:Can a stock have all your desired characteristics and stillbe too expensive?
Gillam: Yes. If a stock’s price-earnings ratio, on estimated earningsfor the next year, exceeds the projected growth rate, we won’t buyit.
Tanous:That’s very interesting as well as very fundamental. You’resaying that if the company is growing by 30% and the price-earningsis, say, 35 x earnings, you don’t buy it because the P/E exceeded thegrowth rate.
Gillam: Right. It might even be a sell signal. That’s why we soldIBM after we had a double. That’s why we sold Microsoft. That’s alsothe reason we don’t buy new issues - in our system we can’t assesstisk levels without a history of trading.
Tanous:What’s a good summary of your investment philosophy,Bob?
Gillam: An acceleration in the earnings growth rate will often leadto excess market returns. An example of this is McDonnell Douglas,a low risk stock where acceleration has worked magic. It was one ofour largest holdings last year. It had less risk than the market and agreat return. Why? Because McDonnell Douglas reinvented itself toreflect smaller military budgets. The company had been misunderstood.
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This company reported earnings above estimates for several quartersrecently. The result was a stock price that doubled in the last fivequarters. Earnings growth rates are everything. McKinley stocks reg-ularly beat the Street estimates. Excellent market results occur whenyour holdings perform above expectations.
Tanous:How does your investment theory work in a down marketwhen the market is not paying as much attention to earnings? Howdoes your philosophy pan out in a bear market?
Gillam: In down markets earnings acceleration is much less import-ant than capitalization. We try to keep our returns within the marketrange when markets decline.
Tanous:This sounds like a very disciplined investment philosophy.
Gillam: Exactly. Our disciplined structure led us to Cognos Inc.,one of my largest holdings. At the end of last year, this was a $40stock, now it’s almost $70. The four or five analysts that follow thiscompany have been between 10% and 30% low on earnings for thelast three reporting periods. Cognos has surprised us with good news.These were estimates for the first period of 1996 [Gillam shows mea list]. They reported $0.73; that’s three cents above the high estimate.Now, if you look carefully, they reported on the 10th of April, andthe stock was about 60. The stock ran from 60 to 69 on that news.Excess market returns. This is typical of a McKinley stock.
Tanous:The question is: How did you know that this stock wasgoing to report better earnings than the Street expected?
Gillam: The E rank, 1 to 99. If you’re 99, you’re near death. Youwant a company like Cognos, with an E rank of 4.
Tanous:Does 99 mean that it’s underperforming the estimates?
Gillam: It means a deceleration in the growth rate. Your productsmight be outdated, Somebody came up with a better gizmo than yours.Your technology is lagging. That sort of thing.
Tanous: What does a 50 mean?
Gillam: Fifty means you’re the median. It means that out of anynumber of stocks, say 100 in this case, there are 49 above you and49 below. What we would like is for all of our stocks to be up nearthe top. Here’s another one with a very high E rank, California Amp-lifier. In January [1996] the stock was 15. The stock is almost 40today. The median return is 4.25%...per week! I’ve got a six figureposition in that stock. As long as the company stays on track, we'll
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stay with it. Another great stock the last several quarters is C-Cube.Look at McAfee and Ascend. Great stocks.
Tanous: We talked to a few of people who own Ascend.
Gillam: We own a boat. A full boat is a full allocation. That means3% of my portfolio is in this stock. Here’s another one, CDN [CadenceDesign]. The high estimate was $0.38; it came in at $0.42. HBOC [HBO& Co., a health maintenance company, not the cable TV company]was a blowout! The high estimate was $0.39; it came in at $0.46. Itgap-traded up 14 points on the next trade. Our stocks do that. Here’sRaychem. The high estimate was $0.97, and we had a big run in it;it came in at $0.89. So we were wrong. Next trade: we’re out.
Tanous: That is certainly consistent with what you've told us.
Gillam: Earnings are everything. It’s not the growth of earnings,it’s the growth of the growth rate. So we have built a big computersystem here. We’ve got 21 employees and we've got 50 computersystems. Those satellite receivers you see on the roof are ours.
Tanous: You haven't fully answered my question about how all thisworks in down markets.
Gillam: Our objective in down markets is to do no worse than themarket. If the market pulls in 10% and we’re down 9% or 10%, pleasedon’t fire me. 1994 is a prime example. We were down 3.2%. TheS&P was actually down a little over 1%, if you take out dividends.So we were in the hunt. Now, if in a down market you are able to dono worse than the market, but in an up market you can do double ortriple or better, then it’s just a matter of time.
Tanous:Let’s talk about performance. Your numbers are amazing.For the last five calendar years, based on the numbers I have, yourcomposite was up over 31% per year net. That’s pretty impressive.What is your portfolio turnover?
Gillam: Sometimes low, sometimes not. For example, if you takeour top ten holdings at the end of 1995, at the end of March 1996,we owned all of them except one. But there are times when the marketrotates and leadership changes. We will be concentrated in the sevenor eight leading groups. When you get a change in one of the leadinggroups, we can have a huge turnover. For example, on November 7,1995, the semiconductor analyst at Merrill, who has been followingthe industry for years, had a conference call. During the call, he madethe comment that he thought that D-RAM chip prices would be down40% in the next one to five quarters. While he was speaking, we re-
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trieved the data on Micron from our computers and we discoveredthat the pre-tax net was 47%. So, let’s see, 47% minus 40% is...notvery much! Of my top seven stocks at that time, five were semicon-ductor stocks - LSI, Altera, etc. Before the call was over, I had soldevery single semiconductor stock we owned.
Tanous:That’s funny. When I was in Richard Driehaus’ [page7Aloffice, we were walking around the office and he decided to sellhis entire position in Altera.
Gillam: We sold 100% of our chip stocks in less than ten minutes.We were able to do it because of our internal system which we callBFG 9000 [don’t ask]. You know, some analyst comes up here and Iknow right off if they’re a prop head. In Alaska, if you’re a computerwhiz, you’re called a prop head. Down in Texas, you’re called a gearhead. It’s a language thing. When we get these people to come in hereand look at us, we know immediately if they’re prop heads. We showthem our trading system, the BFG 9000, and if they know what it is,they’re prop heads. If they don’t, they majored in English. All theprop heads know you have to have a system that allows you to moveon a dime. If you’re a mutual fund, you don’t need it. You only haveone account to manage, the fund. But if you run several thousandindividual accounts, like we do, it’s different. Our BFG 9000 allowsus to do that.
Tanous:Now, in the case of the D-RAM chips, which you just toldus about, a good part of your decision was related to your confidencein the analyst. I suppose that’s an important factor.
Gillam: We rate analysts on a scale of 1 to 5. If you’re a 1 analyst,and you change an estimate big time, up or down, I listen to you. Ifyou're a 5 analyst, you're just a freshman. You have no track record.But guys who can move the market, you pay attention to. I pay atten-tion.
Tanous:How are your accounts divided? When new clients comein, what style choices do they have?
Gillam: Our primary product, the one that made us famous, is ourgrowth equity style with what we call an “anything” capitalizationportfolio. We could have an IBM right next to a Cadence Design. Thestocks in the portfolio have an average capitalization of about $1.7billion. These are all separately managed accounts.
Tanous:That’s not that small. So you’re not buying really small
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companies, presumably because your screens require a minimumamount of market liquidity.
Gillam: Sure. We don’t buy anything below a market cap of $200million. And for the client who says I really want excess returns, butI want less volatility, we accommodate them, too. As I mentioned, aclient once asked us for a portfolio with a standard deviation aboutthe same as the S&P 500 with optimization above that. So we createdit. We run this for several large institutions.
Tanous:Can anybody have access to this?
Gillam: Anybody. That’s our mid- to large-cap portfolio, whichsome clients call the “Blue Chip” portfolio.
Tanous:So it’s not a small-cap product. What has the performancebeen like?
Gillam: It’s a mid- to large-cap portfolio. The average capitalizationis about $8 billion. It’s presently up 20%, after fees, for the first fivemonths of 1996. We use this identical style in the international mar-kets, which also beats the relative indexes by 75% or 80%. So wehave three portfolios: One is an “anything” cap, which has more riskthan the market; the second, the mid to large-cap, has the same riskas the market; and the international portfolio is the third.
Tanous:The “anything” cap, by definition, let’s you buy almostanything. How has it done?
Gillam: The “anything” cap, as I mentioned, is also our growthequity portfolio. Even though we can buy almost anything, we insiston liquidity. This portfolio is up 34% in the first five months. Thatcompares to 15% for the Russell 2000.
Tanous: Very impressive. How about your international portfolio?
Gillam: That’s up 17% this year, after fees. The EAFE [Europe,Australia, and Far East Index created by Morgan Stanley Capital In-ternational] benchmark is up around 4%.
Tanous: You also have a hedge fund, I believe.
Gillam: Yes. It’s called McKinley Select Partners, and we also havean off-shore version for foreign investors. The minimum in the do-mestic partnership is $500,000 and $2 million for the overseas version.It’s a partnership, so we can take a standard performance fee, and wecan also employ a short strategy. The fund is up 72% this year[through May 1996], before taking our performance fee.
Tanous:Sounds like you earned it! What is the total amount younow have under management?
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Gillam: About $750 million.
Tanous:How can a relatively small investor access you?
Gillam: One of our business areas is what we call the carriage trade- individual accounts, which a lot of firms won’t do. I do it becauseI get to meet exceptional people. So I like that business. But we havecertain requirements. The account has to be in a wrap fee environment,so that commission brokers don’t overcharge the clients. [So-calledwrap fees are offered by many of the larger brokerage firms. Theycombine, or “wrap,” all commission charges and manager compensa-tion in one annual fee, which can sometimes be as high as 3% of theamount invested.]
Tanous:But wrap fees can be pretty expensive too, you know.
Gillam: They are if the manager doesn’t trade, like value managers,who in my opinion trade much less often than someone like us. Thereason most people don’t achieve excess returns is that they’re lazywith the time they devote to their investments. If you take an hour-and-a-half train ride from Stamford down to the Street, think of thetransportation time. And are you going to go to the office on Saturdayto put in more time? No way. Notice that today is Saturday and ourstaff is here.
Tanous:Back to the minimums.
Gillam: We take certain wrap accounts at $150,000.
Tanous:Presumably, you have to go through a large brokerage firmto get that. Who do you deal with?
Gillam: Smith Barney, Piper Jaffray, Dain Bosworth, A. G. Edwards.We like firms with a low cost to the client. We also deal with commis-sion brokers, but only if they charge rock bottom commissions. Wedon’t want our performance penalized at the client’s expense by highcommissions. Our minimum institutional account is now $10 million.I remember when we were featured in Money magazine. The guy said,you'll now get 500 calls from 500 people who want to invest 500dollars! He was right.
Tanous:Before we conclude, I have to ask you about where you live.I just made my first trip ever to Alaska to meet with you. I’m here inyour offices, in the distance we can see Mount McKinley, which is180 miles away. That tells you something about the environmentaround here! Yet in this modern office, which is as high tech as any-thing I’ve seen, we’re here on a Saturday and you’ve got a lot of peopleworking.
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Gillam: Our staff usually gets in before 4 A.M. and they start run-ning the quant stuff. We sit around and talk strategy. The kind ofpeople who come here must have some frontier spirit. If the only waya person is going to be comfortable in his environment is riding asubway, he’s not going to make it here. Most of the people here livewithin 15 minutes of the office. I live on a lake, where I park my floatplane in my front yard. It’s ten minutes to the office. The king salmonwill start coming over the dam in the next ten days and I can standon my dock and catch king salmon. The market closes at noon. I gojump in my flying machine. It doesn’t get dark till 11:30 in the sum-mer. I can land on some lakes and rivers and fish and have a greattime. There are a lot of fun things to do here. | have more snow ma-chines than cars. There are virtually no taxes in Alaska. Why paystate taxes and high sales taxes if you don’t have to? We’re the samedistance to Tokyo as we are to London, which is great for an interna-tional player. Our specialty products, the hedge funds in particular,have big participations in Europe and Asia. We make money and wehave fun.
Tanous:It speaks to the technological advances in communicationsthat you can be here in Alaska and get exactly the same quality ofinformation on the same timely basis as somebody in New York City.
Gillam: When we started, we figured we were able to do it becauseof this new, incredibly fast computer called the 286! We originallybought six of them. They used to take 13 or 14 hours to do our quantruns. We now can run them in 35 minutes. Our pricing comes downvia satellite. We don’t use phone lines - they’re unreliable. It’s all partof our philosophy to generate excess market returns. Everyone hereis motivated by fear and greed. Those are the perfect reasons forsomeone hiring us. We’re not motivated by anything other than per-formance. I’ve never had an employee leave. Why? Because we paythem extraordinary amounts of money.
Tanous:What are your personal plans for the future?
Gillam: I’m going to be 50 in a couple of months. I intend to dothis for ten years. I will see to it that almost every one of my employ-ees gets rich, if they perform. If they get rich, I will have done prettywell for myself, too. There is nothing in the world that excites memore than coming to work and seeing that we beat the index yester-day, last week, last month, and last quarter - by 2 or 3:1 - for ourclients.
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I dare say that beating the index by 2 or 3:1 would excite me, too.And Bob Gillam has done it. His performance record proves thevalidity of his methods, although we haven't yet seen how he will doin a really sloppy market. Interesting that he comes right out and tellsyou that his goal is not absolute, but relative performance. If themarket is down 10% and he is down only 9%, he figures he’s doinghis job. That is a perfectly realistic approach, given his style.
Bob Gillam is clearly a product of his surroundings. Perched amidthe towering terrain of the Alaskan frontier, you might think of himas the John Templeton-of-the-North, although the pristine beachesof Nassau (where Templeton works) are definitely not hisstyle. Gillamis as rugged as the environment in which he grew up. His personalityis fully reflected in his style of investment management. I keep remem-bering Rex Sinquefield’s (page 257) admonition about this style ofinvesting: “Not for the faint-hearted.” Yes, indeed.
You may also have been struck by the stark contrast between thestyle of someone like Bob Gillam and other types of managers - valuemanagers, for example. You and I may see the benefit of both growthand value styles; Bob doesn’t want to hear about it. But his single-mindedness does underline the contrast between different styles andthe importance of considering style in your choice of investmentmanagers and funds. For those who seek excess returns and are com-fortable with his style, there are few, if any, better practitioners thanBob Gillam.
305DAVID E. SHAW
When you enter the offices of D. E. Shaw & Co., you immediatelyknow that you are not in a typical Wall Street firm. That’s perfectlyall right, since D. E. Shaw is the antithesis of what most of us expectof an investment firm. Bathed in secrecy, D. E. Shaw is spoken aboutin financial circles in whispers, as if the mere mention of the nameportends the discussion of classified material with its deep, darksecrets. Shaw’s name is little-known to the general public. But thefirm, and its founder, David Shaw, have acquired a growing reputationin financial circles as the king of the quants. Shaw is the smartest,most successful, and his firm is the most secretive of those that employhigher mathematics, and the most powerful computers, to create tradesand arbitrage situations that make good money.
I promised you that our interviews would not be with money man-agers who used exotic techniques that none of us could hope to emu-late, but rather with managers who buy stocks and make a great dealof money doing it. I also promised there would be one exception.David Shaw is that exception. D. E. Shaw’s offices are futuristic andstark, perhaps a harbinger of the future of money management. Thedress code appears to be jeans, polo shirt, and a Ph.D. in math. Theoffice space has been cited in Architectural Digest,and pictures of ithave been displayed at The Museum of Modern Art. The design ismeant to focus on the intersection of finance and technology.
Prior to meeting the firm’s founder, I took a tour with Trey Beck,Nick Gianakouros, and Marlene Jupiter. We visited what they call a“trading pod,” which perfectly resembles the control room of a NASAspace capsule. The press has reported that D. E. Shaw, on busy days,has accounted for as much as 5% of the trading volume on the NewYork Stock Exchange.
On another floor, a huge trading room, much like its Wall Streetcounterparts, houses dozens of young - dare I say?- rocket scientists.They work with proprietary software, designed in-house. The averageage of the staff appears to be under 30. Most of them have graduatedegrees in math and computer science. There are few, if any, MBAs.In a nutshell, the firm devises mathematical algorithms to createtrading opportunities based on inefficiencies in markets worldwide.INVESTMENT GURUS
Typically, the firm accounts for as much as 2% of the NYSE tradingvolume every day. The large number of trades results from Shaw’squantitative trading strategies which are designed to make tiny profitsconsistently, producing above average returns. How much exactly?It’s hard to tell, but Shaw’s investors wear big smiles. The estimatesrange from 20% to 30% a year.
Let’s take a journey into the future: meet David Shaw.
Tanous:How did you first get interested in stocks?
Shaw: I was curious about them when I was quite young. Mystepfather was a professor of finance at UCLA. He built part of hisreputation publishing papers that failed to find any evidence that itwas possible to beat the stock market! So I grew up with the randomwalk model [which holds that movements in stock prices cannot bepredicted] and the efficient market hypothesis. | still believe that, toa first approximation, those theories are largely true. At our firm, wemake our living by finding the rough edges in the efficient market,but it’s remarkable how hard it is to use new information to beat themarket. I grew up believing that there was probably no way to dowhat we now do, and there was a long period when I had nothing todo with any of this.
Tanous:I assume this was during your time in academia.
Shaw: That’s right. I was trained as a computer scientist, and stillteally think of myself as a computer scientist, as do many of thepeople here. I enjoy that tremendously. | finished my Ph.D. at Stanfordand was a professor at Columbia for a while, but was lured away byMorgan Stanley with two enticements. One was an economic one: Iwas able to make many, many times the salary I was making as aprofessor. I was thinking about having a family and knew I wouldneed some sort of net worth if | wanted to feed and educate my chil-dren.
The other lure was that they were claiming to be able to do some-thing that I had learned from my stepfather was probably impossible- to beat the market. That was a challenge. At first | was very skeptical.I asked a lot of questions of the people at Morgan Stanley, who wereclearly very smart. But I knew how easy it was to fall for a statisticalartifact and believe that you actually had something that workedwhen, in fact, you were just lucky. They managed to convince me,without telling me how they were doing it at that point, that therewas no question they really did have something that was working.
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Tanous:This isn’t the proverbial black box, is it?
Shaw: I can’t comment on anything that was done at MorganStanley, but our approach at D. E. Shaw & Co. is very different fromwhat’s sometimes referred to as the “black box” approach, for a par-ticular mathematical reason. If you just plow through enough data,as long as your model is rich enough - by which I mean that it hasenough parameters, enough different variables - you can always findpatterns in the data. But the vast majority of the time, those patternsaren’t useful. They are ones that don’t have any predictive value.That’s what’s called “over-fitting” the data. It’s the big problem thatmost amateurs at this run into. They get very excited; they thinkthey’ve discovered something; but, if they do it by simply siftingthrough a lot of historical data, the patterns they come up with aregenerally not useful for trading.
Tanous:Are you saying that they’re forcing the conclusion?
Shaw: That’s basically right. You’re in a situation where you willalways find something, whether it’s really there or not. The processof finding things that are real, that you can actually trade on, is un-fortunately very difficult and extremely expensive. It requires a hugeamount of research. We have done that through a scientific process- we formulate hypotheses about how the market works, and thentest them rigorously. The vast majority of our hypotheses turn out tobe false. Probably 90% of all the research we do leads nowhere.
Tanous:That’s fascinating. Can you identify what it is about the10% that works, that makes them work?
Shaw: Unfortunately not, or else we wouldn’t do the other 90%!That’s the reason we now have 350 employees around the world, andwhy, at the core, we are really a research organization. We have vir-tually no people here who study companies and decide whether theproducts that they make are good products, or whether the CEO is agood CEO, or whether the market they’re attacking is a good one, al-though those are all very important things. In fact, although I thinkin many ways we are a model for the future of a big part of WallStreet, it’s worth keeping in mind that, for much of what Wall Streetdoes now, not only are we not good at it, we don’t do it at all. I believethat many of those functions will always be important, like analystsstudying companies and understanding industries - there’s an import-ant reason for such activities. But in our case, with the exception ofthe computer industry and other information-related industries, which
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we have to understand very well, we have no expertise at all in thetraditional investment research area.
Our particular niche involves understanding the mathematics ofthe market. The service we provide is that we make the markets moreefficient and more liquid. Unfortunately for us, by doing that, we alsoreduce the number of profit opportunities for ourselves. That’s whywe can’t simply take what we’re doing now and scale up from ourpresent capital [about $800 million], and just take ten times as muchmoney, and make ten times more profit. It wouldn’t work.
Tanous:Is that because, after the first $800 million, efficiency comesback?
Shaw: That’s exactly right. We tend to make the markets efficientby making our profit as a low-cost producer of market efficiency.
Tanous:! want to go back to your 10% that works. I’m fascinatedby that. The efficient market hypothesis holds that whatever patternyou find has no predictive value.
Shaw: Right.
Tanous:So, you’re telling me that, that’s true most of the time, but,guess what? There are some patterns that we have been able to findthat do have predictive value. Is that what you’re saying?
Shaw: That is true, but they [the patterns with predictive value]are also generally very small. We trade in enormous volume. It’s beenaccurately reported in the press that on occasion we’ve accounted formore than 5% of all the New York Stock Exchange volume.
Tanous:That’s incredible.
Shaw: That does include our customer transactions as well astrading for our own account. It’s very large, but in many cases we’remaking unbelievably small profits, on average. In fact, in a givenstrategy, we might only make a profit 51 times out of 100; 49 timesout of 100 we lose. It’s like having a very, very tiny house advantagein an enormously large casino with a huge number of customers.
Tanous:Could you give me an example that most people would un-derstand of a “10%-type-thing” that works?
Shaw: I’ve been asked that before. First of all, even if we could,we probably wouldn’t describe it publicly, since we'd be giving outvery valuable proprietary information. But the fact is that almost allthe things we do are so complicated - and there’s a good reason forthat - that it would be very hard to encapsulate the basic idea suc-cinctly. The vast majority of all the straightforward, obvious, easily
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explainable things that even a highly-trained mathematician mighttry simply don’t work. That’s probably because people out there havealready taken advantage of the simple arbitrage opportunities. So, infact, most of what we do is difficult to describe, highly complex, andvery hard to find. We’ve spent many tens of millions of researchdollars to discover all the subtle things we now know about themarkets, and our job gets harder, and our results get more complex,every year.
Tanous:Tens of millions on research?
Shaw: It’s a very expensive proposition, and it’s not a one-timething.
If we were starting today, which we aren’t, I’m not sure we wouldeven go into this business, just because the barriers to entry wouldbe so high. When we started we could find a few effects that werebig enough for us to make a profit on, and that paid the bills whilewe went on and tried to find more. But at this point, none of thoseindividual effects are really that large. Typically, you have to have anumber of them to make a profit. Without a critical mass of researchresults you would actually lose money - a lot of it, and fairly quickly- after accounting for transaction costs.
Even with extremely low execution and clearing expenses, everytime you buy something you push the price up a little bit, and everytime you sell, you push the price down a bit. In our case, this effectis unusually small because we’ve done a huge amount of research onminimizing transaction costs and market impact. Nevertheless, evenwith our transaction costs - which we believe are probably the lowestin the industry in many of the world’s largest financial markets - ifwe found only one or two of these inefficiencies, they typically wouldbe too small for us to make money. They wouldn’t be as large as costsof making the transaction. So every time we might make a trade, we’dactually lose money. But if you have a number of inefficiencies andyou can find a way to combine them properly, in some cases, severalof the inefficiencies will all point in the same direction, and the sumof all of those inefficiencies will be greater than the transaction costs.
Tanous:But is that the principle? I mean, if you had to summarizemost of what you do, is that it?
Shaw: Yes. Most of what we do, with a few exceptions, does havethis characteristic. We'll typically be looking at 10 or 12 differentsources of inefficiency, each of which was monstrously difficult to
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find, and each of which is very small. Occasionally, they’ll combineand surpass our transaction costs. Even then, we’re just barely ableto break through the transaction cost barrier, do our trading, andmove on to the next set of inefficiencies.
Tanous:David, could you give me an example, using types of secur-ities, so that we can get an understanding of what a transaction mightbe?
Shaw: Well, that part is easy enough to describe. The vast majorityof our strategies are working in many of the instruments in a givencountry. So we might be trading in stocks, bonds, options, futures,warrants, convertible bonds - a large number of different instruments.Our technique is to look at all of them, all at once. There’s no ones