9 -- Part 1: Market Efficiency and Behavioral Finance
The committee appeared to display a sense of humor by giving a shared award to Fama and Shiller because they are best known for holding opposing views on the efficiency of financial markets.
Eugene Fama was one of the first to define the term "efficient markets" in his landmark study that concluded that any attempt to earn better-than-average returns by identifying winners and losers in the stock market was a fool's errand.
Competition among rational investors resulted in accurate stock prices, according to Fama.
Shiller's book challenges investors when markets are efficient.
The evidence shows that it would be better to sit on the sidelines than to invest in stocks.
Less than a decade later, Shiller made headlines again through his warnings that the housing market was becoming List four "decision traps" that may lead investors to overheated, a prediction that the subsequent collapse in make systematic errors in their investment decisions.
For a long time, investment professionals and academics were on opposite sides of the debate.
Explain how the market was very efficient anomalies to investors' cognitive biases.
The professional argued that well-trained investors with access to sophisticated charting, and other indicators of the technical condition of information and trading systems could deliver superior returns to the market.
The two sides have moved closer together.
Many investors will be better off buying and holding a diversified portfolio of securities rather than paying experts to identify mispriced stocks because it is very difficult to consistently identify overvalued or undervalued securities.
This view has led to the growth of low-cost investment options.
The stock market is seen as a form of legalized gambling by some.
They argue that the movements in the stock market are not related to what is happening in the economy or the financial results of specific companies.
In the eyes of people who hold this view, large swings in the market are caused by greed and fear rather than by business fundamentals.
In this chapter, we look at the connection between prices in the stock market and real business conditions, as well as whether or not stock prices might be affected by human emotions.
Figure 9.1 shows Walmart's quarterly revenues from 2000 to 2015.
There are two obvious patterns in the figure.
Walmart's revenues have grown over time.
In early 2015, the company reported quarterly revenues of $132 billion, more than double the revenues they had in 2000.
There is one quarter each year in which Walmart earns higher revenues than any other quarter.
In every year since 2000, Walmart has sold more goods in November, December, and January than in any other quarter.
It should come as no surprise when you think about it.
Walmart sells more at the end of the year because of the Christmas season, which is nearly every retail company in the United States.
Figure 9.1 shows Walmart's revenues, but a plot of the company's net income would show similar patterns.
Walmart is the largest retailer in the U.S. and accounts for over 10% of retail sales.
Walmart's financial results are not difficult to predict partly because it is so large and partly because much of its business focuses on life's necessities.
This lesson is from Figure 9.1.
M10_SMAR3988_13_GE_C09.indd 366 follows a predictable trend.
Walmart's future performance is likely to be fairly accurate.
Walmart's stock price was higher in 2015 than it was in 2000, but it didn't follow the same upward trend as revenues did.
The seemingly random movements in Walmart's stock price, which stand in sharp contrast to the predictable movements in Walmart's revenues, is the striking difference between Figures 9.1 and 9.2.
Our answer is no.
If Walmart's stock price moved in line with its revenues, there would be a seasonal peak at the end of the year.
Walmart stock would shoot up in the fourth quarter every year for many years.
Walmart's stock would be bought by smart investors in the third quarter in order to profit from the fourth quarter runup.
If investors rushed to buy Walmart shares in the third quarter, it would put upward pressure on the stock price in the fourth quarter.
The pattern of fourth-quarter peaks in the stock price would change to a pattern of third-quarter peaks.
In the second quarter each year, investors would see that pattern and begin buying.
The seasonal pat tern would disappear because of the actions of inves tors trying to buy ahead of a peak in the stock price.
Even any pattern, PArtEE I thr InvEStIng.
If stock prices exhibit predictable patterns, the actions of inves tors will eliminate them over time.
The stock market and Walmart's financial performance are unrelated to the seemingly random behavior of Walmart's stock price.
Remember that a stock's price depends on investors' expectations about the future of the company that issued the stock When investors' expec tations become brighter, prices go up, and when they go down, prices go down.
Walmart's stock was bought by investors in 2000 with the expectation that the company's revenues would grow and peak in the fourth quarter every year.
By the year 2000, Walmart had established a long history of growth, and the seasonal pattern in revenues was well known to the invest ment community.
What would cause a sudden and potentially large change in Walmart's stock price is any sign that the firm's future financial performance would deviate from what investors expected.
Walmart's revenues in the first quarter of 2015 were higher than investors had anticipated, so that's a good thing.
Walmart's stock price would go up if investors raised their expectations about the company's future performance.
Walmart's stock price would fall if it reported financial results that didn't meet investors' expectations.
New information is something that people don't know and they don't anticipate.
When Walmart's revenues peak at the end of the year, it doesn't boost the company's stock price.
Stock price movements are largely unpredictable because of new information.
There is no connection between what happened yesterday and what happened today.
An implication of this idea is that it is very difficult for investors to earn high returns by identifying overvalued and undervalued stocks.
Spotting bargains in the stock market is difficult if the market is efficient and the information that leads you to believe that a stock is a good buy is already reflected in the stock's price.
According to the EMH, investors shouldn't expect to earn abnormal returns.
There is a positive relation between risk and return.
Investments that earn higher returns are riskier.
An investment's expected return is related to its risk.
The capital asset pricing model can be used to estimate the expected return on a stock.
There is a stock with a beta of 1.0.
The stock should earn a return that is equal to the return on the overall market if it has average risk.
If the risk-free rate is 2% in a particular year, the stock market return is 10%.
It is nearly impossible to spot stocks that earn positive abnormal returns on a consistent basis, even for highly sophisticated investors.
The efficient markets hypothesis focuses on the extent to which markets rate information into prices.
The more information that is incorporated into stock prices, the more efficient the market becomes.
Different levels of efficiency correspond to different types of information that prices may reflect.
The weak form, semi-strong form, and strong form are the levels of market efficiency.
If investors study the history of stock prices and spot a pattern that seems to repeat, their attempts to exploit that pattern through trading will cause the pattern to disappear over time.
Walmart's stock price does not exhibit predictable patterns, even though its revenues show distinct seasonal peaks, because of this idea.
Past data on stock prices are not used to predict future price changes according to the weak form of the EMH.
According to this hypothesis, prices follow a random walk, meaning that tomorrow's price change is unrelated to today's or yesterday's price, or any other day.
When investors are asked variety of "trading rules," such as buying a stock when it hits a 52 week low, and about their future expectations for then tested these rules using historical information to see what returns investors stock market returns might have earned, those expectors following these rules might have earned None of the trading rules earned abnormal returns, but the results were encouraging.
We know that market returns generate significant transactions costs.
The researchers concluded that investors would do better if they purchased a diversified portfolio and held it.
This means that investors can't consistently earn high cial models.
The company reported Iissue 3 in the report.
When you download the annual report, read it, and call your broker, the market price of the stock will have already increased, reflecting the company's latest good news, according to the semi-strong form of the EMH.
This form of the EMH was tested in a recent study.
The figure shows that for a group of companies reporting favorable earnings, abnormal returns are close to zero leading up to the announcement and beyond 2 days after the announcement.
The market responds quickly to new information.
The companies' stock price behavior was tracked before and after the announcements.
The good news that the companies were reporting was the main factor in all of the announcements.
One day before the announcement and one day after the announcement is when the earnings announcement day is.
Many firms release their financial information after the market closes.
The first chance for the stock market to incorporate the new information occurs the day after the announcement.
The average abnormal return is measured by the vertical axis in the figure.
The companies in the sample earn returns that are essentially normal, so the actual return matches the expected return.
The average company in the sample earned an abnormal return of 2.5%, with an additional 1% abnormal return occurring from day 1 to day 2.
After that point, abnormal returns return to zero.
The market quickly incorporates the good news from earnings announcements.
Many tests of semi-strong efficiency have looked at how stock prices respond to news.
Four companies that were major contractors in the space shuttle program were looked at.
A problem with the O-rings in the booster rockets made by that company caused the accident.
Within minutes of the accident, the market's initial reaction seemed to point to the same conclusion as the investigation.
Studies have examined the investment performance of professional investors.
Although the stock market may be efficient enough to prevent individual investors from earning high returns, surely professional investors who have advanced training in invest ments and who spend their entire professional lives thinking about investments can perform better.
Most studies show that even professional investors struggle to earn abnormal returns on a consistent basis, even though the conclusions from research in this area are not unanimous.
mutual fund managers don't earn returns that beat the market average by enough to cover their fees.
There isn't much persistence in mutual fund returns.
Unless you hear something before prices go up.
Stock prices quickly adjust to any information.
Corporate insiders can get private information, such as officers and directors of a corporation.
They have access to important information about the company's decisions.
Detailed information about the financial state of the firm may not be available to other shareholders.
Insiders are not allowed to trade their employer's shares prior to major news releases.
Corporate insiders can legally trade shares of their company's stock if they report the transactions to the SEC.
The public can see the required forms when they are filed with the SEC.
Corporate insiders tend to buy before significant price increases and sell before big declines, according to several studies.
If the strong form of the EMH were true, this is contrary to what you'd expect.
Market participants have inside information that they obtained or traded on illegally.
They can earn an abnormal return with this information.
Those who violate the law have an unfair advantage.
According to empirical research, those with inside information have an opportunity to earn an abnormal return, but there might be a high price attached, such as spending time in prison, if they're caught.
The concept of arbitrage is linked to efficient markets.
Let's use a simple example to show the concept of arbitrage before the exam.
If banks in New York City convert dollars into euros, it will be at an exchange rate of one dollar per euro.
In London, banks are exchanging dollars and euros at a rate of $1.25 dollars per euro.
One euro is more valuable in London than in New York.
It is possible to say that euros are cheap in New York and expensive in London.
This means that we have the same asset trading in different markets at different prices, so we would say that this presents an arbitrage opportunity.
A trader can exploit this opportunity by buying cheap euros in New York and selling them in London.
Use $1 million at a New York bank.
The value of York is $1.
The price of the euro will rise in New York if many traders start buying it.
At the prevailing exchange rate of $1.25 dollars per euro, sell the 1 million euro in exchange for $1.25 million at the bank in London.
The price of the euro should fall on the London market if many investors begin selling euros.
The trader makes an instant profit by buying euros in New York and selling them in London.
As the price of the euro rises in New York and falls in London, the opportunity to profit from these transactions will disappear.
Consider how the definition of arbitrage applies to this example.
An investor buys and sells the same asset.
In this example, the underlying asset is just a currency, so the investor is buying and selling in New York and London.
Each market has the same underlying asset.
The purchase in New York and the sale in London can be done electronically.
The purchase and sale must occur at different prices according to the second part of the definition.
In New York, $1 is worth $1 in London.
The definition of arbitrage says that the profit must be instantaneous and free of risk.
Again, this example seems to satisfy those conditions because the trader earns the profit as soon as the currency trades take place, and because they take place essentially at the same time, there would appear to be no risk involved.
There are no large differences in currency prices in the real world.
The price in New York and London will be the same.
If that wasn't true, arbitragers would exploit the price differences and push the prices closer together until there was no more opportunity.
Economists refer to this as the "no arbitrage" condition, which means that prices in financial markets will quickly adjust to eliminate arbitrage opportunities.
A key mechanism that makes markets efficient is arbitrage.
If investors have been irrationally pessimistic about the company and its stock price has gone down, the true intrinsic value of the company's stock would be $100 per share.
This represents an opportunity for market advocates.
Smart investors will buy the under valued shares of Pepsi and hedge their bets by selling shares in another similar company, like Coca-Cola, for example.
In the end, the market price and the intrinsic value of the company are the same, because of the buying pressure.
There are limits to the power of arbitrage, and it plays a very important role in setting the prices of many types of securities.
The process of buying and sellingPepsi shares is similar to the process of buying and selling otherPepsi shares.
One can't argue that they are the same investments.
Buying and selling Coca-Cola and Pepsi may be risky because they are imperfect replacements for one another.
Making these trades is expensive for an investor who does not own shares in Coca-Cola.
The investor needs to borrow Coca-Cola shares from someone else before they sell them.
Sometimes, short sales are not possible because there is no one willing to lend the required shares.
There is a risk associated with what happened in the first place.
We assumed that some investors were so pessimistic about the company that they caused it to be overvalued.
There is no guarantee that the actions of smart traders will swamp the trades of irrational traders and move the stock price towards its intrinsic value.
The "smart" traders who conduct the arbitrage trades would suffer losses if Pepsi became more overvalued.
Emh says that trading in and out is what we now turn to.
Researchers have 888-492-0 according to how often they traded.
Some patterns seem inconsistent with the theory.
What all of these anomalies have in common is that they reveal trading strategies that earned higher returns than the most active traders.
Brad Barber and terrance ment results show that certain months or days of the week may be better for investing.
There is an incentive for investors to sell stocks that have gone down in value during the year, and investors who recognize that incentive are likely to sell in December as the tax year comes to a close.
When a firm's stock falls, the market cap gets smaller.
If investors have a tax incentive to sell their loser stocks in December, and they tend to be smaller than average, then their prices may be temporarily depressed, and they may rebound in January.
There is at best mixed evidence that this explanation can account for the puzzling behavior of small stocks in January.
Several studies have shown that small firms earn higher returns than large firms even after taking into account the higherbetas typical of most small firms.
In the United States, as well as in many stock markets around the world, this tendency has been documented.
The stock prices react to earnings announcements.
The study showed that stocks with good earnings had abnormal returns for a day or two.
The tendency for stocks to drift after earnings announcements in the same direction as the initial reaction was reported by several older studies.
When companies reported better-than- expected earnings, their stock prices jumped immediately, earning positive abnormal returns.
These firms' stock prices earned positive abnormal returns for weeks or even months after the earnings announcements.
Negative abnormal returns continued for several months after the initial announcement of earnings.
When bad news is reported, investors don't fully appreciate how bad the news is, so stock prices take a long time to adjust to a new level.
This pattern makes it possible for investors to earn abnormal returns by buying stocks that have recently issued good earnings news or by short selling stocks that have recently delivered poor earnings results.
The post earnings announcement drift pattern is shown in Figure 9.4.
The ver tical axis shows the cumulative abnormal return from 52 weeks prior to the earnings announcement to 52 weeks after the announcement.
There are two types of companies that are tracked in the figure--companies that announce better-than-expected earnings and companies that announce worse-than expected earnings.
The red line tracks abnormal returns for the "bad news" stocks while the blue line plots cumulative abnormal returns for the sample of "good news" stocks.
When firms announce good news, their stock prices move quickly, as shown by the jump in the blue line at week 0.
When firms reveal that their earnings are below expectations, their stock prices move down immediately, as shown by the drop in the red line at week 0.
The pattern that an efficient market should produce is the rapid initial reaction.
The investors underreact to the news contained in earnings announcements.
The blue and red lines show trends, with the blue line slowly rising and the red line slowly falling.
The initial reaction to the earnings announcement was not large enough, and stock prices are adjusting slowly to the information in the earnings announcement.
The adjustment process creates opportunities for investors.
When a company announces positive earnings news, investors who buy the stock earn abnormal returns.
According to Figure 9.4, investors who closely monitor earnings announcements and buy stocks after firms announce better-than- expected returns will earn a return that is 2% higher than one would expect given the risk of the stocks being purchased.
The shares of com panies that announce poor earnings results can be short sold by investors.
The stock prices following the earnings announcement are not in line with the predictions of the EMH.
The momentum anomaly is a slight variation on this story.
There is a tendency for stocks that have gone up recently to keep going up or for stocks that have gone down recently to keep going down.
It's easy to see the connection to earnings announcement drift.
It is common for good news to leak out before the official earnings announcement when a company has a good quarter.
When the firm releases good news, the price goes up more, but then it goes down for a while.
When a company releases good earnings news, its stock price goes up, and then it goes up again after the announcement.
Positive momentum shows up in these stocks.
The same thing happens when a company has bad quarters.
An investor following a value strategy might calculate the P/E ratio or the ratio of market value to book value for many stocks, and then buy the stocks with the lowest ratios (and perhaps short sell the stocks with high P/E or market-to-book ratios).
Studies have shown that value stocks are more likely to perform better than growth stocks.
In the United States and most stock markets around the world, this pattern has been repeated decade after decade.
Rational explanations for the pattern observed are offered by each new discovery that appears to violate the EMH.
The most common explanation for market anomalies is that the stocks that earn high returns are riskier than the rest of the market.
M10_SMAR3988_13_GE_C09.indd 373 is not surprising since practitioners agree that small firms are riskier than large firms.
According to the CAPM, if a small stock has a 2.0 and a large stock has a 1.0, the small stock should earn more than the Treasury bills that the large stock earns.
The small-firm effect is known as an anomaly because small stocks seem to earn higher returns than they can justify.
If a better risk measure were available, the difference in returns between small and large stocks could be attributed to differences in risk.
Some trading rules may appear to earn high returns simply as a matter of chance, which is an explanation for market anomalies.
The Super Bowl anomaly is one of the more amusing market anomalies.
The stock market will rise if the team winning the Super Bowl is one of the original National Football League teams.
The stock market will fall if there is no change.
The "trading rule" correctly predicted the direction of the market more than 80% of the time.
Most people agree that the connection between the Super Bowl winner and the stock market is not likely to happen again in 48 years.
Most market anomalies are just an artifact of random chance according to some EMH advocates.
Evidence shows that anomalies such as the small-firm effect, momentum, and the value effect are common in most markets around the world.
In contrast to traditional finance, which starts with the assumption that investors, managers, and other actors in financial markets are rational, behavioral finance says that market participants make systematic mistakes and that those mis takes are linked to cognitive biases that are hard-wired into human nature.
We are going to discuss the basics of behavioral finance and how they may help explain market anomalies.
Give a brief description of each of the following.
The efficient markets hypothesis has been influential in financial markets for more than 40 years.
A large body of academic research supports the idea that asset prices fully reflect all available information.
The market is efficient according to a recent study.
They know that any time and performance of 22 U.S. mutual funds is spent researching individual securities, it will only serve to increase the fund's expenses, which will drag down investors' returns.
The concept of market efficiency is supported by a lot of evidence.
This research shows anomalies and draws from research showing negative abnormal returns on cognitive psychology to offer explanations.