: “Widespread failures in financial regulation and supervision proved devastating to the stability of the nation’s financial markets.”
The result of the credit crisis and market meltdown in Sept. 2008 was the Dodd-Frank Act, which attempts to prevent another Sept. 2008. But the flash crash insinuated itself into the picture, pointing out that no one had baked that possibility into the market reforms. And, ironically, the market reforms set the stage for more flash crashes.
At the Tabb Forum Derivatives Reform Event a couple of weeks ago, a lot of people commented that Dodd-Frank puts in place a market structure that injects the equities and futures markets model, along with fragmentation, price transparency, streaming quotes, into other asset classes. This theoretically invites algorithmic and high frequency trading and the threat of more flash crashes. At the event Peter Fisher of BlackRock said that what keeps him up at night is a flash crash in the interest rate market, citing the market structure argument, but specifically pointed out that this possibility was not envisioned in Dodd-Frank.
With more and more asset classes becoming tradable electronically, partly thanks to mandated swap execution facilities (SEFs), the possibility of truly wild or rogue algos and market abuse becomes increasingly inevitable. And, as we pointed out last week, the very real possibility of a flash crash splashing across asset classes - we call it a "Splash Crash" - rears its ugly head.
Although the evidence against algos gone wild is thus far anecdotal for the most part, the belief that they can and will go wrong permeates the industry. Market abuse such as insider trading and manipulation are undoubtedly more prevalent. Fat finger errors are easier to prove, and are a fact of life in a high speed, high stress electronic marketplace.
Stay Calm and Remain Vigilant
The antonym of recklessness is vigilance. The regulatory parents must be more vigilant when it comes to their arguably brighter and naughtier children - algorithms and HFT. With algorithms and HFT come the possibility of mistakes and abuse. Many more firms outside of the equities world are embracing HFT and their inexperience can cause market disruptions. A flash crash in oil or other commodities - or even foreign exchange - is not to be scoffed at. In fact, many commodities markets are much less liquid and homogenous than equities, and can be even more vulnerable to mistakes or manipulation.
There are a number of best practices that can be used to mitigate against algos going wild:
- Diligent backtesting – using historic data and realistic simulation to ensure many possible scenarios have been accounted for. A backtesting process needs to be streamlined of course – as short time to market of new algos is key.
- Real-time risk monitoring - building a real-time “risk firewall” into your algo environment. Just like a network firewall stops anomalous network packets reaching your computer, so a risk firewall should stop anomalous trades getting to trading venues.
- Real-time market surveillance. Even if trades do not breach risk parameters, they may breach compliance rules, regulations or may be perceived by a regulator as market manipulation.
An algorithm is a tool in a trader's toolkit, not a naughty wild child. If the regulator parents are vigilant, and algos are subject to practical controls and monitored constantly for performance and for errors, market participants can sense and respond to market patterns before the aberrations or errors have a chance to move prices.