As a research director on Bay Street I always sought analysts who had an artistic hobby. What I looked for was the ability to see a pattern, not just details. One of my top-ranked analysts played the piano; another played poker professionally (yes, it's an art); a third played chess. And it's from the latter that I learned of computerized chess programs - and how they paralleled modern investing methods.
Computers raised chess to such a high level that even world champion Garry Kasparov lost to one - IBM's Deep Blue. Did chess computers, then, reach a level that mere humans cannot attain? Nope. Joining that which he couldn't beat, Mr. Kasparov suggested humans team with computers to produce Advanced Chess, where each player can use a computer to analyze his moves as he plays. As a result, man-machine teams often rank higher than either human or computer can alone.
And as in Advanced Chess, so in the world of advanced investing: Some sophisticated investors now team with computers to produce results that neither can produce alone.
By computer investing I don't mean simply using computers to screen stocks for low price-to-earnings ratios or whatever - this was done 30 years ago. Rather, the modern use of computers, in both chess and investing, is more akin to the use of a battle computer in a supersonic fighter plane. The pilot can ask (and get answers for) complicated questions on the fly, in real time, so as to fight smarter and better. In Advanced Chess, "fighting better" means picking a set of better moves from which the grandmaster will choose the one he intuitively prefers; in advanced investing, it means producing a list of likely winners from which the investor can pick the best, via due diligence.
To make this clearer, let me first compare a chess move-picking program with a modern stock-sorting program; second, compare a real-time chess-move analyzer with a real-time due-diligence helper; and third, using the same real-time verification principles, mention a way to help your due diligence be more effective.
First, the picking and sorting process: In all chess-playing programs, there's an evaluation function (EF) that evaluates the current position based on a number of criteria. Things like material, mobility, king safety, centre control and so on. To pick superior moves, the computer compares the current EF with those of all future positions, which in turn depend on the opponent's future moves. The number of calculations can quickly mushroom, so the program "prunes" low EF moves. In this, even chess grandmasters cannot compete with computers. However, intuitive grandmasters may tactically accept a lower EF now, for a strategic gain later. That's how, by combining human intuition with computer rigour, Advanced Chess can improve the game of both.
Similarly, in modern computerized stock sorting, an EF uses things like value, earnings momentum, relative strength, insider buying and so on, to sort stocks in a database. The computer then produces a short list of stocks with the highest EF (or potential). A billion-dollar quantitative fund (which invests based on numbers alone) may simply buy this list; but it's best to prune it further via due diligence - and it is here where a man-machine partnership is most effective.
Say you are on the phone with a chief financial officer. "Yes," he says, "we did lose money last quarter, but it was mainly in Europe, where everyone in the industry lost money." You query your database as you listen, then say, "Well, of the 11 companies in the industry only yours lost money in Europe. The other 10 made a profit." After a short silence, the CFO says, "What I meant to say is, our inventory in Europe was high, so we got slammed on the currency." You click your keyboard again. "Well," you say, "your European inventory was the lowest in nine years…" And so on.
The idea here is to have instantaneous access to data which you can query smartly on the fly, so as to get the most out of your human sources. In my experience, this ability can improve your sleuthing effectiveness several-fold - just as using a chess-playing program to evaluate moves can improve your chess playing measurably.
But how can you use this principle on your own? After all, you don't have access to the databases and query tools that I, and others like me, do. Well, you can do this: Whenever you talk to management, always have the company's financial statements, and those of their competitors, on an interactive spreadsheet before you. Then, anything management tells you, check for veracity, logic, and impact, and use what you find to refine your questions. It's a simple but effective form of man-machine interaction that should help any investor improve his due diligence.
And a final note: Using EF sorting alone in computerized chess is a low-level method, and so is mere EF sorting in investing. The higher-level methods enable an investor to ask sharper questions, such as: Which industry today has the highest supply-demand imbalance, which the lowest? There are other questions too, but I'd rather not elaborate here, since money management is, after all, a competitive business.