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esis. These studies are designed to find exceptions, or anomalies, to the predictions associated with efficiency. The goal of many of the studies has been to find an investment strategy or trading rule that consistently produces investment returns, adjusted for risk, that are greater than the returns associated with a long-term buy-and-hold the general stock market strategy. Some of the studies found that certain trading rules produced higher returns than a buy-and-hold strategy, but when trading costs were incorporated, the excess returns vanished. Other studies found that a certain investment approach (the January effect, small cap stocks, Dogs of the Dow) worked for a period of time and generated excess returns. However, once the strategy was touted and known by the general public, the excess returns disappeared due to too many investors playing the same game. The majority of studies have shown that new information is quickly incorporated into stock prices and the excess returns that are associated with certain stock-selection strategies are arbitraged away. In market lore, there is empirical evidence that the stock market is relatively efficient, or at least semiefficient. A number of assumptions about investor behavior and the structure of capital markets underlie modern portfolio theory and the efficient capital market hypothesis. Investors are assumed to be rational and calculating, to have identical beliefs and expectations of how the market works, and to have equal access to new information. Investors are assumed to be intelligent and so well informed that the prices they establish, based on new information, are correct (equilibrium) prices. Sound like the real world If the stock market is truly efficient, stock prices will react quickly to new information. Let s assume that at 11 a.m., XYZ Company releases positive-earnings news that should increase the value of its stock by $10 to $60 per share. If the efficient capital markets theory holds, we would expect the type of price reaction shown in Exhibit 2-3 as the Immediate Adjustment example. If markets are not efficient, we would expect the market to adjust to new information over time, as shown by the Gradual Adjustment example.
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Enter Behavioral Finance
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In recent years, the assumptions underlying MPT have been challenged by academicians who specialize in the field of behavioral finance, a branch of finance that examines human decision-making and
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EXHIBIT 2-3
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behavioral patterns and interjects sociology and psychology into the mix. MPT assumes rational, calculating, intelligent investors who focus solely on stock prices. Behavioral theorists have conducted studies that show that investors are not like that at all. The 2002 Nobel Prize in Economics was awarded to behavioral finance specialists, Dr. Daniel Kahneman, a professor of psychology at Princeton University, and Dr. Vernon Smith of George Mason University. Kahneman, in collaborating with the late Dr. Amos Tversky, challenged the assumption that consumers are rational and markets behave rationally. He showed that individuals make errors in judgment that can be accurately predicted. Smith in the late 1980s conducted mock stock market experiments with students and showed that stock markets were not efficient. He found that people and markets, at times, behave irrationally. Sound like the high-tech bubble Today s younger proponents of behavioral finance, notably Professors Richard Thaler, Robert Shiller, and Robert Haugen, have published studies and books3 that also call into question the assumptions of rational investor behavior that underlie efficient capital markets and modern portfolio theory. They find that investors hate to lose, which causes them to hold on to losing stocks much longer than they should.
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The 10 Principles of Finance and How to Use Them
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They find that investors often are ill informed and tend to overreact or underreact to new information, and that investors love patterns (technical analysis) and tend to find them, even where they don t exist. They also find that investors are overconfident in their abilities and tend to be overoptimistic. Overconfidence causes investors to think that they are smarter than they are, and leads them to underestimate risk. In short, they find that investors are human exhibiting all of the associated flaws of humanity. Investors are not the cold, calculating, completely rational automatons that are assumed in MPT.
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