Can Stock Analysts Really Predict the Future?

Chapter 7 of A Random Walk Down Wall Street asks a question that should make every investor uncomfortable. All those analysts on Wall Street, the ones in suits flying first class and talking earnings forecasts all day, can they actually predict the future? Malkiel digs into the evidence. And it’s not pretty.

Wall Street vs. the Professors

There are two camps here. Wall Street believes fundamental analysis is getting better every year. The pros say that individual investors don’t stand a chance against teams of researchers visiting companies, studying balance sheets, and building financial models.

Academics, on the other hand, think that’s mostly hot air. Some have gone so far as to say a blindfolded monkey throwing darts at a stock listing would do just as well as the pros.

Malkiel doesn’t fully side with either group. But the data leans heavily toward the professors.

Are Analysts Clairvoyant? Not Even Close

Security analysts live and die by earnings forecasts. That’s their whole job. So how good are they at it?

The first problem is that they love to look at past earnings growth and project it forward. If a company grew fast last decade, surely it’ll keep growing fast, right? Wrong. Academic research shows that knowing which companies grew fastest in the 1980s gave you zero help predicting which ones would lead in the 1990s. The pattern just doesn’t hold. Only one in eight large companies maintained consistent growth during the 1990s boom. Not a single one kept it going into the 2000s.

Malkiel and his colleague John Cragg went straight to the source. They asked nineteen top Wall Street firms for their earnings predictions, then compared those to what actually happened. The analysts’ five-year forecasts were worse than just assuming every company would grow at the national average. Their one-year forecasts were even worse than the five-year ones.

When analysts complained that high-tech stocks were too unpredictable, they were told to try utilities instead. They didn’t like those results either. No industry turned out to be easy to forecast. And no individual analyst was consistently better than the others. Being right one year meant nothing for the next.

Here’s the kicker: a Harvard and MIT study found that analysts’ average error rate was 31.3% per year. Malkiel puts it perfectly. “Financial forecasting appears to be a science that makes astrology look respectable.”

Five Reasons the Crystal Ball Is Broken

Malkiel identifies five reasons analysts keep getting it wrong.

Random events are everywhere. Oil price shocks, government regulations, natural disasters, terrorist attacks, surprise lawsuits. These things blindside even the best analysts. The “stable” utility industry got hammered by unpredictable fuel costs and deregulation.

Creative accounting hides the truth. Companies love making their numbers look better than reality. Enron swapped fiber-optic capacity with Qwest, and both recorded $500 million in fake sales. Sunbeam’s CEO convinced retailers to buy grills in winter just to pump up quarterly numbers. Kodak took $4.5 billion in write-offs over a decade to make future earnings look artificially strong. When the numbers companies report are fiction, analysts working from those numbers are just guessing.

Analysts make basic mistakes. Malkiel shares a story about a metals analyst named Louie who misplaced a decimal point, making a stock look ten times more attractive than it was. When the error was pointed out, Louie shrugged and said the recommendation “sounds more convincing” as-is. A plastic surgeon writing for Barron’s examined biotech analysts’ reports and found their market share predictions for competing companies added up to well over 100%. They didn’t even understand the industry they were covering.

The best analysts leave. The smartest analysts get pulled away to become salespeople, portfolio managers, or hedge fund managers. The actual analysis work gets left to whoever stays behind.

Conflicts of interest poison everything. Analysts at major firms were paid based on how much investment banking business they helped bring in. That means they had every reason to recommend stocks of companies their firm was doing deals with. During the 1990s, the ratio of buy to sell recommendations was 100 to 1. When Henry Blodget at Merrill Lynch was publicly recommending certain internet stocks, his private emails called them “junk” and “dogs.” Merrill settled for $100 million but didn’t admit guilt.

Mutual Funds Can’t Beat the Market Either

If individual analysts are unreliable, maybe funds full of analysts can do better? Malkiel looks at the one group where performance records are public: mutual funds.

The answer is straightforward. Over a twenty-year period ending in 2009, the average equity mutual fund returned 7.53% annually. The Russell 3000 Index returned 8.42%. Just buying the whole market and sitting there beat most professionals.

But what about star fund managers? Here’s the problem with that. Malkiel shows the same pattern across decades. The top 20 funds of the 1970s performed worse than average in the 1980s. The top funds of the 1980s lagged behind the S&P 500 in the 1990s. The top funds of the 1990s lost money in the 2000s while the index merely declined.

The Mates Fund was number one in 1968. By 1974, it had lost 93% of its value. The manager quit investing and opened a singles bar in New York called Mates.

Malkiel compares this to a coin-flipping contest. Start with 1,000 people flipping coins. After seven rounds, eight people will have flipped heads every time. They’ll look like geniuses. People will write articles about their technique. But it was just luck.

Market Timing Doesn’t Work

Some managers claim their real skill is knowing when to move money in and out of the market. The data says otherwise. Mutual fund managers held the most cash at market bottoms (1970, 1974, 1982, 1987, 2002, 2009) and the least cash at market peaks (like March 2000, right before the crash). They got it backwards almost every time.

John Bogle, founder of Vanguard, summed it up: in 30 years of business, he never met anyone who could time the market consistently. Academic research shows you’d need to be right 70% of the time for market timing to beat a simple buy-and-hold strategy. Nobody bats .700.

What This All Means

Malkiel walks a middle road. He doesn’t say every analyst is useless or that markets are perfectly efficient. He admits there could be exceptional managers out there. But the evidence says they are extremely rare, and you have no reliable way to identify them in advance.

Even Benjamin Graham, the father of fundamental analysis, admitted before he died that he no longer believed elaborate security analysis could find enough bargains to justify the effort. Peter Lynch and Warren Buffett both said most people would be better off in an index fund.

The market isn’t random because it’s irrational. It’s random because it’s efficient. Prices adjust to new information so fast that by the time you hear about it, it’s already baked into the price. And real news develops unpredictably. No amount of chart-reading or balance-sheet-studying changes that.

If there’s one takeaway from this chapter, it’s this: the people getting paid to beat the market mostly can’t. And the few who do can’t keep doing it. That’s not a comforting thought for anyone paying management fees. But it’s a very useful one.

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