Automated trading

Trading firms need to move fast to take advantage of price anomalies, and automated trading technology can make it happen, solution provider Trading Technologies explains.

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By  Diane Saucier and Tom Haldes Published  May 21, 2008

Trading firms need to move fast to take advantage of price anomalies, and automated trading technology can make it happen, solution provider Trading Technologies explains.

Recent years have seen a surge in the growth of automated trading. The global electronic markets continue to attract more volume, as firms worldwide utilise trading automation at an increasing rate.

This allows traders to deploy complex strategies that would be impossible to execute manually.

Many trading firms are moving from traditional position trading strategies into high-frequency strategies centred on statistical arbitrage and automated market making.

As data volumes soar, the ratio of quotes to trades increases as well.

Consequently, they are devising increasingly complex trading algorithms that seek to identify temporarily mispriced assets, taking short-term positions to capitalise on theoretical price anomalies and reversing the trade when they feel the price has reverted to its intrinsic value.

As more trading firms move toward high-frequency, automated trading, more order flow is generated. The increased flow by definition increases liquidity.

This in turn stimulates more orders from other market participants, and so on. With the emergence of multi-exchange, high performance electronic trading platforms, traders can more easily build strategies centred on cross-product relationships across any number of exchanges.

As a result price movements on one exchange may generate transactions across other exchanges around the world, adding to the ever-increasing volume of electronic order flow and market data.

Market data rates are skyrocketing as a result of automated electronic trading. In the last 10 years, market data has grown by roughly two orders of magnitude, requiring ongoing upgrades of data networks and computing systems.

And this growth is continuing, so today's data infrastructures will require persistent improvement and expansion to keep up with constantly increasing market data volume.

But as data volumes soar, the ratio of quotes to trades increases as well. In some markets this ratio approaches 1,000:1. While the ratios are not as high on the futures side, all exchanges have seen a dramatic increase in their quote-to-trade ratio. Eurex, for example, received eight times as many quotes per trade in 2006 as in 2001. 

To understand what is behind the so-called market data "tsunami," consider a high-frequency trading system that is auto-quoting options. A single price movement in the underlying security may cause the system to re-quote every strike for every month in the series.

Now assume the underlying security itself is being quoted by a high-frequency black box algorithm.

This means that each re-quote of the underlying security can result in re-quotes of hundreds of strikes in the options series. This illustrates why real-time market data is becoming such an issue for exchanges, vendors and trading firms alike.

Technologies devised for automated trading are making markets more interdependent. As bigger data pipes and faster computers are increasingly deployed by trading firms to monitor real-time prices across multiple markets, the window of time required to capture inter-market arbitrage opportunities is diminishing.

At the same time, high-performance trading systems are no longer strictly in the domain of the world's largest banks and funds. Instead, high-performance, low-latency technology is becoming a basic necessity for the ways in which most trading firms assess opportunities, execute trades and manage risk.

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