Algo Trading Lures the Buy Side in a Fragmented Market
As it becomes harder to trade large blocks of stocks in U.S. equities without tipping their hands, buy-side firms are turning to algorithmic trading - a computerized strategy that carves up their orders into smaller pieces to conceal their executions.
"The logical response by the buy side has been to kind of slice and dice all of their orders into much smaller pieces so that you don't leave any footprints," says John Wheeler, vice president and director of U.S. equity trading at American Century. He notes that this is important so that trades do not move the market.
If American Century gives a floor broker 50,000 shares to represent its order on the New York Stock Exchange floor, the order is subject to price improvement and can be broken up by the specialist and other buyers on the floor, Wheeler says. So Wheeler feeds part of American Century's large orders into algorithmic trading strategies - proprietary models that reside on the sell side's computers.
How does it work? The buy-side trader picks which strategy he or she wants, then fills in the order ticket with parameters - such as start time, end time, the order type and the duration or time frame over which the order must be completed. The model analyzes the security's trading pattern and processes other data - such as liquidity of the stock, volatility, the spread and the bid/asked price - and then slices the order into a series of trades. An order for 10,000 shares may be broken into 40 trades and executed over the entire day, or several hours, depending on how aggressive or passive the buy-side customer wants to be. The computer might sell 200 shares, then sell 300 shares, then buy 400 shares, all in a random pattern to mask the goal behind the strategy so an institution remains anonymous and other participants don't catch on. It used to take a human being thousands of keystrokes to break up orders; algorithmic trading fills a void by doing it by computer.
The automated-trading strategy is taking off for three reasons: First, changes in United States equity market structure have made it harder to execute large blocks of stock. Second, the algorithms help buy-side traders manage workflow by automating the relatively easy and more liquid orders and giving traders time to focus on more complex orders. Third, on the buy side - as part of an effort to lower transaction costs and limit market impact - there is a trend toward measuring the quality of trades against the performance of a benchmark.
The Incredible Shrinking Order Size
While each of these factors is contributing to the demand for algorithmic-trading strategies, it's the limitations of the current market structure that seem to be piquing the buy side's interest the most, according to sell-side firms and buy-side customers.
Ever since the conversion on Wall Street from fractions to decimal pricing, the average order size has shrunk from 1,400 shares seven years ago to around 500 shares on both the NYSE and Nasdaq. "The markets have become more fragmented," says Goldman Sachs' global head of algorithmic trading, Jana Hale, who cites the introduction of decimalization, electronic communications networks and different trading strategies, such as statistical arbitrage, as factors contributing to the current market structure.
In addition, the depth on the inside book - the amount of volume at the inside quote - has fallen by 50 percent on the NYSE, and the total volume on the book has fallen by about 30 percent, says Andrew Silverman, U.S. head of algorithmic trading at Goldman Sachs.
"The pockets of liquidity have actually become much more hidden, order size has become much smaller," Hale says. Combine that with regulatory pressures to understand the costs and fees that are being charged in the industry and, Hale adds, "As a result, people need to access this new market structure in a much more efficient manner."
Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio
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