Blink, and you'll miss it: The blinding speed of trade
The blink of an eye lasts 300 to 400 milliseconds. And the last time you blinked, billions of dollars were made or lost through high-frequency trading - the lightning-speed, mathematics-driven, computer-based buying and selling of huge blocks of securities.
It's the way the bulk of trading is done nowadays in the United States. It's going to take over stock exchanges around the world and will leave retail investors like you and me flailing in its wake.
More stock exchanges may be providing 'real-time' prices to various free website services such as Google and Yahoo Finance, but we don't stand a chance against speed trading measured in milliseconds.
Our traditional image of securities trading is hectic activity on the trading floor, with brokers yelling into phones, traders waving paper order slips and talking heads opining on firms' results and the impact on their stock prices - facts and figures that ordinary investors can understand and act on.
That relatively low-tech scenario is receding from today's hi-tech reality. Financial markets are increasingly driven by the arcane mathematics programmed into supercomputers, and the market movers are high-frequency traders - armies of mathematicians who decide to buy or sell securities in milliseconds.
Their decisions are based on the short-term statistical behaviour of a company's stock price regardless of that firm's fundamentals or prospects. Their goal is not to realise a healthy gain in the long term - a year, a month or even a day - but simply a cent or two per share in each transaction.
Of the 20,000 trading houses in the US, 2 per cent of them now account for 70 per cent of total trading volume through high-frequency trading. In Europe, 40 per cent of trading is high-frequency, while the estimate for Asia is about 10 per cent and growing fast.
High-frequency trading involves a variety of strategies but underlying them all is the mining of a large amount of financial market data and geopolitical information, and acting on them before anyone else does. One major trading house estimates that if every trade is delayed by just one millisecond, it would lose about US$100 million in a year.
An example of a simple strategy used by high-frequency traders is to monitor the volume of transactions and price fluctuations of stocks, known as the order flow. They extract information from the order flow to make buy-sell decisions before the market at large has fully digested such data.
In fact, many trading houses locate their computers in the same data centre as the New York Stock Exchange, for a fee, to capture the NYSE order flows within 65 microseconds (one-millionth of a second) after a trade is made. That is about 5,300 times faster than the blink of an eye.
While technology and mind-curdling math may be great for high-frequency traders, what do they do for the rest of us? They may make markets more unstable. The large amounts of securities traded and the speed with which powerful computers execute those transactions can create a domino effect across the market.
Witness the 'Flash Crash' in the US stock market on May 6, 2010. On that day, the Dow Jones Industrial Average plunged 600 points in 20 minutes, the largest intraday point loss in history, only to recover much of those losses within minutes. The event was triggered by a trader who, in one transaction, sold US$4.1 billion in securities, whose immediate price drop led to dramatic swings in the market.
Indeed, high-frequency traders may seek market volatility, which puts those with the technology and brain power at great advantage. In the past two years, whenever there was widespread uncertainty about central banks' monetary policy or response to the financial crisis, there was a corresponding surge in high-frequency trading activity.
A trader stands to make millions by anticipating by mere milliseconds whether Greece will default on its debt or if China will make its currency more convertible.
Adding to this unpredictability is the complexity of the mathematical models used in high-frequency trading. From chaos theory, we know that even simple mathematical models can result in unexpected outcomes. The Flash Crash is a prime example.
There's the optimistic view that as computers get ever faster at scrutinising larger amounts of information, we will better understand the behaviour of the financial markets, which would benefit us all.
But the late mathematician Benoit Mandelbrot disagreed with this view. Applying fractal geometry to financial markets, he concluded that their complexity resembled complex configurations in nature. For example, the ruggedness of a coastline remains rugged no matter how closely you observe it. Similarly, the financial market will always be complex and unpredictable no matter how closely you monitor it. This perhaps is the fundamental law of financial physics - and not even high frequency trading can violate it.
Ordinary investors who do not have the information, technology or financial scale of the high-frequency traders will just have to ride the tsunamis they generate, and prepare to be submerged.
Tom Yam is a Hong Kong-based management consultant. He holds a doctorate in electrical engineering and an MBA from the Wharton School of the University of Pennsylvania. He has worked at AT&T, Ernst & Young and IBM
Number of shares traded on the high-frequency platform in Hong Kong last year - a 'negligible' amount, according to HKEx's CEO