VWAP: down but not out

While the VWAP benchmark has lost favour among the buy-side, with some describing it as “a measure of mediocrity”, many traders still consider the VWAP execution algorithm as a useful component of
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While the VWAP benchmark has lost favour among the buy-side, with some describing it as “a measure of mediocrity”, many traders still consider the VWAP execution algorithm as a useful component of their daily trading strategies.

Instead of allowing a benchmark-based algorithm to work an order throughout the day, dealers are regularly tweaking parameters, limits and even switching algorithmic strategies on the fly to ensure they generate as much value as possible from the trade.

“More and more traders are being given discretion to change strategies halfway through an execution,” says Rob Boardman, head of algorithmic sales at agency broker ITG. “They are not after an average, they are trying to beat everybody else and they are trying to impress with execution quality.”

The buy-side’s willingness to make a judgement on how, where and when to trade is “a profound change”.

Active management of algorithms forms a core part of some buy-side firms’ execution strategies. “We have never really seen algorithms as tools that you simply leave running without monitoring them,” says Peter Baillie, senior equity dealer at Edinburgh-based asset management firm Martin Currie Investment Management, which has been using algorithms since November 2007. “We have always used a dynamic approach to strategies, limits and aggression levels rather than letting the algo get on with it, unchanged from the first release.”

Through the course of the day, says Baillie, Martin Currie’s traders might progress from working part of an order in an implementation shortfall strategy to stretching the order out over time using a VWAP strategy before shifting part of the order to a more liquidity-seeking type of algorithm. “We have a dynamic strategy around altering the algorithm used from one strategy or provider to another and varying limits or aggression levels throughout the course of the day,” he says.

For others, algorithms allow an important degree independence from brokers’ sales trading desk. “If there is no natural liquidity in the marketplace, we feel that our traders have better access to a larger amount of trading venues than a sales trader at an investment bank. Algorithms allow us to deal the order ourselves,” says Steve Wood, global head of trading at Schroder Investment Management. Use of algorithms for single-stock trading “gives us a lower commission rate, plus we don’t have any information slippage. The deployment of algos in the high-touch single-stock arena has increased dramatically,” he adds.

Schroder does not use VWAP algorithms, opting instead for implementation shortfall and derivative strategies, plus some proprietary algorithms.

While a VWAP algorithm may seem to some like a poor choice in a trading environment that favours quick executions, choosing the right strategy is not that simple. High volatility may affect a VWAP algorithm’s ability to hit a VWAP benchmark, but it does not diminish its usefulness as a tool to spread an execution over a period of time.

If you use a more aggressive algorithm to capture an attractive price quickly, this could be deemed a bad execution if the price continues to move in your favour after the trade. A VWAP algorithm, however, could capture this favourable movement if employed correctly.

“If you call the market right on a VWAP strategy, you will get a good execution,” says Baillie. “If you call it wrong you will end up stretching the order out into a market that is going against you and get a bad execution. Implementation shortfall can be the same. An IS strategy will tend to execute more slowly as the price moves away from you, so if you consistently call the market wrong when using an IS strategy, you will get a slower execution and a worse price.”