Making money when markets go nowhere

You can probably save a good-sized forest by recycling academic papers on risk and diversification. These concepts are drummed into students’ heads in academia, but their practical application usually is spoiled by long formulas awash in Greek symbols. I kept that in mind and wrote this chapter from the practitioner’s point of view.

MANAGING RISK

One way to approach risk is from the perspective of volatility: a stock declining in price or returns falling below one’s expectations. Another school of thought comes from Warren Buffett and Benjamin Graham — it looks at risk as permanent loss of capital. Are these definitions mutually exclusive? The truth lies somewhere in between.

What risk means to us is shaped by our time horizon. If you are investing for the long run — at least five years — a permanent loss of capital is the risk that you should be concerned with the most. The distinction here is that if you are armed with a long-term time horizon, volatility is a mere inconvenience (and often an opportunity, especially in a sideways market). Assuming the volatility is temporary in nature, given enough time, the investment will come back to its original level.

If you have a short-term time horizon, volatility is not temporary. Even a temporary stock decline results in permanent loss of capital, since you don’t have the time to wait it out. Permanent loss of capital is a true risk to the long-term investor, since time will not heal that problem. This book is written for long-term investors, and thus we approach risk as permanent loss of capital.

There is another important, although less tangible, issue with volatility: It impacts our emotions and makes us do the wrong things — buy high and sell low. For a very rational, computerlike decision maker, this is not an issue. But we are not computers. Therefore, you shouldn’t ignore the emotional element of volatility. Make reasonable attempts to minimize its impact on the portfolio through diversification, and/or own stocks from businesses you understand so that you can be comfortable with their price fluctuations.

Knowing the past is essential to being able to predict the future. But the past provides only one (though definitive) version of what could have taken place. Identify other possible pasts. “A winner is not to be judged” is a popular but dangerous Russian expression. This is a very common attitude when executive decisions, company performance or investment results are analyzed: Since it worked, it must have been a good decision.

ALTERNATIVE HISTORY

Here is an example of how dangerous it is to evaluate decisions by focusing solely on the outcome. Let’s say the chief executive of a company that has all of its operations in Grand Cayman decided to save a lot of money by canceling the company’s hurricane insurance, saying something to his constituents along the lines of, “Why waste millions of dollars on insurance when we can put it into R&D instead?”

With God’s help and a little bit of luck, there was no hurricane the first year. The company saved a lot of money on insurance premiums, and its earnings went through the roof, marking the best year in its history. Now, should the CEO be given a huge bonus for saving millions of dollars on insurance premiums or should he be fired?

Hindsight analysis based on observed history would tell us to reward the CEO. He did not waste money on insurance and saved millions of dollars.

But this conclusion completely ignores other very probable alternative paths and risk that have not surfaced — hidden risks. Analysis of what could have taken place, a look at alternative historical paths, would tell us the other, arguably more accurate side of the story. From 1871 to 2004, a hurricane hit Grand Cayman about every two-and-a-quarter years. In other words, there is a 44% possibility that a hurricane will hit Grand Cayman in any given year. This estimate is based on 133 years of historical observations, a pretty large data set.

If we gain an understanding of alternative historical paths, we will be able to assess the past more accurately — and thus gain a better understanding of the future.

In our example, the company’s substantially improved profitability was accompanied (actually, generated) by a very great hidden risk. The CEO had absolutely no control and no predictive forecasting power over if and when a hurricane would hit Grand Cayman. Unless he accurately predicted about a million different factors that impact the creation and direction of hurricanes, the CEO made a very blind decision that exposed the company to grave risk, and then just got lucky. By analyzing results only in the context of observed risk, we subject ourselves to the mercy of randomness, because it determines how much risk to expose. When evaluation of results is based solely on observed risk, success is often attributed to skills of an investment or a corporate manager, and not to Lady Luck, who really deserves it.

In 2006 or early 2007, a broker who had his clients’ accounts with my company called me and asked why our accounts were not doing as well as a mutual fund that he held in his personal account. I looked up that mutual fund and found that though our accounts were up nicely for the year, the mutual fund was up double or triple what we were. I took a closer look and discovered that more than half of the fund’s assets were in energy-related stocks, and this allocation was responsible for all of the fund’s spectacular returns; at that time, oil was making all-time highs. My response to the broker was simple: “Performance of this mutual fund will be driven in large part by a very volatile and unpredictable commodity — oil. You see the spectacular returns now, but what you don’t see is the risk that has been taken by this fund. You don’t have to have a rich imagination to picture what would happen to the returns of this fund if oil prices were to fall. I would never let this fund manager run my parents’ money, or my kids’, for that matter — the hidden risk (which showed up within a few years) is just too great.”

It is useful to analyze mutual funds or money managers looking at their worst-period results, not average longer-term returns, even though this may not reveal the embedded hidden risk. For instance, Amaranth Advisors LLP, a large hedge fund, had phenomenal performance until … it did not. It placed large leveraged bets on the direction of the price of natural gas in the summer and fall of 2006. The fund did very well until it lost billions of dollars in less than a month. Such an event is the reason why, in your analysis of money managers or mutual funds, you want to make sure that their investment process makes sense to you. If it doesn’t, even if past returns are terrific, stay away.

The investing environment is infested with randomness — it is a continual professional hazard. Our skill, knowledge, and experience should help to reduce the risk of randomness, but eradicating it completely is impossible, since randomness is the nature of the investing jungle. Stay within your circle of competence and do in-depth research to decrease the amount of randomness and its impact on your portfolio. Focus not only on what has happened (which often is random) but also on what could have happened. Learn from the past and judge companies and managers based on all possible outcomes. Finally, to help protect yourself from randomness — diversify!

DIVERSIFICATION

It is frequently said that diversification is the only free lunch an investor will ever get, since this risk reduction strategy doesn’t need to lead to a subsequent reduction in return. Or does it? Warren Buffett disagrees: “Diversification is a protection against ignorance. It makes little sense for those who know what they are doing.”

Both statements are correct. At one extreme, investors often fail to diversify, holding just a handful of companies and subjecting themselves to unnecessary risk. The following happened to a good friend of mine. Let’s call him Jack. He and his wife both worked for the largest insurance broker in the world, Marsh & McLennan Cos., a much-respected firm with a market capitalization of over $20 billion and revenue in excess of $12 billion. Over the years, Jack and his wife accumulated a large position in Marsh’s stock, which they were reluctant to sell.

Sometime in 2000, he asked me what I thought of their financial situation, having all this wealth in Marsh’s stock. I commented that although I didn’t see Marsh going out of business anytime soon, I would not recommend having all of their net worth in one company. Employees of Enron Corp., MCI Inc. or Lucent Technologies Inc. did not foresee that their 401(k)s would disappear just months before they did so. Although the probability of Marsh’s disappearing was very, very small, this couple’s lack of diversification just was not worth the risk, especially considering that both of their personal income streams (paychecks) also came from Marsh. Jack listened to my advice and agreed with it. He did not feel the urgency to do anything about it, though, so he stayed busy with his day-to-day life and did not take action, until …

Several years later, one sunny day (at least it was sunny on my side of Denver), I was driving to work when I got a call from Jack, who asked, “Did you see what happened to Marsh?” I had not. Jack explained that Eliot Spitzer (the state attorney general of New York at the time) had filed a lawsuit against Marsh accusing the company of bid rigging, insinuating that Marsh was not acting in clients’ best interests when it charged (often undisclosed) contingent commissions. Marsh’s stock was almost halved on the news, since contingent commissions accounted for a large portion of the company’s profits. Talk about bankruptcy was in the air. To my surprise, Jack was very calm (considering that Marsh stock was his entire net worth at the time), and he asked my thoughts on what he and his wife should do about their Marsh stock.

In this type of situation, when all hell is breaking loose, you need to weigh the probabilities of possible outcomes. Bankruptcy, which was an improbable outcome for Marsh a day before the lawsuit was filed, suddenly became a lot more probable. Or at least the odds went from one in a gazillion to a remote, but imaginable, outcome. Marsh’s debt did not seem high, at about 30 percent of total assets. However, without contingent commissions (whose future was very uncertain and which carried almost 100 percent gross margin), Marsh was barely profitable, if at all. Also, this had a similar smell to the Arthur Andersen LLP debacle. Both firms were in the intellectual capital, or trust, business, in which a lawsuit could trigger a massive client exodus that would put the company out of business.

If Marsh was just another stock (one of 15 or 20) in a diversified portfolio, the remote risk of its bankruptcy — the worst-case scenario — would have been considered as one of the risks, with appropriate attribution of probabilities to each potential outcome. But this is what theory doesn’t tell you: When one cannot afford a low-probability outcome (and Jack could not afford it), one starts treating that outcome as having a much-increased probability.

Following our conversation, Jack sold a good portion of his Marsh stock at a significant loss. At the time the Marsh debacle was taking place, he was going to buy a new house, but he had to break the contract. He lost his down payment, plus he was not sure he and his wife would have their jobs down the road. Luckily, neither of them lost their jobs, and several months later, he went to work for another insurance broker (the move was a promotion; working for Marsh was not the same anymore). I bet Jack will never look at diversification with the same complacency again.

A portfolio consisting of just a handful of stocks enormously impairs your ability to make rational decisions at the time when that ability is needed the most — under pressure. Managing this emotional reality is one of the more subjective aspects of risk management through diversification.

TOO MANY BASKETS

At the other extreme, investors holding hundreds of stocks incur another cost — ignorance. The dictionary defines ignorance as the condition of being uneducated, unaware or uninformed — the costs to which Buffett is referring. A very large number of companies in investors’ portfolios makes it impossible for them to know these companies well. Lack of knowledge leads to an inability to make rational decisions, which then causes investors to behave irrationally and hurts portfolio returns. Another side effect of overdiversification is indifference to individual investment decisions. In a portfolio of hundreds of stocks, an individual position might represent 1% or less of the total portfolio. The cost of being wrong is very small, as is the benefit of being right. If, for instance, one stock goes up or down 20%, the overall impact on the portfolio is only 0.2% either way. This breeds a semi-indifference to incremental decisions that is common among overdiversified buy-and-hold investors.

You need to strike an appropriate balance, weighing the consequences of either extreme. Academics disagree on the exact number of uncorrelated stocks needed in a portfolio to eradicate individual stock risk, but that number is usually given as somewhere between 16 and 25 stocks. This is another case where being vaguely right is better than being precisely wrong. I find that a portfolio of about 20 stocks is manageable and provides an adequate level of diversification; at this level, the price of being wrong is not too high, but every decision matters.

Taking diversification a step further, stress testing a portfolio (playing out different what-if scenarios) is critical, since it exposes the portfolio’s weaknesses in the case of hidden risks rising to the surface.

Excerpted from “The Little Book of Sideways Markets” by Vitaliy N. Katsenelson (John Wiley & Sons Inc., 2011).