My New Stock Stat: Slug-to-Whiff Ratio - TheStreet

My New Stock Stat: Slug-to-Whiff Ratio

It's hard to find innovative stock performance metrics, so I've decided to invent some.
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Major League Baseball and the major stock exchanges both will hit midseason in a week, and die-hard fans of hitters and equities are busy voting for their all-stars with either ballots or money.

Both sets of voters let their emotions guide them to a certain extent, but it's remarkable to me that baseball offers observers a richer and more thoughtful set of performance-measuring statistics to guide their decisions.

Visit any major sports Web site and you will typically find a "Stats" link right on the home page, offering access to easily sorted tables of all the hitters in each league by year-to-date batting average, on-base percentage and slugging percentage. Sometimes you'll find more-obscure metrics, such as hitters' stats against individual teams and pitchers, or in particular ballparks, or in day games vs. night games.

Visit any major financial news Web site, in contrast, and you'll have to hunt for a list of even the current day's top 10 performers, much less a quickly sorted list of the top 100 or 500 most heavily traded stocks. Moreover, the metrics are largely limited to the current day's percentage gain or loss, plus the raw number of shares traded. How useful is that? Click a little deeper and you might find one-year, six-month and three-month percentage returns for individual stocks. But it's pretty hard to find a year-to-date return, standard deviations, alpha or any more-sophisticated measurements of performance that might help you get beneath the yadda-yadda-yadda of the market players and learn about the tectonic changes that are truly going on beneath the surface.

How come? Despite the fact that stocks appear on the surface to be all about numbers -- growth rates,

price-to-earnings ratios,

return on equity, etc. -- the high priests at brokerages and in the press typically profess wariness about statistics, preferring to talk mainly about ethereal factors like management, new products and global economic conditions. Very few technical analysts or statisticians have managed to rise above the investment media's math phobia to offer just plain facts about the condition and direction of the only thing that ultimately matters about a stock -- its price. Some Web sites, like

Briefing.com

, offer pretty good numbers for market indexes overall -- e.g., the number of daily advancers vs. decliners, or new highs vs. new lows -- but outside the

Investors' Business Daily

newspaper, there's still an appalling lack of useful daily, weekly, monthly or annual performance data on individual stocks.

Love of Sports Stats

The fact that baseball has exalted stats to higher and higher levels is thanks in significant part to sportswriter Bill James. His philosophy could also serve as a standard for statistics-loving investors. From 1977 to 1988, James published a series of books called "Baseball Abstracts" that extolled the advantages of understanding baseball by analyzing an aggregation of data about players and teams rather than just observing them on a daily basis and listening to their timeworn refrains. "Cliches are the soldiers of ignorance," he wrote, while "statistics look at games by the hundreds ... Without them, it is impossible to have any concept of the game, save for meaningless details floating in space."

So what can we do to make stock statistics more helpful in our quest to understand the market game? I have some ideas.

My favorite Jamesian conceit, for starters, is to invent new statistics from time to time to uncover trends that aren't well explained by conventional means. In my line of work, these typically come in the form of new stock screens. A screen, after all, is essentially a big algebraic equation which attempts to solve a problem. In my

last column, for instance, I offered my new Rocket Range equation -- a formula that finds the stocks that are trading within both the widest possible range of long-term and short-term moving averages and within the widest ratio of current price to 52-week high. I don't really know how useful this statistic is, but it won't be long before we find out.

My quest now is to create a whole new suite of stats that will help us understand stock movement better -- and I would like to encourage you to help. If there's a stock price or volume situation that you believe can be captured in a formula -- and the numbers are easily downloadable through the Web, and processed in a spreadsheet -- then send an email, or post it in the

SuperModels

online bulletin board. I'll offer one new one today, and many more over the summer.

Search for a Formula

My first attempt to take a fresh approach to stock stats was HiMARQ, or historical monthly average return quotient analysis. (See the portfolio, in the "Fine Print" section below.) But for something new, in keeping with the baseball theme, I realized recently I would like to know how many times over a one- and three-year period an individual stock either rose or fell by 10%, 15% or more in a daily or a weekly period. After all, most of the time our stocks wander aimlessly, dribbling down 1% to 3%, only to advance 1% to 3% the next day. It's really those big days -- when we get walloped or fly -- that end up characterizing our feeling about volatility and risk.

To quantify this, I simply downloaded the daily and weekly closing prices of a small universe of stocks into an Excel spreadsheet. I then devised a macro that calculated the daily change of each stock in my spreadsheet, and made a separate table with formulas that group all that activity into eight buckets: Days of +/- 1%, +/- 5%, +/- 10% and +/- 15%. (I did the same for weeks over the prior three-year period in a separate spreadsheet).

Next, I created a simple linear expression (it could have been nonlinear, but I'll leave that for the statisticians among you to propose) for quantifying all these moves -- giving a stock one point for landing in the first bucket, two for the second bucket, three for the third and four for the fourth. I then added these and divided by the total number of days (or weeks), and

voila

, I had a figure that approximates baseball's slugging percentage on the upside and a "whiffing" percentage on the downside. I also created another table that pulls out each stock's five best and five worst days (or weeks) in the period.

I found that these figures helped me understand the differences in volatility between two stocks that look very similar on the surface in a clearer way than standard deviation and beta. Take the two big semiconductor makers,

Micron Technologies

(MU) - Get Report

and

Texas Instruments

(TXN) - Get Report

, for instance. The key figures, in my view, are these: Texas Instruments never had a gut-wrenching day of negative 15% performance, but it also only had a single day in which it was up more than 10%. In contrast, Micron had three days in which it fell 10% to 15%, but it also recorded eight days of 10%-to-15% increases and three days of 15%-plus jumps.

Overall, Micron recorded a slugging percentage of 0.782 vs. a whiffing percentage of 0.544, a slug-to-whiff ratio, or SWR, of 1.44. Texas Instruments recorded a slugging ratio of 0.547 and a whiffing percentage of 0.421 for a SWR of 1.29. That's pretty close, but the advantage goes to Micron for being more volatile in a

positive

direction. (The figures correlate well to the two stocks' beta in contrast to the

S&P 500

index -- a more standard measure. They were 1.54 and 1.41, respectively.) Now, when you calculate the average gain of the two stocks over that time -- 0.67% per day for Micron vs. 0.45% for Texas Instruments -- you have to conclude that Micron was reasonably easy to own over its period of outperformance vs. Texas Instruments, even though it was a bit more volatile. In general, an SWR greater than one is desirable, and the higher the better. The best way to use this metric may be using weekly data.

Fine Print

MSNBC Sports does a very nice job with a wide variety of baseball stats, including six different ways of understanding position players' batting and fielding performance. For some very creative statistics, check out

ESPN's

"

Misc. Batting" pages, which allow you to sort on such obscure stats as Offensive Winning Percentage, Grounded Into Double Play and Ground Ball /Fly Ball ratio.

Majorleaguebaseball.com has introduced the Stats Explorer, which allows you to chart players' stats month by month... Don't look now, you might jinx it, but our HiMARQ portfolio is finally showing signs of life. The nine stocks that show the most historical promise in the month of June are up 19% in aggregate through June 16, beating our S&P 500 index benchmark, which is up 3% in the period. Leading the charge are

Rambus

(RMBS) - Get Report

, up 89%;

MedImmune

(MEDI)

, up 35%;

Zoran

(ZRAN)

up 25% and

Advanced Fibre Communications

(AFCI)

, up 21%. We're now, umm, only down 26% for the year . . . To learn more about HiMARQ, visit

column 1 and

column 2.

At the time of publication, Jon Markman owned or controlled shares in the following equities named in this column or listed in the SuperModels portfolios: BroadVision, Cisco Systems, Digital Lightwave, Emulex, Kopin, Maxygen, Microsoft, Nokia, Nortel Networks, Oracle, Qualcomm, Siebel Systems, SDL, Superconductor Technologies, Veritas and Xcelera.com. Under no circumstances does the information in this column represent a recommendation to buy or sell stocks. He welcomes your feedback at

mctsc@microsoft.com.

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