“And now,” cried Max, “let the wild rumpus start!” —Where the Wild Things Are by Maurice Sendak
An algorithm gone wild may cause a rumpus, to paraphrase Maurice Sendak, but it won’t be much fun. With algorithms and high frequency trading come the possibility of mistakes. Many more firms outside of the equities world are embracing algorithms and HFT, and their inexperience can cause market disruptions.
Thus it was that on May 6th when a mutual fund in Kansas entered a rather large ($4.1bn) sell order in E-mini S&P 500 futures contracts on the CME, the reverberations were felt throughout the marketplace. The order sparked a totally human panic on a day when fear was in the air and sentiment was leaning toward the bearish. The fire was then fanned by algorithmic trading strategies and HFT, causing an unprecedented drop within minutes.
Another type of algo gone wild happened last September when the CME Group plugged in some new contracts to Globex to try them on for size; they mistakenly went live and almost instantly got traded. The mistaken order flow began at 3:38pm ET time on Monday, September 13th and lasted for six minutes. Futures brokers noticed oddly anomalous spread price activity during that period, when trading is usually slow.
This six minute phantom orders mystery was solved, but the very fact that it occurred supports the argument that brokers, traders and exchanges need to have more advanced capabilities to detect problems and abuse as they happen, and recommend actions to take in response.
And, although the flash crash and phantom orders were christened in the equities and futures markets, the algo gone wild phenomenon has not since limited itself to one asset class.
An algo gone wild was spotted in the oil market last year: High frequency trading firm Infinium Capital Management suffered a six-month probe by CME Group (and reportedly the CFTC) into why its brand new trading program malfunctioned and racked up a million-dollar loss in about a second, just before markets closed on Feb. 3. The brand new algorithm went live four minutes before the end of trading and fired in 2000-3000 orders per second before being shut off. It caused a spike in trading volumes by nearly eight times in less than a minute and oil price surged $1 then slid $5 over the course of the next two days.
These two examples show you how HFT strategies are not supposed to work. 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, and it needs to be taken care of as such. Algorithms must be monitored constantly for performance and for errors, and sometimes tweaked on-the-fly to ensure best results. A good algorithmic trading platform will enable trading firms to do just that.
Trading firms are not the only ones who need to be on guard for possible algos gone wild. In the case of Infinium, the regulators and the exchange were also slow on the uptake. In the CME’s case, the mistake shows how the exchange lacked adequate monitoring technology to see that some test contracts had entered the live environment – and were being traded.
Everyone needs to be proactive in using the correct tools to monitor algorithmic trading. Sensing and responding to market patterns before the aberrations or errors have a chance to move prices is the right thing to do – in all asset classes. Be like Max and tame the wild things!
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