As the markets have stabilized from the COVID-19 health crisis, we will move on to other topics in the general area of best execution. Hopefully, we will not have to return to the impacts of the virus on trading. We will continue to provide a series of insights into the current trading environment.
Understanding the market environment in which traders attempt to achieve best execution is critical to understanding performance. That is why we have been looking over the past few weeks at key trading metrics such as volatility and shifts in available liquidity. All of this, however, is in the service of providing context for measuring and understanding trading performance. The aims of best execution are to report and monitor performance as part of due diligence oversight, as well as to understand how trading behavior can be modified to reduce costs. This week, we will begin a look at trading cost performance.
In order to examine trade costs, we need to first decide which benchmarks we should use to measure performance. There is a wide variety of trade cost benchmarks which cannot all be addressed in a short research note. All of them attempt to answer at least one important question about best execution, but none of the benchmarks answer all the requirements for doing Best Ex. As such, a suite of benchmarks is generally used for trade cost analysis.
The headline benchmark needs to be Implementation Shortfall (“I/S”). Implementation Shortfall is the difference (slippage) between the market price of the stock when the decision was made to implement the investment idea and the final execution price for an order. Because I/S measures the true cost to the fund to the investor it is the key benchmark in providing best execution.
Why I/S became not only the leading benchmark but, in many cases, the only benchmark for evaluating trade costs is an interesting case study in the history of ideas, but suffice to say here, that it largely supplanted VWAP because of the potential for VWAP benchmarks to be gamed by a trader.
By Henry Yegerman, ISS LiquidMetrix