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April 19 - July 7, 2018
Rule 2: A rational investor should pay a higher price for a share, other things equal, the larger the proportion of a company’s earnings paid out in cash dividends or used to buy back stock.
Rule 3: A rational (and risk-averse) investor should pay a higher price for a share, other things equal, the less risky the company’s stock.
In pro forma earnings, companies decide to ignore certain costs that are considered unusual;
Pro forma earnings are often called
“earnings before all the ...
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Louie’s lack of attention to detail revealed his lack of understanding of the industry he was covering.
Whenever the returns from two
securities move in tandem (when one goes up, the other always goes up), the covariance number will be a large positive number. If the returns are completely out of phase, as in the present example, the two securities are said to have negative covariance.
AS EVERY READER should know by now, risk has its rewards.
Thus, diversification in practice reduces some but not all risk.
capital-asset pricing model.
The basic logic behind the 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.
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.
Professionals call high-beta stocks aggressive investments and label low-beta stocks as defensive.
The risk associated with such variability is precisely the kind that diversification can reduce.
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.
Not so, declares a new school of financial economists who came to prominence in the early part of the twenty-first century.
While that may be all well and good for the professors and the students, what about all the other people who want to invest in stocks. How can behavioral finance help them? More to the point, what’s in it for you? Actually, quite a bit.
Behavioralists believe that market prices are highly imprecise. Moreover, people deviate in systematic ways from rationality, and the irrational trades of investors tend to be correlated. Behavioral finance then takes that statement further by asserting that it is possible to quantify or classify such irrational behavior. Basically, there are four factors that create irrational market behavior: overconfidence, biased judgments, herd mentality, and loss aversion.
In the loosest sense of the term, “arbitrage” is used to describe the buying of stocks that appear “undervalued” and the selling of those that have gotten “too high.”
In so doing, hardworking arbitrageurs can smooth out irrational fluctuations in stock prices and create an efficiently priced market.
On the other hand, behavioralists believe there are substantial barriers ...
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The remainder of this chapter explores the key arguments of behavioral finance in explaining why markets are not efficient and why there is no such thing as a random walk down Wall Street. I’ll also explain how an understanding of this work can help protect individual investors from some systematic errors that investors are prone to.
As Part One made abundantly clear, there are always times when investors are irrational. Behavioral finance, however, says that this behavior is continual rather than episodic.
Researchers in cognitive psychology have documented that people deviate in systematic ways from rationality in making judgments amid uncertainty. One of the most pervasive of these biases is the tendency to be overconfident about beliefs and abilities and overoptimistic about assessments of the future.
These kinds of experiments have been repeated many times and in several different contexts.
Daniel Kahneman has argued that this tendency to overconfidence is particularly strong among investors.
What should we conclude from these studies? It is clear that people set far too precise confidence intervals for their predictions. They exaggerate their skills and tend to have a far too optimistic view of the future. These biases manifest themselves in various ways in the stock market.
First and foremost, many individual investors are mistakenly convinced that they can beat the market.
People are prone to attribute any good outcome to their own abilities.
They tend to rationalize bad outcomes as resulting from unusual external events.
Steve Forbes, the longtime publisher of Forbes magazine, liked to quote the advice he received at his grandfather’s knee: “It’s far more profitable to sell advice than to take it.”
Many behavioralists believe that overconfidence in the ability to predict the future growth of companies leads to a general tendency for so-called growth stocks to be overvalued.
Overoptimism in forecasting the growth for exciting companies could then be one explanation for the tendency of “growth” stocks to underperform “value” stocks.
Biases in judgments are compounded (get ready for some additional jargon) by the tendency of people mistakenly to use “similarity” or “representativeness” as a proxy for sound probabilistic thinking.
As all readers of this book recognize, the market as a whole does not invariably make correct pricing decisions. At times, there is a madness to crowd behavior, as we have seen from seventeenth-century tulip bulbs to twenty-first-century Internet stocks.
One widely recognized phenomenon in the study of crowd behavior is the existence of “group think.”
Solomon Asch
“There is nothing so disturbing to one’s well-being and judgment as to see a friend get rich.”
Such herding is not limited to unsophisticated individual investors. Mutual-fund managers have a tendency to follow the same strategies and herd into the same stocks.
One of the most important lessons of behavioral finance is that individual investors must avoid being carried away by herd behavior.
Kahneman and Tversky’s most important contribution is called prospect theory, which describes individual behavior in the face of risky situations where there are prospects of gains and losses.
Losses are considered far more undesirable than equivalent gains are desirable.
In other words, a dollar loss is 2½ times as painful as a dollar gain is pleasurable. People exhibit extreme loss aversion, even though a change of $100 of wealth would hardly be noticed for most people with substantial assets.
Interestingly, however, when individuals faced a situation where sure losses were involved, the psychologists found that they were overwhelmingly likely to take the gamble.
Kahneman and Tversky also discovered a related and important “framing” effect. The way choices are framed to the decision maker can lead to quite different outcomes.
Note first that the expected value of the number of people saved is the same 200 in both programs. But according to prospect theory, people are risk-averse when considering possible gains from the two programs, and, as expected, about two-thirds of the respondents to this question picked Program A as the more desirable.
Behavioralists also stress the importance of the emotions of pride and regret in influencing investor behavior. Investors find it very difficult to admit, even to themselves, that they have made a bad stock-market decision. Feelings of regret may be amplified if such an admission had to be made to friends or a spouse. On the other hand, investors are usually quite proud to tell the world about their successful investments that produced large gains.
Many investors may feel that if they hold on to a losing position, it will eventually recover and feelings of regret will be avoided.
