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Faster than a forest fire, the May 6th, 2010 flash crash was a breathtaking nearly-1000-point drop-then-surge on the Dow Jones Industrial Average that shocked traders and the general public to their core. Unlike Smokey the Bear, who can sniff out and fight fires before they start to flame, US regulators only became aware of the flash crash after it was over. The flash crash left scorch marks that have scarred the reputation of the bulwark U.S. stock market and singed investor confidence.
Regulators were completely stumped as to the cause. Months of investigations unearthed one very important piece of information: the regulators were unprepared and ill-equipped to deal with this kind of event. They had no method of sniffing out the smoke that could lead to a flash crash fire.
A year ago, the flash crash revealed the first significant sign of growing pains in a new generation of trading. This new generation introduced the capacity to let computer models do the dealing; it allowed clever traders with clever programmers to build complex algorithms that buy and sell in the blink of an eye. All of this progress was made with little thought to the possible repercussions of a mistake.
Thus it was that on May 6th, 2010 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 and wiping out $1 trillion in market value before recovering. That a simple mistake could take the market down so fast was unthinkable.
Since the original flash crash we have seen dozens of smaller ones, which barely warranted a thimbleful of ink in the press:
And as energy and other asset classes outside equities - commodities, FX, derivatives - become increasingly automated there will be more flash crashes. Increased interdependence of asset classes will lead to cross asset flash crashes – a domino effect where the crashes 'splash' across asset classes, possibly wreaking havoc for market participants and regulators. As regulators said following the flash crash: "a complex web of traders and trading strategies" links the fragmented multitude of markets here in the U.S.
Band-aids have been applied by the SEC; circuit breakers that prevent further trading when a stock moves more than 10% during a five-minute period. Market makers have been strong-armed to ensure they don't disappear when the market wobbles. The joint CFTC-SEC Advisory Committee on Emerging Regulatory Issues has made 14 recommendations on the May 6 Flash Crash including: implementing a limit-up/limit-down system, more extensive market access rules, studying the impact of maker-taker pricing and cancellation rates, and looking at a more cost-efficient audit trail.
These are a good start, but far from address the underlying problem. Like Smokey the Bear, regulators need a way to sense the smoke before the fire takes hold of the marketplace. Luckily there exist responsive and intelligent algorithms that can sense and react instantaneously to market anomalies and anticipate interruptions to liquidity. These rapid response algorithms could help to prevent the next flash crash by alerting risk and compliance managers of impending issues, or by changing trading strategies to accommodate market glitches. They can smell the virtual smoke and help to put out the fire before it starts.
On top of smarter algos, there are a few other splash crash prevention measures:
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. Brokers need better pre-trade risk controls to prevent fat fingered trades from getting to market. Algorithmic trading means that the market moves too fast for exchanges or other venues to detect problems before they impact prices. The detection of abusive patterns must happen in real-time, before any suspicious behaviour has a chance to move the market. This approach should be taken on board not just by the regulators, but by the industry as a whole. Only you can prevent flash crashes.
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