Thank you for that kind introduction. And my sincere thanks to everyone here for joining this lunchtime session. It’s a great pleasure and privilege to return to New York.

I want to offer a few reflections this afternoon on market innovation and, in particular, the on-going debate around high frequency trading (HFT), which has dominated global media over the last few months.

For regulators of course, the interest here is not simply around the novelty of 21st century technology (as important as this is) it’s also in the link between speed, market fairness, efficiency and safety – which is clearly a much longer-running saga in financial services.

And I feel able to speak with at least a little authority on this, having spent much of my career at the London Stock Exchange. And the London Stock Exchange was, of course, the venue for the first high frequency trade.

Now, I sense a little scepticism here – I am sure you are asking how anybody could be so definitive on such a fast-moving topic. Even the experts can’t quite agree a firm definition of what a high frequency trade is, so let me explain.

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A new book by author Michael Lewis describes how trading algorithms that detect and exploit tiny, fleeting profit opportunities, called high-frequency traders, have transformed the stock market. And not by ripping off middle class investors. But that doesn’t mean there are no problems. Read on to understand what high-frequency trading is, and what the real issues with it are.

What is high-frequency trading?

If you’re an average human being, your eyes take around 400 milliseconds to blink once. High-frequency trading is a kind of market activity that moves in less than one millisecond to spot and take advantage of an opportunity to buy or sell. It happens through trading algorithms, programs that determine how to trade based on fast-moving market data.

The kind of profit opportunities that high-frequency trading looks for aren’t the things most investors ever think about. They’re not betting that technology companies will see their profits grow more quickly than expected, for example, or that a recession is coming.

Instead, they’re looking for tiny opportunities for arbitrage. Imagine that, at precisely 10:30:01.01 AM, a share of Bank of America’s stock was trading at $16.02 on the New York Stock Exchange – but it was $16.04 on a smaller exchange called BATS. A high-frequency trading computer might spring into action by buying up shares of stock on the New York Stock Exchange and selling them on BATS. To make money this way you need to move super-fast, because the opportunity could vanish at any moment.

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