Ahead of the Curve (14 page)

For the first twenty minutes of each class, I would know where we were. I could feel the outline of the problem we were trying to solve. But then the chalk began to scratch on the board and the ground vanished beneath my feet. It was late October, though you would never know it from our windowless classroom. The air was heavy with concentration, bafflement, and the faint stench of scrambled eggs, brought to class each day by a student who had recently gone on the Hay diet—no carbohydrates, lots of protein. He sat in the next-to-last row cheerily digging into his breakfast with a plastic fork, oblivious to the nauseating effect he was having on others.

Finally, a Scottish doctor in the front row put up his hand. “I’m sorry, but what is OCRA?”

“It’s the optimal combination of risky assets.”

“So it’s not a vegetable, then.”

Ruback screwed up his face. “No. I should have explained. It’s the point where you get the maximum benefit from diversification. You have diversified enough to minimize risk for this level of reward, but not diversified so much that you are actually getting less than you should.”

Before studying finance, I had thought about investments almost solely in terms of reward. I had some idea that the index funds I owned at Vanguard were tied pretty closely to the fortunes of the broader U.S. economy. If the United States did well, I did well; if not, I suffered. But as long as I remained roughly in place, I was getting all I wanted for very little investment of my time. What I did not realize was that serious investors think as much about risk as they do reward. Whereas reward can be expressed in a simple percentage, risk is a far more slippery creature, making it the preserve of specialists.

During the first few finance classes, we had been working our way toward predicting the future cash flows of a business. Like any kind of prediction, this was a process of educated guesswork. You began with a company’s historical revenues and tried to project them forward. If they had been growing at 10 percent a year for five years, perhaps they would have a couple of years of this kind of growth before settling down to grow along with the rest of the economy. If the company planned to acquire a rival, however, or launch a revolutionary new product, those revenues could be much higher. The key was to make reasonable assumptions for a reasonable period into the future, normally five to ten years. The next step was to predict costs. Would they rise in lockstep with revenue? Perhaps they might fall as a percentage of revenue if the company became more efficient. Would revenue growth require some additional investment, a new factory, perhaps, in five years’ time? Would tax rates change or stay the same? Once again, the most important thing was to make sound assumptions based on all the available evidence. Then it was simply a question of putting the numbers into a spreadsheet—“plug and chug” as the bankers called it.

At this point you had, say, ten years of predicted profits or losses for your company. But these values applied to the future. What was all that cash worth now? We started with the idea that a dollar today is worth more than a dollar in a year’s time. If I had a dollar today, I could buy a one-year Treasury bill promising 5 percent interest, and have a dollar plus five cents in one year. Whereas the dollar in a year is just a dollar. And if I wanted a dollar in a year, I could buy 95.2 cents’ worth of T-bills and earn 5 percent while having those 4.8 cents to spend. A similar logic applies to figuring out the present value of a firm’s future cash flows.

In the case of the T-bill, we could simply take the promised cash flows in future years and discount them back by 5 percent. The dollar in a year’s time is worth 95.2 cents today. We can do this because a T-bill is considered a risk-free investment, since your counter-party is the U.S. government. That 5 percent is the rate at which people are happy to lend money to the government, and it tends to be the lowest lending rate around because no one expects the government to default. A company, however, can expect investors to demand higher returns to compensate for the risk of their business. And the riskier the business, the higher those expected returns will be. General Electric, with its long history and portfolio of diverse businesses, will be able to attract investors with the promise of lower returns than a single business start-up, say, a wallpaper company. The next stage in valuation was to figure out what kind of return was expected by investors in a firm, lenders and equity holders combined. If you were an investor, you would call this your opportunity cost of capital, the return on the best alternative to this investment, which you were forgoing to make this one. If you were management, it would be your hurdle rate, the minimum return you would expect on any investment you made. If you were an investment banker valuing the company, it would be the discount rate, the number you used to discount the company’s future cash flows to see how much they were worth today. Whatever you called it, it would be the same number. And calculating it forced us to think seriously about risk, asking the questions for company after company: What are the risks to its future cash flows and how does this affect how I value it and the decisions management should take?

Each of us has an intuitive sense of risk and of the nature of the risks we are likely to take for a given reward. Someone placing ten dollars on an outsider in the Kentucky Derby is probably doing so on the off chance of winning, but is reaping additional rewards from the excitement of having a stake in the race. Others are comfortable with the odds of throwing themselves off a bridge attached to a bungee cord. People in dire straits are inclined to take bigger risks for bigger rewards than those in comfortable situations, whose main goal tends to be preserving what they have.

When I bought my first apartment in London, with a friend who had recently graduated with an MBA from INSEAD, he drew up this elaborate spreadsheet showing the opportunity cost of investing in an apartment rather than stocks.

“What,” I said, jabbing at his laptop screen, “is an opportunity cost?”

He explained how illiquid an apartment was and how much easier it would be to trade in and out of other investments. He told me that part of the reason ordinary savings accounts offered such minuscule returns was that they were highly liquid. If you tied up your money for a long period, you should expect higher returns. The downside, of course, was that you could not get to it so easily if you needed it. Part of the difference in returns could be explained by the fact that a long-term, illiquid investment denied you certain other investment opportunities. And you should expect to be rewarded for that. I listened patiently, but couldn’t help but feel that all of this was make-believe. Intuitively, I could not grasp the idea of an opportunity cost. It seemed that you made decisions in life, some worked, some didn’t, but the idea that you would ever try to put a sum on the price of making one decision rather than another seemed fantastical. I told him that all I wanted was a place of my own that I could afford and that no bank was offering to lend me a hundred thousand pounds to buy stocks.

He tried to put it another way. Say you had a choice of two parties to go to on a Saturday night. You chose the wrong one and missed out on meeting the person who could have changed your life. The opportunity cost of not going to the other party was enormous. Risk, he said, was not just the possibility of something bad happening, but also the chance of something good not happening. First understanding and then pricing this kind of risk did not come easily.

Fortunately, we have a wonderful window into humans’ appetite for financial risk: the stock market. The market provides decades’ worth of data showing how the prices of companies in every field of business move in relation to one another. We can see, for example, not just how a single telecom company has performed but also how the broader telecom sector has performed. We can track the market, the entire portfolio of listed stocks, and then see how companies and sectors performed in relation to it. If the market was up, for example, were telecoms up at the same rate, or at a higher rate? Or were they down? Some companies tend to outpace a rising market, such as luxury goods, and some perform poorly in good times but soar when the rest of the economy sours, such as debt collection. Divining the patterns in all this data gives us a pretty good idea of people’s perception of risk.

By this winding route, I found myself face to face with beta. Beta is a nifty way of describing the risk of a stock. A beta of 1 implies that the stock, on average, tracks the market perfectly. If the market goes up 8 percent, the stock goes up 8 percent. A high-beta stock is one that exaggerates the market’s movements. Say the market goes up 10 percent; a stock with a beta of 1.5 goes up 15 percent. If the market falls by 10 percent, that stock falls by 15 percent. A low-beta stock is less volatile than the market. If the market goes up 10 percent, a stock with a beta of 0.5 goes up only 5 percent. If the market goes down 10 percent, the stock goes down 5 percent. It is less risky, and consequently less rewarding. Calculating a company’s discount rate became a process of using historical data to figure out a company’s beta—if it was not a listed company, you could draw on the data from similar companies—and then multiplying it by the risk of investing in the stock market as a whole. You then combined this risk to the equity holders in a company with the risk to debt holders to reach a discount rate.

Once we had discovered beta, people began bandying it around in every context. They referred to themselves as high or low beta, risk-takers or risk-avoiders. Presented with a new and dubious choice in the cafeteria, they might say “that grouper is a high-beta fish dish.” Or if they saw someone driving a boring secondhand Toyota, as I did, they observed that my car was a low-beta automobile. Low risk and definitely low reward. Once my class found itself looking for work, jobs were defined as low-beta (consulting) or high-beta (your own start-up).

The problem with such a handy little way of assigning risk and reward is that some of the greatest investors in the world consider it trivial. Warren Buffett, for example, is the anti-beta. Buffett’s argument goes something like this: Imagine a perfectly good company with strong revenues, low costs, and a sustainable competitive advantage. Its stock trades at an earnings multiple just above its peers. Then, one day, the chief executive is found in bed with a sheep. It turns out he has been using company money to amuse both himself and his sheep. The chief executive is humiliated, and the company becomes a nationwide joke. The stock price plummets in relation to the market. For reasons that have nothing to do with the company’s fundamental performance, it suddenly looks like a high-beta stock—volatile and risky. But for the value investor like Buffett, an investment in the company just became dramatically less risky. The stock is now cheap and will more than likely recover ground, as the company is still appreciated by its customers, giving the investor a higher return for pretty much the same company-specific risk as existed before the sheep incident. The key is to keep your focus on the price of the stock in relation to the future cash flows it will generate. How that price has moved historically, either in absolute or relative terms, is all but irrelevant. Focusing on beta is a near-certain way of denying yourself alpha, the true measure of greatness.

Alpha is the white whale of the investment community—coveted, precious, sought with a maniacal fury, and yet rarely captured. It reflects the extent to which you make nonsense of standard risk/reward measures. To understand alpha, imagine a situation in which you take the risk of having your foot stamped on for the high-probability return of an apple. Everyone in the market knows that if you risk having your foot stamped on, you should get an apple, and they can decide whether or not to take the risk. But imagine if someone in this market is taking exactly the same risk of having his foot stamped on, but receiving both an apple and a five-dollar bill. That five-dollar bill is alpha and it is what the very best investors are measured by.

If an investor can look at ten car companies that have all historically returned 6 percent, and pick the one that will return 15 percent for the same degree of risk as the others, that 9 percent is his alpha. If he can find weird alternative assets—say, aluminum futures or documentary films— that have the same risk profile as the car companies but return 20 percent, even better. Like beta, alpha also cropped up regularly in conversation at HBS. “Matt’s alpha is his quantitative skills, whereas Ben’s is his ability to shoot from outside the three-point line.” You can achieve alpha in all kinds of ways, but there are two basic ones: picking the right investment and picking the right mix of investments, which, bundled together, provide higher reward for lower risk than any of the individual investments would. Serious investors will always insist on talking not about returns but about risk-adjusted returns. This was one of the most important lessons I took from Finance.

Between classes a group would form at the back of the room to track the portfolio of Chad, the finance stud, in his search for alpha. Some days would be headily alpha, a successful exit from a short position on a biotech firm. Others would be gloomily beta, just moving along with the market. Very occasionally, a pencil would snap between Chad’s meaty paws as a negative return showed up on his Yahoo! Finance page.

Benjamin Graham, the intellectual godfather of value investing, spoke about risk in yet another way. He liked companies that had a “margin of safety,” some cash in the bank, perhaps, or a very manageable amount of debt. A good product needed or loved by customers was another good sign. You basically want to look at companies much as you would people. Do they work hard? Are they honest? Likeable? Creative? Entrepreneurial? Do they spend more than they earn? Are they mortgaged to the hilt? What if they lost their job tomorrow, what would happen? Would they find another one quickly?

There seemed to come a point in every class involving the use of numbers when the professor would say, “This is an art not a science.” And there always seemed to be a note of regret in his voice. Valuing companies, for all the sweat and effort people put into it, always ran into immeasurable uncertainties. The bankers in the class told us that they would frequently produce proposals to companies, with elaborate valuation spreadsheets, knowing they were nonsense. They bore the appearance of competence and intelligence but meant desperately little. These deal books were simply churned out by overworked analysts in their early twenties, using hoary valuation tricks, to make the banks look as if they had done their work. The cost of capital used was normally 10 percent and then adjusted up or down if necessary. In many cases, the bankers simply took a book created for one firm and adjusted it a little for another. It was not even art, it seemed to me, but downright deception.