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COMMENTARY 72 SEPTEMBER 2OO2

HOW BIG IS THE STRIKE ZONE?

At the heart of Plexus Group's transaction cost measurement is the comparison of the "strike price" atthe time when the trade order became actionable to the transaction prices received in the marketplace.The difference is the cost of implementing the order. In this spotlight, we discuss how Plexus establishesa strike price, and present some ideas on how to set more representative strike prices.

Strike Prices

The financial management industry assigns greatprominence to markei prrces. Yet we all realize thatany historical price is no more than a snapshot or aflicker of a volatile, dynamic process.

Suppose a portfolio manager forwards an order tohis trade desk on February 13th at forty secondsafter 1:30 in the afternoon. The implementationshortfall methodology requires comparing pricemovements between this point of initiation (the strikeprice) and the ultimate execution prices. Should weaccept the bid, the ask, or the last print (13:30:40 on2113102) as the best benchmark? Did the portfoliomanager really focus all of his intellectual power onthat particular instant? ln contrast, would someappropriate sample of the concurrent stream ofprices result in a more representative strike price?

Years ago Plexus adopted a solution for this strikeprice question that applied a "representative timeframe" approach. We knew - or could infer - thetime at which the order was presented to the buysidetrade desk, but we were concerned about therepresentativeness of these flicker prices. Oursolution was to average prices surrounding themoment of order release.

Somewhat arbitrarily,we

chose a ten minute clock period during which theorder was received on the trade desk. Our loqic wasas follows:

1 . By using an average we minimize the effects of thebouncing of prices between bid and asked.

2. We selected the volume weighted price for thisshort time interval instead of the mid-spread pricebecause it would tend to weigh the

preponderance of buyers and sellers in themarket: When buyers were dominant, the volumeweighted price would likely be above the mid-spread price.

3. Averaging dampens the pafticularly unstableopening and closing prices.

4. The recording of time stamps into the ordermanagement systems is often subject to smallrandom delays.

5. Most investment managers base their selectionson a threshold price, not on a specific momentaryorice.

6. Organizing our databases on a ten minute timeslice vastly accelerates data retrieval and reducesstorage requirements.

While ten minutes felt "about right," not everybody

buys into this logic. Some argue that ten minutes itoo long an intervalwhen markets are moving rapidly.So we decided to re-examine our assumptions in thelight of new data capabilities at Plexus.

We looked into our new daily-updated databases otick data on the 8000+ most widely traded stocks onthe planet. We examined the dis-tribution of numberof trades per day across all companies. We thenexpanded our investigation to focus on non-retailtrades greater than 1000 shares or 5000 shares per

trade.

The table shows the compiled information for the lasttrading day in June, 2001. Any of the first threecolumns can be read as a category. To illustrate,consider the last line in the table. One company(Cisco) recorded 52,455 trades that day, 874+ perminute, or on average one every seven-hundredthsof a minute.

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Suppose we were to rebuild our average pricedatabases to include higher frequency data"buckets." Instead of ten minute buckets, we couldform one minute intervals on, say, every stock withmore than '1000 trades per day. In the table, thisstandard applies to the line describing the 1001-5000Trades Per Day. 1000 trades per day implies a tradeevery 5 seconds on average, or 12.5 per minute.

Responsible statistical averaging requires arespectable sample size. Plexus distrusts any tradingstatistic based on less than ten observations. Thustwelve samples per minute, 5000 trades or more perday, corresponds to this lower time interval to buildreasonable samples.

Elimi nating Retail Tradi ng

One of the bothersome aspects of counting eachand every trade is we overstate the liquidity oncompanies such as the NASDAQ-Iistedcompanies that command a great deal of retailinterest but little trading in institutional size. Toanalyze the depth of institutional interest, weperformed the same analysis, this time eliminatingall trades less than 1000 shares.

The results clearly indicate how rapidly marketliquidity thins out. Only nine stocks make the

1000 trades drops from 785

twelve trades/min.cutoff: six NYSE,three NASDAQ, andzero non-US. Thenames

areHoney-

well (story stock ofthe day), ExxonMobil, Citigroup, No-kia, Global Crossing(story stock) AOLTime Warner, Intel,Oracle, and Cisco.)The number ofstocks with at leaststocks to 190.

Our conclusion is thus even stronger than before.Focusing on only institutional sized trades over1000 shares, there are only a handful of com-panies with sufficient daia to justify shoi-teraveraging intervals. lf we set a standard of at least5000 trades per day to form rea-sonableaverages, 10 minute or longer trade intervals arepreferable for 99.9% of all stocks in our universe.Against a standard of 1000 institutional trades perday, a minimum of a 10 minute interval is requiredfor 9B.B% of the trading universe.

The table shows us that exactly 99 stocks, I NYSE,75 NASDAQ, and 15 non-US had 5000 trades ormore per day. Only 12% of the institutional universehas more than 5000 trades per day.

Companies with lower trading frequencies require alonger time interval (e.9. ten minutes or more) togather enough data for averaging. However,suppose that instead of cutting off at 5000 trades perday, we cut off at 1000 trades. In this sample thereare 785 stocks with more than 1000 trades per day;

199 NYSE, 372 NASDAQ, and 214 non-US stocks.Even by this loosened standard, 90% of the stockstrade so infrequently as to make an averaginginterval less than ten minutes questionable.

Reprint any porTion with credit given to:Plexus NewsPlexus Group has been acquired by JPMorgan lnvestorServlces. This relationship helps us to rapidly strengthenexisting services and introduce new products, whilemaintaining our confidentiality, objectivity and trustworthiness. ''Iexug

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