meant it. On an analytical basis,there was no question about it.
Tanous:You’re making it irresistible for me to ask you what youthink about buying equities in mid-1996?
Murray: In mid-1996, they are overvalued. The case is not as ex-treme as in 1987, but it’s only not as extreme because we do not havethe interest rate factor as strongly positioned as it was in 1987. In1987, I got every one of my pension asset management clients to cuttheir equity exposure by 20% to 25%.
Tanous:What would you do today?
Murray: Today, I would get back to the minimum part of your
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range. My typical pension fund range is 50% to 75% in equities. Youdon’t rebalance unless you cross 80%. But if that’s really your range,you ought to be down close to your minimum. Of course, my minimumis higher than most people’s.
Tanous:Some of our readers are going to want to know how youpick stocks. How do you do it for yourself, for example? What’s youradvice to others who aspire to wealth through common stocks?
Murray: Do intensive analytical work on a limited number ofcompanies, where you have an opportunity to get a real good under-standing of what decisions are being made, and what is going on inthose companies. That’s why I have never owned a lot of stocks inmy portfolio. I would rather have, and I will get better results, froma dozen companies that I really understand, and that I know wellenough so that I can make an informed decision on whether I shouldcontinue to own those companies. That affords me a basis on whichto judge the quality of the important decisions that managementmakes from time to time in a variety of circumstances.
Tanous:I think that is sound advice. I really get upset at those booksthat purport to tell you how to beat the market without mentioningthe hard work you have to put in to do it.
Murray: One thing I’m sure of is that, in the market, there is nosuch thing as a free lunch - as Milton Friedman always says. As theold saying goes, you build your wealth the old-fashioned way, youearn it.
Tanous:One last question, Professor. Some people might find itsurprising that someone who witnessed first hand the 1929 crash andlived through the Great Depression, would emerge so bullish onequities.
Murray: The answer is, if you went through that period and youwere, as I was, an MBA and a Ph.D. candidate, immersed in thosefinancial markets and in the economic environment, after you hadbeen through that, the kinds of worries and concerns that baffled in-vestors and market-makers in the ’50s, ’60s, ’70s, ’80s, and ’90s aretrivial.
Tam certain Roger Murray is right about that. It is interesting indeedto hear an investment perspective that covers not just a decade ortwo, but every important period in the history of the American equitymarkets. To have that perspective, from the viewpoint of someonewho worked on Wall Street and subsequently became a well-known
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academic, is truly invaluable. I enjoy conjuring up mental images ofyoung Roger Murray and his colleagues, Ben Graham and Dave Dodd,teaching security analysis to thousands of eager students. And whatwas that fellow Warren Buffett thinking about in class?
Let’s take a quick look at the main points. Professor Murray givesus a different viewpoint from the other academics with whom wespoke. He doesn’t believe in efficient markets, at least not perfectlyefficient markets. Did you catch the difference between market valueand intrinsic value? Graham and Dodd, and Murray, seek the intrins-icvalue of the company as a business by poring over financial dataand applying ratios. Is all that intrinsic value reflected in the priceof the stock at all times? Murray doesn’t think so, and neither do anyof the value managers we talked to. Of course they don’t. Their raisond’étre is finding undervalued securities.
l also found the notion of redoing the financial statistics - ina waythat is not designed to put the best foot forward - interesting. That,presumably, is what you and I are supposed to do as part of our fin-ancial analysis. And financial analysis is how we attempt to discoverthose undervalued stocks.
That leads us to his investment advice. Are you inclined to listento hot tips and great stories? Then you would be better off, as ProfessorMurray suggested, buying a combination of index funds and stayingout of trouble. That’s the easy way and, incidentally, with that advicehe joins with our efficient market theorists, who don’t think you canbeat the market in any case. Are you prepared to do all the work ne-cessary to make an informed investment decision? Then go for it! Butdon’t forget to do all the work. Good advice, Professor. And by theway, isn’t that what Peter Lynch told us to do?
287ROBERT B. GILLAM
Bob Gillam is a very successful money manager in a most unlikelyplace: Anchorage, Alaska. His firm, McKinley Capital Management,Inc., was started in 1988. Gillam actively manages investment port-folios incorporating modern portfolio theory, with quantitative com-puter models. Alaska is awesome by any standards. Bob Gillam, alifelong resident, will tell us about this State, which is more thantwice as big as Texas. I visited in early summer, when the weather isnear perfect and the scenery beautiful beyond description. Alaskansare rugged people, and proud of it. My hotel resembled a huntinglodge complete with intimidating stuffed bears - which looked 20 feettall. In fact, it seems like almost every public place in Anchorage hasa trophy bear. I vividly recall trying to sleep at 10:30 P.M. ANDHAVING TO CLOSE THE CURTAINS IN MY ROOM TO KEEP THESUN FROM STREAMING IN. SUCH IS SUMMER IN ALASKA.
Gillam’s success is not only a testimony to his intelligence and skill,but also to the dizzying advances in communications and electronics.After earning his B.S. in economics from Wharton, he received hisM.B.A. from the Graduate School of Business at UCLA. He startedmanaging individual and institutional accounts in 1970. Sitting inAnchorage, he gets information as fast as anyone on Wall Street. Heneeds to. His style is a combination of both quantitative analysis andmomentum. Both judgment and instant reactions are the keys to suc-cess.
Gillam’s performance record proves that he is doing somethingright. For the 12 months ended June 30, 1996, his portfolios wereup 42%. For the trailing 6 years ended June 30, 1996, his clientsenjoyed annualized returns of 31%. Let’s find out how he does it.
Tanous:How did you first get interested in stocks?
Gillam: I’ve been interested in the stock market since my earliestmemory, probably going back to when I was 12 or 13 years old. Istarted looking at the financial page, which at that time, here inAlaska, was a week old. I was fascinated by stocks. My fascinationwith stocks is even stronger today.
Tanous: You grew up in Alaska?
Gillam: My father was fortunate enough to come here just beforeINVESTMENT GURUS
the start of World War II. He came here on an adventure. When thewar started, the War Department found out that he had been a WestPoint cadet. That was it. They drafted him on the spot and put himin charge of freight coming into Alaska. The freight was transshippedto Kbarask, in Russia. The U.S. supported the Soviets by shipping warmaterial through Alaska. We put it on the Alaska railroad and shippedit to Fairbanks. From there, the cargo was loaded onto DC 3s, whichmade over 25,000 flights to Russia, then onto the Trans SiberianRailroad and across to the front with Germany. After the war, myfather stayed here. That’s how our family ended up here.
Tanous:So, you were born here.
Gillam: Yes, I was.
Tanous: Your company, McKinley Capital, has a phenomenal record,which we'll get to in a minute. One thing I noticed in looking at yourstyle, is that you don’t fit neatly into nice style boxes - value, orgrowth, and so forth, the way most managers do. How do you describeyour style?
Gillam: First of all, the people who designed the styles,value/growth, large/small, apparently didn’t know much about themarket. We are in the business of finding the stocks that go up. Weare not in the business of fitting ourselves into a category. Our busi-ness is generating excess market returns with controlled market risk.It doesn’t matter to us whether it’s a $300 million stock or a $30 bil-lion stock. It’s irrelevant. My client doesn’t call me at the end of theyear and ask: Tell me how you beat the index? Did you buy small-cap or large-cap? Value or growth? It doesn’t matter to them. We area value manager when that’s the thing to do, we’re a growth managerwhen that’s the thing to do, same for large-cap and small-cap.
Tanous:So you’re not what we call style-specific.
Gillam: Absolutely not.
Tanous:In that case, let’s find out how you do it. Let’s talk aboutmethodology. Since whatever it is you do transcends specific styles,what common elements allow you to make money in all these differentcategories?
Gillam: First, we look at the market as a whole. We let the marketlead us. At any time the market will reward certain industrial groupswith “excess” returns. We invest in market leadership. Our databasecontains 13,000 stocks from which we choose our portfolios. Eachweek, every Saturday, we rerun the numbers on the entire universe
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of stocks. For every security in the universe, we calculate an alphavalue [a measure of excess return] and a risk value, which are twovery important numbers to us. Remember, there’s nothing we can doabout the stock market’s moves up or down.
Tanous:Do you also use something like the Sharpe ratio?
Gillam: Not exactly. Our alpha is a straight linear alpha. We use abase index which could be the S&P 500, the Over-the-Counter Com-posite, it doesn’t really matter as long as the base is constant for theentire regression. When we come up with a stock’s alpha value, wecompare it to all other alphas in the universe. We want alphas of ourstocks to be in the top 6% or 7% of the continuous universe - a veryselect group of stocks. Assume that the S&P 500 has been going upat one percent a week. If your company has an alpha of one, thatmeans that you’ve been going up at two percent a week.
Remember, there’s nothing we can do about the stock market’s upsand downs. What we can do, however, is buy the stocks that havepositive alphas. People who buy companies that have a big negativealpha [meaning they have been returning less than the market] mightas well believe in the tooth fairy. You are trying to buy somethingcheap. But there is nothing cheap in the market. Nothing! The marketknows! We never bottom fish.
Tanous:!I suppose the next thing you’re going to tell me is that youare an efficient market theorist.
Gillam: No. There are inefficiencies in the market every day. Ourexperience suggests that about 9% of the universe is inefficientlypriced on any given day. There is a series of studies I used when I didgraduate work at UCLA that dealt with stocks which make new highsand with those making new lows. This has now been popularized inAmerica as “momentum investing.” My research at the time showedthat, if your stock makes a new high on any given day, the probabilityexceeds 70% that it will make yet another new high in the next 90days. That was true then, and it’s true today. What was also true, atthe time, was that, if your stock made a new low, the probabilitiesexceeded 65% that it would make another new low in the next 90days.
Tanous:That’s momentum investing, all right.
Gillam: Exactly. So clearly, all you have to do is buy the new highs,right? The trouble with that approach is that, at the end of the year,you've got hundreds of stocks that you own long, and hundreds that
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you shorted, and you have no way of getting out, because there isno sell signal for any of them. The second problem with this approachis that it doesn’t tell you why highs breed highs and lows breed lows.But the fact is that they do.
What that really means is that excellence breeds excellence. Here’show we get to it. Assume we know that the alpha value of a marketindex is zero [by definition]. We wish to own those sectors and stocksthat are now demonstrating superior performance. We'll relate theoutperformance to real earnings later. Why don’t we divide the market,so that we can figure out which stocks have a positive return, abovethe index? It doesn’t matter how much the index is up or even if it’sflat. Remember, our objective is to earn excess market returns. Themarket might be down 20%. If I’m down 10%, that’s excess return -because we beat the index. On a relative basis, we did better usingour long style only. Our hedge fund, however, seeks absolute returns,and that’s not the same. [A hedge fund shorts stocks as well as buyingstocks and holding them. Hedge funds are generally considered aggress-ive.] But for most of the money we manage, we try to develop a returnabove an index.
So, start with the companies that have positive alphas above thedesired index. It turns out that the stocks that have a positive alpha[above the market] comprise only 20% of all the stocks in the universe.Some 15% - 20% of stocks will earn all of the excess returns aftercommission and fees! We run the data every Saturday to stay currentwith the tides of the market. Now, what you really want to have is astock that is making more money than the market. But someone willsay, gee, I don’t want to buy it because it just made a new high. Well,the typical stock that we owned in our portfolio in 1995 made 50new highs over the year. So, if the first time it made a new high yousaid, gee, I don’t want to buy that because it’s too high, you missedthe next 49 new highs.
Tanous:Are we back to talking about momentum investing?
Gillam: You could call it momentum investing, but we have gonefurther and have discovered and explained mathematically whycompanies make successive new highs. We think that, more oftenthan not, companies whose share price is doing well [versus an index]exhibit a common trait with other stocks that are also doing well;namely, the earnings growth rate is expanding. We've discovered, webelieve, that excess market returns occur in a stock for somewhere
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between one and five quarters. Market inefficiencies never last. Themarket does catch up. Let’s assume that we can calculate a markettisk number for every single security. If we can do it, we could thenoptimize the risk/reward ratio. We calculate risk by taking the standarddeviation of the string of returns [for each stock] over the time peri-odicity.
Tanous:Hold it, Bob. We’ve got to get back to speaking English.
Gillam: It’s not as hard as it sounds. What we do is calculate a risknumber, which is based on the standard deviation of a string of re-turns. Look at this list. [We pore over a computer run of alphas.] Thiscolumn shows the stocks that have an alpha of, say, 2 or better. Theseare the stocks you want to own.
Tanous:So this list represents most of the market?
Gillam: Right. You don’t buy something that has an alpha of zero.Why not? Because by the time you get through with commissions,spreads, and inefficiencies, you wind up with a return less than themarket. That’s not our business. [Gillam points to another set of stocksthat have alphas close to zero.] So, what this means is that you don’tbuy these.
Tanous:So this is a distribution of returns, and you’re saying youwant to buy the outliers, which are the star performers.
Gillam: Yes. But the return, in and of itself, is not enough. Supposeyou have an alpha of, say, two. It only means something when it isrelated to everything else. Now, you could just buy the high alphas.There are fellows who do that. They’re called momentum investors.
But here’s what you really should be doing, in my opinion. Takean alpha value of two, which is desirable. Ideally, we also would liketo have risk below the market’s. I was sitting in Denver a number ofyears ago, looking at managers because I had a hand in the managedmoney department of Boettcher and Company. We had managerswhose performance was all over the chart. We would look at theirrisk and return, and we’d hire the manager with the right character-istics for the particular client.
What we do at McKinley is look for the stocks whose risk/rewardcharacteristics are optimized, based on our guidelines. Our formulacalculates not the theoretical risk, but the actual market risk of aspecific security compared to all other securities. [Risk is often calcu-lated using standard deviation, or the volatility of the stock comparedto the volatility of the market.]
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Tanous:! think what you’re doing, is segregating and identifyingthe high alpha stocks with lower risk from all the others. That givesyou potentially higher market returns with acceptable risk.
Gillam: That’s almost right. We can use our understanding of riskto optimize return at a given risk level. Two years ago one of ourclients asked us to create a portfolio with a risk characteristic similarto, and no more than, the S&P 500, but earning a higher net return.We did that by identifying the market risk, holding it as a constant,and optimizing alpha. We’ve been able to earn 50% or so more thanthe index, with similar risk to the market.
For the first five months of 1996, our large-cap portfolios are up19% to 20% versus the Russell 1000, which is up 9.8% or so. In ouraggressive portfolio style, where we buy small and large-cap stocks,we're up about 35%, while the Russell 2000 has gained about 15%for the same period. In fact, our aggressive equity portfolio has aver-aged twice the index return over the last six years or so, after feesand commissions.
Tanous:That’s extraordinary. Is this unhedged?
Gillam: Unhedged. Straight long.
Tanous:If we use standard deviation as a measure of risk, it seemsto me your standard deviation is about three times that of the market.
Gillam: Not true. The fact is, we run several different styles. Mymid- and large-cap portfolio is designed to have a standard deviationabout the same as the market. And it does, we think. In our aggressivegrowth equity style, the one you have the numbers on, we calculateour standard deviation a little differently than others do. The priceyou pay for “excess returns,” however, is occasional excess volatility.
Tanous:Let’s summarize before we go on. You’re saying that thealpha is the excess return of that particular security compared to anindex.
Gillam: Could be any index, as long as you are consistent. Whatwe want is relative alpha value. The alpha and the standard deviation,combined as a fraction, create what we call the OR index. It’s ameasure of the risk and reward. What McKinley requires is that thealpha value be positive, and for every additional measure of risk weassume, we demand more return.
Some people look at stocks differently. They might say, I’m goingto be a value investor. I’m going to buy this particular stock becauseits book-to-price ratio is high, or it has a large cash flow. A correlation
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analysis of this approach shows little relation to stock performance.Think about it. The fellows who buy value, what do they believe in?You might say it’s book-to-price.
Tanous:That’s fairly classic.
Gillam: Okay. Others say value is cash flow per share. My point isthat there is no definition of value. If the stocks that have low price-to-book ratios do outperform over time, by definition, they will bethe stocks that have positive alpha values. We would own them atthat time, and not before.
Tanous: There is a definition of value stock. It’s high book value tomarket value.
Gillam: That’s not true. I know guys who say that value has to dowith cash flow per share. I’m a value investor. Every value investorI have ever known has different views of what value is. The ultimatevalue is to optimize the equation of alpha versus risk. We’re in thebusiness of excess returns. We’re not in the excuse business. We arenot going to try and excuse poor performance by saying that our“style” is now out of favor.
Tanous:Let’s go back to excess returns.
Gillam: Once we do our analysis of the 13,000 companies in ourdatabase, we screen out the top 5%, say 650 or 700 stocks that exhibitthe highest OR score, or risk-reward ratio. These stocks are often inef-ficiently priced because the earnings growth rates are accelerating,which creates a lag between market expectations and earnings per-formance. The next question is, why do these companies typicallyhave excess retums for one to five quarters?
Tanous:That’s the question.
Gillam: It’s taken me 20 years to get the answer.
Tanous:Okay. What’s the answer?
Gillam: The answer is that these companies have a positive valuefor the second derivative of the earnings growth rate.
Tanous:Hold it right there. I just heard the sound of ten thousandof my books slamming shut. We have just lost all the readers, includingme.
Gillam: Okay. Let me explain it this way. If a company has earningsgrowing each year by 15%, and has had such growth for years, thenthe market’s level of uncertainty is very low; everybody knows! Whatif the growth rate itself is growing? Then, not everyone knows, and,indeed, uncertainty is high. When earnings growth exceeds market
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expectations, excess returns often occur as the market adjusts to thenew reality, usually very quickly. The typical performance ofMcKinley stocks during earnings [announcement] seasons, four timesa year, is such that almost two-thirds of our holdings report earningsabove the highest earnings estimate on the Street, and much higherthan the mean estimate. Those stocks are inefficiently priced!
Tanous:That’s a lot better.
Gillam: It doesn’t have to be some Silicon Valley stock. Supposeyou had a company that, five years ago, grew earnings 3%; four yearsago they were growing at 6%; three years ago, 11%; two years ago,14%; and now it’s 22%. That is acceleration of the growth rate, abetter circumstance than a company whose earnings are up a constant15% a year. In the latter circumstance, the market knows and expects15% and the stock is priced to anticipate 15%. It’s in the first casethat you have the opportunity for excess returns. It’s not the growthin earnings. It’s the growth of the growth rate of earnings. We wantcompanies where the rate of growth is intensifying.
Tanous:Even so, some of these companies won’t always do well.Some will have problems and their stocks will do badly. How do youidentify those, or don’t you?
Gillam: The most important thing about making money in the stockmarket is to realize that you’re hunting with a shotgun. That meansyou'll have outliers. If you’re wrong, you’re wrong. So we sell imme-diately if our expectations are incorrect. We follow the dead-cat-bounce rule.
Tanous:Excuse me?
Gillam: The dead-cat-bounce rule. If a cat jumps off the top floorof a skyscraper, when it hits the pavement, it will bounce a little bit,and on that first bounce we sell. We’re out. If you’re wrong, get out.If we buy a stock at 50 and something goes wrong and the next tradeis at 33, the first trade at 33 is me. I’m out. The price you pay forholding a loser is that you allow the loser to occupy a spot in theportfolio that could otherwise be occupied by a winner! Selling ismuch harder than buying.
Tanous:We haven’t talked about fundamentals in this process.
Gillam: There are a lot of fundamentals. After we have done therisk/reward work, the second thing we do is balance sheet integrityanalysis. We do not want any embarrassing events for our clients.Remember, we narrowed our search from 13,000 to 650 companies
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based on a risk/reward analysis. Our next set of screens narrow thepotential portfolio picks even further. We don’t buy anything below$10 a share. We don’t buy anything unless it trades a minimum of50,000 share a day. These two screens eliminate a lot of little compan-ies that don’t trade very much. Next, we look at the balance sheet.We have a maximum leverage allowed on the balance sheet, depend-ing on the specific industry. Steel stocks have a different numberthan, say, communications stocks.
Tanous:So you do classic balance sheet analysis.
Gillam: Yes. We use our company designed screens to do thisanalysis quickly. We do it every week. Red flags can appear abruptly.If we own it and the numbers change, we sell it. We look at the quickratio to be sure a company has enough cash to pay its bills. [The quickratio, or acid test ratio, is: current assets, excluding inventory, dividedby current liabilities.] The definition of corporate bankruptcy is notzero net worth, it’s that you don’t have the cash to pay the bills whenthey’re due. Two-thirds of our 650 stocks will be eliminated by thebalance sheet, liquidity and pricing tests. There are only three rulesthat count: safety, liquidity, and rate of return. Is there anything else?
Tanous:How about what the company does?
Gillam: It doesn’t matter, as long as the business is legitimate! Itcould be hula hoops, widgets, or steel bars. It doesn’t matter. We willnot, however, put more than 20% of our clients’ money in any onesector. We do know what they do, and we follow the research of everyanalyst that follows the company. Our quantitative data ranks everystock’s earnings acceleration and growth rate, on a scale of 1 to 99.That’s our E rank [E is for earnings]. We rank growth rate accelerationfor deceleration] into a 1 to 99 grid. These rankings are recompileddaily from data garnered around the world by our computer system.An E ranking of 1 means that your earnings growth rate is acceleratingmore than 99% of all stocks in our universe. It’s a comparative value,not an absolute value. All of our holdings must be in the top 20thpercentile, or better, to be included in one of our portfolios.
Tanous: You track earnings estimates, presumably.
Gillam: We try to use all the data services that provide earningsintelligence.
Tanous:! presume that if earnings come in above the estimate,you've got to be pretty quick to take advantage of that.
Gillam: Actually, we try to own stocks before good earnings are
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reported. That’s the trick. Some of the data services such as I.B.E.S.[Institutional Brokers’ Earnings System] track the pre-earnings an-nouncement chatter. They have a database of pre-announcement in-formation that we use with our other quantitative systems. The theoryis that, if a company is going to put a spin on a bad number, it doesit as early as it can. So, for a number of days before a company actu-ally reports, we do a ratio of the percentage change [in estimates]over the number of days. Then we can assign a probability that thecompany is going to hit the expected earnings number or go over orunder the expectation.
Tanous:! see. Some talk about earnings revisions long before theactual announcement might be a harbinger of bad news. Who preparesthat?
Gillam: LB.E.S. and others. We blend all the sources into our finalranking. Market intelligence comes from many, many sources thesedays.
Tanous:What’s an example of a pre-announcement?
Gillam: Say the company announces a charge in the first quarterof $6 million. IB.E.S. puts it in the database, and we adjust theearnings estimate immediately. But we do it intelligently. Supposethe company had a terrific quarter and was going to earn, say, $0.30.As a result of the charge, their earnings might now be down $0.06,but that was only a one-time charge. The quarter was actually verygood. The prior quarter was $0.20 and the Street was looking for$0.24 this quarter, but they did $0.30! It’s very important to knowthat. Sometimes the Street is fooled by looking at a reported numberand doesn’t look behind the number. You've got to keep your data-bases current if you expect to outperform. We try to follow everyanalyst live.
Tanous:From Alaska?
Gillam: Right. The proper use of technology today is to gather vastquantities of data from every spot on the globe and distill it quicklyinto usable buy and sell decisions. Communications systems knowno geographic boundary. McKinley portfolios regularly own the su-perior stocks in the leading groups; technology keeps it that way. It’snot, what we think is going to happen. It is what is actually happen-ing. We are in the reality business. Technology keeps us informedand realistic. While a guru may forecast future events, we try to bepragmatic about what is happening now.
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Tanous:Tell me more about your E rank system of 1 to 99.
Gillam: There are five sub-components of the score. It’s not onlyearnings, it’s the quality, the size, and the speed of change. The SUEindex [Standard Unexpected Earnings] is an important subset of theE rank. We give you a score much like Value Line does, only theirsis 1 to 5 and ours is 1 to 99. If we give you a score of 10, it meansthat, based on all of the numbers and comparisons we are looking at,your company’s earnings growth rate is accelerating and that acceler-ation exceeds that of 90% of the universe. That stock would be a de-sirable holding if it meets all our other screens.
Tanous:This sounds a lot like momentum investing.
Gillam: It’s not. Momentum is stock price. We’re talking about ac-celerating growth rates. We will also go through the Graham andDodd methodology - the balance sheet and liquidity tests - and it’sall very important. We pay attention to leverage, and quality ofearnings. If a company has too much leverage on the balance sheet,we drop it from consideration. Leverage creates bankruptcies. Ourstocks all have a ranking of earnings growth rate of 1 to 99.
Tanous