A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing

by Burton G. Malkiel

If you examine past stock prices in any given period, you can almost always find some kind of system that would have worked in a given period. If enough different criteria for selecting stocks are tried, one will eventually be found that selects the best ones of that period. The real problem is, of course, whether the scheme works in a different time period.

For the sake of argument, suppose the technician had found a reliable year-end rally, that is, every year stock prices rose between Christmas and New Year’s Day. The problem is that once such a regularity is known to market participants, people will act in a way that prevents it from happening in the future.† Any successful technical scheme must ultimately be self-defeating.

If people know a stock will go up tomorrow, you can be sure it will go up today. Any regularity in the stock market that can be discovered and acted upon profitably is bound to destroy itself. This is the fundamental reason why I am convinced that no one will be successful in using technical methods to get above-average returns in the stock market.

Moreover, buying and selling, to the extent that it is profitable at all, tends to generate capital gains, which are subject to tax. By following any technical strategy, you are likely to realize short-term capital gains and pay larger taxes (as well as paying them sooner) than you would under a buy-and-hold strategy. Thus, simply buying and holding a diversified portfolio suited to your objectives will enable you to save on investment expense, brokerage charges, and taxes.

There are, I believe, five factors that help explain why security analysts have such difficulty in predicting the future. These are (1) the influence of random events, (2) the production of dubious reported earnings through “creative” accounting procedures, (3) errors made by the analysts themselves, (4) the loss of the best analysts to the sales desk or to portfolio management, and (5) the conflicts of interest facing securities analysts at firms with large investment banking operations.

Depending on what expenses are considered to be improperly ignored, companies can report a substantial overstatement of earnings. Small wonder that security analysts have extraordinary difficulty estimating what future earnings are likely to be.

I am not suggesting that it is impossible to beat the market. But it is highly unlikely.

The academic community has rendered its judgment. Fundamental analysis is no better than technical analysis in enabling investors to capture above-average returns.

The efficient-market hypothesis explains why the random walk is possible. It holds that the stock market is so good at adjusting to new information that no one can predict its future course in a superior manner. Because of the actions of the pros, the prices of individual stocks quickly reflect all the news that is available. Thus, the odds of selecting superior stocks or anticipating the general direction of the market are even. Your guess is as good as that of the ape, your stockbroker, or even mine.

One of the best-documented propositions in the field of finance is that, on average, investors have received higher rates of return for bearing greater risk.

Still, over the long haul, investors have been rewarded with higher returns for taking on more risk. However, there are ways in which investors can reduce risk. This brings us to the subject of modern portfolio theory, which has revolutionized the investment thinking of professionals.

Portfolio theory begins with the premise that all investors are like my wife—they are risk-averse. They want high returns and guaranteed outcomes. The theory tells investors how to combine stocks in their portfolios to give them the least risk possible, consistent with the return they seek.

Nevertheless, because company fortunes don’t always move completely in parallel, investment in a diversified portfolio of stocks is likely to be less risky than investment in one or two single securities.

In general, diversification will not help much if there is a high covariance (high correlation) between the returns of the two companies.

Now comes the real kicker; negative correlation is not necessary to achieve the risk reduction benefits from diversification.

anything less than perfect positive correlation can potentially reduce risk.

is there a point at which diversification is no longer a magic wand safeguarding returns? Numerous studies have demonstrated that the answer is yes.

the golden number for American xenophobes—those fearful of looking beyond our national borders—is at least fifty equal-sized and well-diversified U.S. stocks (clearly, fifty oil stocks or fifty electric utilities would not produce an equivalent amount of risk reduction). With such a portfolio, the total risk is reduced by over 60 percent.

The paradoxical result of this analysis is that overall portfolio risk is reduced by the addition of a small amount of riskier foreign securities.

It turns out that the portfolio with the least risk had 17 percent foreign securities and 83 percent U.S. securities.

Moreover, adding 17 percent EAFE stocks to a domestic portfolio also tended to increase the portfolio return.

International diversification provided the closest thing to a free lunch available in our world securities markets. When higher returns can be achieved with lower risk by adding internatio...

EAFE index of developed foreign stocks,

Even during the horrible stock market of 2008, a broadly diversified portfolio of bonds invested in the Barclay’s Capital broad bond index returned 5.2 percent. There was a place to hide during the financial crisis. Bonds (and bond-like securities to be covered in Part Four) have proved their worth as an effective diversifier.

diversification cannot eliminate all risk—as it did in my mythical island economy—because all stocks tend to move up and down together. Thus, diversification in practice reduces some but not all risk.

finance specialists John Lintner and Fischer Black—focused their intellectual energies on determining what part of a security’s risk can be eliminated by diversification and what part cannot. The result is known as the capital-asset pricing model.

capital-asset pricing model is that there is no premium for bearing risks that can be diversified away. Thus, to get a higher average long-run rate of return, you need to increase the risk level of the portfolio that cannot be diversified away. According to this theory, savvy investors can outperform the overall market by adjusting their portfolios with a risk measure known as beta.

We go on to say that part of total risk or variability may be called the security’s systematic risk and that this arises from the basic variability of stock prices in general and the tendency for all stocks to go along with the general market, at least to some extent. The remaining variability in a stock’s returns is called unsystematic risk and results from factors peculiar to that particular company—for example, a strike, the discovery of a new product, and so on. Systematic risk, also called market risk,

Some stocks and portfolios tend to be very sensitive to market movements. Others are more stable. This relative volatility or sensitivity to market moves can be estimated on the basis of the past record, and is popularly known by—you guessed it—the Greek letter beta.

Basically, beta is the numerical description of systematic risk.

The beta calculation is essentially a comparison between the movements of an individual stock (or portfolio) and the movements of the market as a whole.

The calculation begins by assigning a beta of 1 to a broad market index. If a stock has a beta of 2, then on average it swings twice as far as the market.

If a stock has a beta of 0.5, it tends to go up or down 5 percent when the market rises or declines 10 percent. Professionals call high-beta stocks aggressive invest...

Now, the important thing to realize is that systematic risk cannot be elimina...

Indeed, if you diversified perfectly by buying a share in the Total Stock Market index (which by definition has a beta of 1), you would still have quite variable (risky) returns because the market as a whole fluctuates widely.

Receipt of a large new contract, the finding of mineral resources, labor difficulties, accounting fraud, the discovery that the corporation’s treasurer has had his hand in the company till—all can make a stock’s price move independently of the market. The risk associated with such variability is precisely the kind that diversification can reduce.

The only part of total risk that investors will get paid for bearing is systematic risk, the risk that diversification cannot help. Thus, the capital-asset pricing model says that returns (and, therefore, risk premiums) for any stock (or portfolio) will be related to beta, the systematic risk that cannot be diversified away.

The beta for any security is essentially the same thing as the covariance between that security and the market index as measured on the basis of past experience.

I found a similar result for the relationship between return and beta for mutual funds. There was no relationship between returns for stocks or portfolios and their beta risk measures.

Beta, the key analytical tool of the capital-asset pricing model, is not a useful single measure to capture the relationship between risk and return.

Thus, the beta measure of relative volatility does capture at least some aspects of what we normally think of as risk. And portfolio betas from the past do a reasonably good job of predicting relative volatility in the future.

Second, as Professor Richard Roll of UCLA has argued, we must keep in mind that it is very difficult (indeed probably impossible) to measure beta with any degree of precision.

What is clear, however, is that beta, as usually measured, is not a substitute for brains and cannot be relied on as a simple predictor of long-run future returns.

Changes in interest rates also systematically affect the returns from individual stocks and are important nondiversifiable risk elements. To the extent that stocks tend to suffer as interest rates go up, equities are a risky investment, and those stocks that are particularly vulnerable to increases in the general level of interest rates are especially risky. Thus, some stocks and fixed-income investments tend to move in parallel, and these stocks will not be helpful in reducing the risk of a bond portfolio.

Changes in the rate of inflation will similarly tend to have a systematic influence on the returns from common stocks.

First, an increase in the rate of inflation tends to increase interest rates and thus tends to lower the prices of some equities,

The stock market appears to be an efficient mechanism that adjusts quite quickly to new information. Neither technical analysis, which analyzes the past price movements of stocks, nor fundamental analysis, which analyzes more basic information about the prospects for individual companies and the economy, seems to yield consistent benefits. It appears that the only way to obtain higher long-run investment returns is to accept greater risks. Unfortunately, a perfect risk measure does not exist. Beta, the risk measure from the capital-asset pricing model, looks nice on the surface. It is a simple, easy-to-understand measure of market sensitivity. Alas, beta also has its warts. The actual relationship between beta and rate of return has not corresponded to the relationship predicted in theory during long periods of the twentieth century. Moreover, betas for individual stocks are not stable over time, and they are very sensitive to the market proxy against which they are measured. I have argued here that no single measure is likely to capture adequately the variety of systematic risk influences on individual stocks and portfolios. Returns are probably sensitive to general market swings, to changes in interest and inflation rates, to changes in national income, and, undoubtedly, to other economic factors such as exchange rates. Moreover, there is evidence that returns are higher for stocks with lower price-book ratios and smaller size. The mystical perfect risk measure is still ...

Nevertheless, we must be careful not to accept beta or any other measure as an easy way to assess risk and to predict future returns with any certainty.

Basically, there are four factors that create irrational market behavior: overconfidence, biased judgments, herd mentality, and loss aversion.

In a strict sense, the word “arbitrage” means profiting from prices of the same good that differ in two markets.