I have been having all sorts of conversations with people about different ways that the FFI might be used. One such area concerns how fragmentation distorts common trading benchmarks such as Volume Weighted Average Price (VWAP). This is commonly used to measure a broker’s ability to execute a large block of shares over the day without impacting the market price of the stock concerned. By comparing each trade that comprises the original order with the average market price at that time, it is possible to build up a picture of how those executions compared with the price of the stock over the day. Now, here’s the problem: when a stock is heavily fragmented you no longer have one single venue to benchmark the price at and, without a consolidated tape, there is no “agreed” market price for a stock. Most VWAP algorithms reference the home exchange for a particular stock and so they are becoming increasingly unreliable as an indication of broker performance.

Instead, the broker and his client need to agree which venues are to be included in the VWAP calculation. This could be all possible venues a stock trades at; all venues a broker has access to; or all venues that trade above a certain percentage of the stock. The net result of this is that VWAP will become a meaningless measure as different brokers will use different criteria in its calculation.

The answer could lie in the FFI. This can be used as a benchmark to agree the appropriate valuation of VWAP so, for example, stocks with an FFI less than 1.5 could still just reference the home market and those with an FFI above 2 will need to include all venues in any VWAP calculation. I suspect we would need to calculate the FFI on a more real-time basis for this to really work but it’s a good example of how the FFI can solve a real world problem.