NYSE and the Ficaps

This is part 3 of the series on NYSE order flow started on Sept. 1st. This post looks at the residual of retail and program trading, which I have termed FICAP (funds, institutions, commercials and prop shops). This is the deep jungle where the 800 lb gorillas roam and includes the likes of GS, MER, LEH, C, and the usual suspects with deep pockets seeking alpha. In August this group accounted for 16% of NYSE trades but 38% of the volume. The average trade size was only 809, which suggests this group is also masking true order flow volume by trickling 100 share orders into the pipeline, but they are having a harder time doing it perhaps because of the sheer volume of trades that need to be executed and the fact that many of the trades are executed de facto rather than run through the electronic algorithmic trickle filter. It's understood that the bulk of the program trading discussed yesterday is also executed by this group, so the numbers may be somewhat misleading, but the focus of this study was to understand order flow dynamics, not necessarily the character of those submitting the orders.
NYSE case study - WM - just looking at a few stats we find 888.41M shares outstanding with 92% held by institutions with average daily trading volume in July 8M shares and 14M in August. So we are seeing 1-1.5% of total shares traded each day for the past 2 months. In August WM averaged 44,000 trades per day or about 113/minute. These numbers are averages and the 60M chart shows that the volume is typically skewed towards the open and close so a more realistic trade frequency is in the range of 250 trades/minute for the first and last hours. As I watch my L2 time and sales data for WM stream by this morning the vast majority of the trades are 100 lots, a few 200 and an occasional 1000. In the first 90 minutes WM has already traded 4M shares = approx. 12,500 trades = 140 trades/minute. As Dr. Brett points out, it would be very helpful to have this information available as a data stream in order to gauge market momentum. This can be accomplished by dumping your data feed into an excel spreadsheet (if available on your platform), and then massaging the data a bit to produce a dynamic force indicator. This is not a trivial effort and is possible with only a limited number of data providers. This is a work in progress and I'll report on any new developments.
Prop shops - the impact of proprietary trading shops is often overlooked, but it should not be underestimated. These are typically hypertraders who are scalping pennies out the market on sheer volume. In order to accomplish these ends trades must be executed as blocks. The large cap NYSE stocks are a regular stomping ground of this group and the effects can be substantial. A few months ago I met a very accomplished trader who worked with a little known 1000 trader Chinese prop shop with $1B capitalization and a very active participation in US equities. These traders are the top financial and mathematics college graduates and are carefully selected and trained (and culled when they don't perform). Do you think these guys can nudge the markets a little bit when they set their minds to it?