Behavioral Finance and Human Interaction a Study of the Decision-Making
Processes Impacting Financial Markets
Understanding the Stock Market
Contrasting Financial Theories
Flaws of the Efficient Market Hypothesis
Financial Bubbles and Chaos
The stock market’s dominant theory, the efficient market hypothesis (EMH) has been greatly criticized recently for its failure to account for human errors, heuristic bias, use of misinformation, psychological tendencies, in determining future expected performance and obtainable profits.
Existing evidence indicates that past confidence in the EMH may have been misdirected, as the theory’s models do not show a thorough understanding of trading operations in a realistic light.
Researchers have suggested that a variety of anomalies and inconsistent historical results demand that traditional financial theories, namely the EMH, be reconstructed to include human interaction as a key decision-making process that directly affects the performance of financial markets.
This research paper aims to determine whether or not there is a need for a refined financial model that incorporates the behavior of the stock market’s investors.
When explaining the efficient market hypothesis (EMH), Fama (1970) described three types of EMH: the weak type, the semi-strong type, and the strong type.
The strong type indicates that stock prices are reflective of all available information, including both public and private data. However, Seyhun (1986, 1998) has gathered significant evidence to support his theory that insider information has enabled many investors to capitalize when trading based on data that is not included in stock prices.
According to the semi-strong type (Fama, 1970), security prices reflect all publicly available information. This type maintains that undervalued or overvalued stocks simply cannot exist, as new information is incorporated into stock prices quickly and efficiently. However, intraday data prompted tests that proved public information could have a tremendous effect stock prices in a matter of minutes (Patell and Wolfson, 1984).
The weak type indicates that past prices or returns are a reflection of future prices or returns. Studies revealing the inconsistent performance of technical analysts are used to support this theory. However, Fama (1991) showed that the evidence of predictability of returns disproves the weak form.
In the past, the EMH has been the dominant force in providing a theoretical basis for investment market research. Researchers revealed that prices appeared to follow a random walk model and patterns in returns were insignificant. However, when research shifted from predicting prices based on historical prices to forecasting based on variables, including dividend yield (Fama & French ), the inadequacies of existing models came into question.
Many researchers have suggested that stock prices are predictable on a fairly consistent basis, which has caused a great debate over the accuracy of the EMH. EMH supports hold that the predictability of stocks is the result of time-varying equilibrium expected returns generated by rational pricing in an efficient market that makes up for the level of risk assumed in the market (Fame & French, 1988).
Those who believe that the EMH is inaccurate say that the predictability of stock prices shows that psychological factors, social events, human errors, and the irrationality of investors play a huge role in the stock market, which the EMH does not account for.
When certain anomalies, such as the January effect, the weekend effect and panic effect, were discovered to have a major impact on the stock market performance, the EMH became a controversial theory. Such events were labeled as anomalies because they were impossible to explain in the EMH.
As a result, extensive research has been undertaken to prove that information alone does not determine stock prices. Researchers have been force to reexamine the accuracy of the EMH and look for alternative means of predicting the stock market performance.
As all types of the EMH appear to have flaws and anomalies have been discovered, existing research suggests a strong need for a revised financial market theory. This research paper will examine the history of the stock market, existing research on various anomalies, the behavior patterns of its investors, and the flaws of EMH to determine the extent of the need for a revised financial market theory.
III. LITERATURE REVIEW
A. UNDERSTANDING THE STOCK MARKET
When the stock market is mentioned, most people picture the New York Stock Exchange’s (NYSE) immense trading floor, a widely publicized area with well-dressed traders and a lot of action. However, this is only a small portion of what the stock market truly is.
In the United States, more than 50 million people own stock directly. More than 100 million investors take an indirect role in the market, whether it is through insurance companies, banks or pension funds. Therefore, it is of utmost importance to understand the stock market to figure out exactly how it works.
Nearly 3,000 companies have their stocks listed on the New York Stock Exchange (Gross, 1997). These companies are located across the United States and around the world. They produce automobiles, ballet shoes, entire networks and much, much more.
They manage real estate and livestock. They operate shopping malls and restaurant chains. All of these industries form the core of our system of private enterprise. As a result, the stock market affects every single person in America and every single person affects the market. This chapter will introduce the stock market in an effort to explain how it works.
The Earnings of a Company
A company’s earning performance is the single most influential factor in the stock market (Wurman, et al., 1990). Its earnings gauge its profitability, which describes the positive difference between the sale of products or services, and the cost of production. Most businesses report their earnings every fiscal quarter.
A company’s earnings information usually includes the quarter’s sales figures, profit, and average amount of shares, as well as the figures for the previous year. The earnings per share figure are calculated by dividing the net profit by the average amount of shares.
Most investment strategies rely on the ability to successfully evaluate a company’s earnings performance. In addition, strategies focus on comparing the earnings performance of multiple companies in the stock market.
A crucial factor in comparing companies is the earnings per share. Earnings Per Share and Relative Strength Rank are helpful factors in enabling investors to identify companies with strong earnings and price performance.
Many investors identify companies with strong earnings and price performance by identifying industry groups that are outperforming the market. In many cases, stocks from the same industry group will show similar price movement, mainly because developments within a particular industry, including technology and product innovation, are similar.
The major investors in the stock market play a large role in the market’s performance. There are several major investors.
Mutual funds involve investors that buy shares in professionally managed funds that invest in many different vehicles, including stocks, bonds, futures and options (Wurman, et al., 1990). A great deal of mutual fund assets comes from IRA and retirement accounts.
Banks are a rapidly growing sector of the stock market, as banks buy many different forms of securities as part of their client financial services.
Companies, unions, government organizations, and private parties typically create pension funds as a means of investing in securities to finance the benefits received by retired workers.
Insurance companies are considered a major investor in the stock market, as premiums received from policyholders are invested in a variety of vehicles, including stocks.
Lastly, individuals are a large part of the stock market, managing their own accounts, and making their own decisions about which stocks to buy and sell. In many cases, brokers, money managers, and investment advisors often represent individual investors.
When these major investors make decisions and choices regarding investing in the stock market, they wield great influence over the prices of stocks. Institutions, including mutual funds, pension funds, and banks, purchase and sell stocks in large quantities. These large transactions significantly push prices up or down depending on the amount of buying or selling.
Like all products, stocks are subject to the laws of supply and demand. When demand for a stock increases, its price typically increases. On the other hand, stock prices tend to decrease when there is an abundant supply of shares or less demand.
Macro Economic Indicators
There are a variety of macro economic factors that have a strong influence on the stock market. The Federal Reserve discount rate, which is the interest the Federal Reserve charges its member banks to borrow money, has a direct effect on inflation, the economic growth, and stock prices.
Basically, when the discount rate changes, the cost of borrowing money changes, as well. Therefore, if the discount rate drops, banks borrow more money, which increase the supply of money. If it increases, the opposite occurs.
The rate of unemployment is another key macro economic factor. For example, increasing employment is considered bullish for the economy, but if the rate goes down too much, the cost of employing people rises. Higher labor costs mean higher costs of production, which translates to higher inflation. Higher inflation means higher interest rates, and higher interest rates are typically bad for stocks.
Retail sales can serve as a measure of the economy’s strength. Low retails sales often mean that the economy is weak, which could cause a drop in the Federal Reserve interest rates.
The Consumer Price Index (CPI) measures the average change in the prices that consumers pay for a fixed amount of goods and services. The Federal Reserve monitors this data and uses it as a key measure if inflationary pressure on the economy. As a general rule, if the CPI’s value increases, the money supply will tighten.
The Gross Domestic Product (GDP) measures economic activity. It is the output of all goods and services created by labor and property in the United States. GDP provides important information on the current economic climate.
Characteristics of Winning Stocks
According to many research studies, there are several characteristics of winning stocks. According to William O’Neil (1988), a professional investor: “The first step in learning to pick stock market winners is for you to examine leading winners of the past to learn all the characteristics of the most successful stocks.” recent study shows that, over the past four decades, the top performing stocks have shown seven basic characteristics (Gross, 1997). First, a company consistently has increases in recent quarterly earnings per share of at least 25%. Its three, four or five-year annual earnings per share growth rate are greater than 25%.
Many successful investments are made when a stock hits a new high and is emerging from a period of price consolidation. New companies with new products or services and improving sales are often successful.
Companies with a total number of shares outstanding between five and 30 million are often good bets, as are the top performing leading stocks in leading industry groups. In addition, stocks that are owned by at least one quality institution have shown promise. When a stock performs well in the general market daily, it is usually headed in a good direction.
According to William O’Neil (1988): “The stocks you select for purchase should show a major percentage increase in the current quarterly earnings per share when compared to the prior year’s same quarter.”
Many of the most successful stocks have shown a significant percentage increase in the current quarterly earnings per share when compared to the same quarter the year before. In a forty-year study, three out of four stocks showed earnings increases averaging more than 70% in the quarter prior to a major price advance (Wurman et al., 1990). The one that did not show a substantial current quarter increase did so in the following quarter.
According to William O’Neil (19880, “Each year’s annual earnings per share for the last three, four or five years should show an increase over the prior year’s earnings.”
While evaluating a company’s quarterly earnings is important, it may be even more important to evaluate a company’s annual compounded earnings growth rate. A recent study shows that the majority of top performers had a three, four or five-year average annual compounded earnings growth rate of 24% just before their greatest price moves.
When buying stocks, investors are encouraged to look for companies demonstrating consistent long-term growth, or a three to five-year annual growth rate greater than 25%.
According to William O’Neil (1988): “It takes something ‘new’ to produce a startling advance in the price of a stock.”
Almost the entire group of top performing stocks studied in the 40-year period experienced something ‘new’ just before their major price advances. For example, a new product or service many have significantly increased sales and earnings. This is due to the resulting increased consumer demand.
In addition, nearly all of these stocks were at or near a new price high right before their greatest price movement. However, studies reveal that less than 2% of investors will purchase a stock when it is at a new high.
The Law of Supply and Demand
According to William O’Neil (1988): “The law of supply and demand is more important than all the analyst opinions on Wall Street.”
The law of supply and demand applies to all goods and services, including stocks. If a stock’s supply is small and there is a lot of demand for that stock, the stock’s price will increase.
If a company has a lot of numbers of shares outstanding, it would take a large buying demand to increase the stock price. Conversely, companies with a small or moderate number of shares outstanding require only a moderate amount of buying demand to markedly influence their stock’s price.
When examining the stock market, it is important to understand the concept of short selling, which is basically a sort of reverse stock buying. Most people buy a stock hoping that it will go up in price.
However, with short selling, investors sell the stock before buying it in the hopes that it will go down in price. According to William O’Neil (1988): “Short selling is a topic few investors understand, and in which even fewer succeed.”
In short selling, an investor borrows shares from a broker, sells them in the open market and gets the profits from the sale. The investor hopes that the stock will go down in price so that he can buy the stock back at a lower price. He then replaces the shares borrowed from the broker and makes a profit. Investors tend to sell short if they believe that the market is headed for a dramatic decline or that a stock is about to drop.
A great deal of financial theory is based on the assumption that humans will act rationally and take into account all available financial data when making decisions. However, research shows that human behavior is often irrational and unpredictable. Several incidences of irrational behavior and human errors have been reported in research studies in recent years.
For example, in “Against the Gods,” Peter Bernstein reported that evidence “reveals repeated patterns of irrationality, inconsistency, and incompetence in the ways human beings arrive at decisions and choices when faced with uncertainty. (p. 224)”
According to William O’Neil (1988): “Be objective and recognize what the marketplace is telling you…. The fastest way to take a bath in the stock market or go broke is to try to prove that you are right and the market is wrong.”
The current condition and direction of the overall market heavily influences a stock’s performance. Therefore, investors need dependable tools to determine exactly what type of market they are in. The market could be bullish, with rising prices, or bearish, with decreasing prices.
Stock Market Changes
Over the past few years, the stock market has become one that is price volatile and driven by liquidity. Today’s stock market seems to have little regard for fundamental values. Instead, it seems to react more to the emotional mood of its investors, swinging in different directions at a fast pace. As a result, researchers today have developed certain indicators that aim to weigh emotion in the market to determine when it could shift.
Put/Call ratio is the amount of put options traded divided by the number of call options traded (Gross, 1997). When large amounts of call options are traded, it shows that investors are confident in the market. However, when large numbers of put options are traded, it shows a lack of investor confidence.
The Option Volatility Index (VIX) relates to the premium paid for options on the OEX. It is expressed as a percentage of prices. The VIX usually goes down as the market goes up and goes up as the market goes down. Researchers say that deviations from the expected behavior are the result of human emotions.
Another tool that is used to weigh emotion in the market is the tick number, which refers to the number of stocks trading on the NYSE trading on an up tick, which means they are trading above the preceding price, minus the number of stocks trading on a down tick, which refers to stocks trading below the preceding price. High positive ticks usually occur at intra-day highs while high negative ticks tend to occur at intra-day lows.
According to the FirstCapital Corporation Web site (2002): “We relate the extreme tick values to an index price such as the S & P. 500 price. Repeated extreme tick numbers around the same price on the index within one or two days, indicate a resistance level above the market or a support level below the market.
When the market trades thru the possible support or resistance level on a much reduced tick number it means that there is no support or resistance level and the market will continue to move in the same direction.”
There are several other measures of market extremes, including the percentage of stocks above various moving averages and the number of stocks above various averages by one or two standard deviations.
It could be expected that investors might feel more optimistic after the market closes up, as opposed to when the market closes down.
Based on the trading history from 1950 to 2000, if an investor had held the S&P500 index for this entire time period, he would have seen a return of 491%. According to recent statistics, investor emotion is the greatest forecaster of the stock market today, averaging 27% per year for the past five decades with half the risk of the S&P500 (Palisades Research, 2002).
Assuming that emotions truly dictate the stock market performance,
On the Palisades Research Web site (2002), the company analyzes a day after the market closed up and a day after the market closed down, separately.
We take the sum of the next day’s percentage change not counting for dividends and commissions or compounding. Buying after up days returned 875%. Buying on up days and selling short after down days returned 1,265%. If you add in compounding, the holder (buy and hold) of the S&P index would have gone from $100 in 1950 to $8,390 by October 2000. The emotional trader would have gone from $100 to $19,592,300. The difference looks enormous but it is only a compound annual rate of 27.1% verses the S&P500 50-year rate of 9.1%, about 3 to 1!”
The worse loss for the long-term holder of the S&P index took place in 1973-1974 with a decrease of nearly 50% and a recovery period of over seven years (Palisades, research, 2002). The emotional trader’s worse drop took place in 1984 with a decrease of 24.7% and a recover period of over two years. These worst cases did not coincide with each other, suggesting that there must be some synergy in combining long-term investing and a good emotional-based program.
This shows that show that emotion has a very significant effect upon the stock market. While emotional force is no the single driver of the stock market, it is a powerful factor that must be recognized.
According to Sigmund Freud: “The less a man knows about the past and the present, the more insecure must be his judgment of the future (Palisades Research, 2002).”
The stock market is viewed as an efficient and rational model, despite the fact that various outbreaks of hysteria have influenced it tremendously throughout history (Gross, 1997). Stocks have been massively undervalued and overvalued by both individual and professional investors.
As a result, the fundamental theories of the stock market have been questioned, as have the intrinsic value upon which shares are supposedly based. When stocks are overvalued, the market usually corrects them. However, these revaluations have resulted in some of the most horrific stock market crashes in history, with dire consequences.
Fundamental analysis basically values shares according to three factors (O’Neil, 1988):
the state of the economy, the state of the industry in question, and the earning power and potential performance of a specific company.
Fundamental analysts seek stocks that are, in their opinion, overvalued or undervalued, and then sell or buy these shares in the hope of turning a profit when more investors realize that the stock is valuable.
Rational pricing of stocks is very important for resource allocation and to ensure that prices will eventually correspond to their long-term competitive equilibrium (Journal of Economic Perspectives, 1990). Speculative bubbles show that the pricing of stocks is often irrational. The role of expectations in the pricing of securities is often blamed for this irrationality.
Eugene Fama, when looking at the 1987 crash from a rational pricing perspective said that all explanations were “driven by a change in expectations about conditions.” Still, no good reason has been found for expectations to change initially.
It appears that investors are not as concerned about market fundamentals as they are with the behavior of their peers. “If an ordinary rational investor had good reason to believe that other investors would not behave rationally then it might well be rational for him to adopt a strategy he would otherwise have rejected as irrational.”
For example, if an investor feels an air of panic around him over the climate of the stock market, he too may panic. This can result in a stock market crash, as large numbers of investors panic.
During the 1987 Wall St. crash, when $1 trillion was lost in a single day, The Economist blamed the “psychology of the mob” for the bull market, and the crash that followed. “Just before the stock market crash, commodity analysts were saying that metal prices were rising because of ‘market fundamentals’. Come the crash, they threw their fundamentals out of the window, and indulged in old fashioned panic instead (The Economist, 1987)”
One of the most frustrating problems that researchers face is that “there is no scientific way to show that security prices are rational or irrational.” The fundamental economic theory accepts that all investors act rationally. However, in many cases, rationality breaks down, and this economic theory has nothing to do with the market. Some of these cases include the Great Depression, Black Monday, and the 2000 Tech Boom.
CONTRASTING FINANCIAL THEORIES
The Efficient Market Hypothesis (EMH)
When investors put their money in the stock market, they hope to generate a return on their money. It is the ultimate goal of every investor to outperform or beat the market.
In 1970, Eugene Fama coined the term “market efficiency, which suggests that at any given time, prices completely reflect all available information on a given stock (Heakel, 2002). Therefore, according to the efficient market hypothesis (EMH), it is impossible to beat the market because prices already incorporate all relevant information. This means that no one has access to data that is not available to everyone else.
EMH has caused a great deal of controversy and debate amongst researches and financial professionals, largely because its implications are profound. The majority of investors that invest in the stock market assume that the stocks they are buying are worth more than they are paying for them, while the stocks they are selling are worth less than they are selling them for.
However, if the EMH is correct, then buying and selling stocks in an attempt to outperform the market is actually based on luck and chance rather than skill and knowledge.
Fama’s theory argues that, in a market that is active and includes knowledgeable investors, stocks will be appropriately priced and reveal all available information (Heakel, 2002, Fama, 1995). If a market is efficient, no information or analysis can be expected to result in outperformance of an appropriate benchmark.
An efficient market is best described as one in which large groups of educated investors actively compete with one another, each trying to predict future market values of individual stocks. In an efficient market, no investor has an unequal or unfair advantage over another, as all are supplied with the same information.
This competition creates a situation in which actual prices of individual stocks already reflect the effects of information based both on past events and expected future events. Thus, in an efficient market, at any time the actual price of a security can be seen as a good estimate of its intrinsic value.’
According to Robert Higgins, author of Analysis for Financial Management (1992, p. 147), “Market efficiency is a description of how prices in competitive markets respond to new information. The arrival of new information to a competitive market can be likened to the arrival of a lamb chop to a school of flesh-eating piranha, where investors are – plausibly enough – the piranha. The instant the lamb chop hits the water, there is turmoil as the fish devour the meat. Very soon the meat is gone, leaving only the worthless bone behind, and the water returns to normal. Similarly, when new information reaches a competitive market there is much turmoil as investors buy and sell securities in response to the news, causing prices to change. Once prices adjust, all that is left of the information is the worthless bone. No amount of gnawing on the bone will yield any more meat, and no further study of old information will yield any more valuable intelligence.”
According to the random walk theory, price movements do not follow any patterns or trends. This theory states that past price movements cannot be used to predict future price movements. This theory dates back to 1900, when French mathematician Louis Bachelier concluded, “The mathematical expectation of the speculator is zero.” He stated that this condition was “fair game.” However, Bachelier’s thinking was so advanced that it was ignored for decades. In 1964, his dissertation was translated into English and published.
The random walk theory states that any investment strategies that try to consistently beat the market are doomed to fail. The EMH suggests that, due to the high transaction costs involved in portfolio management, it would be more profitable for an investor to invest in an index fund, which is a portfolio of investments that are weighted the same as a stock-exchange index in order to mirror its performance.
There are three forms of the efficient market hypothesis
The “weak” form states that all past market prices and data are fully reflected in securities prices. Therefore, technical analysis is obsolete.
The “semistrong” form states that all publicly available information is fully reflected in securities prices. Therefore, fundamental analysis is obsolete.
The “strong” form states that all information is fully reflected in securities prices. Therefore, insider information cannot give an investor an advantage.
The stock market is played by thousands of educated, well-paid investors, who actively seek under and over-valued securities to buy and sell. Therefore, the more players there are and the faster information is available, the more efficient a market should be, according to the EMH.
Role of Investors in an Efficient Market
To fully understand the EMH, it is important to look at the potential role of investors in an efficient market. According to the EMH, the role of the investor involves analyzing and investing according to an individual’s tax considerations and risk profile (Tini-C, 1979, pp. 141-153).
Financial analysis involves a variety of factors, including age, risk profile, tax bracket, and employment. In an efficient market, an investor’s role is to create a portfolio to meet individual needs, rather than striving to outperform the market.
Some EMH supporters think that it is impossible to outperform the market yet others believe it is possible if stocks are divided into categories based on risk factors (p. 143). For example, these investors view small stock as riskier investments with higher returns. They may also believe that value stocks are riskier than growth stocks and offer higher returns.
Many financial managers insist that the markets are not efficient, which is understandable since their jobs rely on the belief that they can outperform the market. Financial media outlets assume this position, as well, as they make a profit from investors who pay money for financial data.
Even with the thousands of studies on the EMH, it is difficult to determine whether outperformance is the result of skill or chance. For instance, with thousands of financial managers, it can be expected that one or more will significantly outperform the market. Still, this presents a challenge to investors– to identify an outperformer before it happens, rather than in hindsight.
It must also be noted that even the strongest performers of one period can underperform in the future. Many studies reveal that there little or no correlation between strong performers from one period to another. The lack of consistent performance persistence among investors supports the EMH.
In an efficient market, prices become random instead of predictable, so no investment pattern can be distinguished. A planned approach to investment, therefore, will not be successful.
The classic investment theory is based on the belief that all investors act rationally based on consideration of available information (Neil, 2002, p. 18). This means that they weigh the pros and cons of their options, consider all probable outcomes and choose the best solution.
Rather than making quick decisions, they examine the long-term picture and stick to their original plans. Meanwhile, they are making systematic deposits to their portfolios to take advantage of dollar cost averaging. While they are aware of current conditions, they do not act hastily based on the economic climate.
Behavioral finance theories view investor strategy in a different light (Neil, 2002, p. 18). Behavioral finance takes into account that investors are human being and therefore are not always completely rational. They do not always look at all available information and rarely approach decisions in a systematic, practical manner. Often, they misinterpret information and act in the wrong way with the right information.
It is possible that the outperformance of value investing is a result of human interaction, such as the irrational overconfidence shown by investors in innovative growth companies or the pleasure investors take in owning growth stocks. Many researchers believe that these human errors are consistent, predictable, and can be exploited for profit.
There are several basic theories of behavioral finance:
Increasing levels of confidence have not been proven to show correlation with greater success.
Many investors believe that they can consistently time the financial markets even if evidence shows that they cannot.
Investors tend to place too much weight on recent experience.
People have a tendency to view other people’s decisions as the result of disposition but view their own choices as rational.
Research suggests that markets often fail to behave as they should if trading were actually dominated by fully rational investors. This suggests that markets are not completely efficient.
Behavioral finance experts aim to explain how emotions and human errors influence investors and their decision-making processes. Researchers believe that the study of psychology and other social sciences can be useful in understanding the efficiency of financial markets, as well in explaining stock market anomalies, market bubbles, and crashes.
Behavioral finance provides great insight into investor actions. Behaviorists believe that investor behavior is neither random, nor totally irrational. Instead, they believe that non-rational behavior falls into predictable patterns and can be prevented. As a result, behavioral finance gives investors the tools and techniques to counteract destructive decisions.
Research suggests that investors who take the time to monitor price and volume changes in the general market indices on a daily basis are more likely to be successful in the stock market. The most popular market indices are the NASDAQ Composite, S&P 500, and the Dow Jones Industrial Average.
Analyzing the price and volume activity of the market indexes is a sensible way to determining market direction without relying on the various conflicting opinions of financial experts.
Psychographics is a term used in behavioral finance to describe the psychological characteristics of individuals and describe an individual investor’s strategy and risk tolerance (Tini-C, 1979, p. 181). According to research, an investor’s background and past experiences play a key role in his investment decisions.
The Bailard, Biehl & Kaiser Five-Way Model places investors in five categories (Investor Home, 1999). “Adventurers” are risk takers and are usually difficult to advise. “Celebrities” prefer to be where the action is and are easy targets for brokers. “Individualists” avoid extreme risk, do their own research, and act rationally. “Guardians” are usually older, more careful, and more risk-averse. “Straight Arrows” fall in between the other four personalities and tend to be more balanced than the other types.
In summary, people trade for both cognitive and emotional reasons. They trade because they think they have information when they have nothing but noise, and they trade because trading can bring the joy of pride. Trading brings pride when decisions turn out well, but it brings regret when decisions do not turn out well. Investors try to avoid the pain of regret by avoiding the realization of losses, employing investment advisors as scapegoats, and avoiding stocks of companies with low reputations.” (Statman, 1988, p. 318)
According to Jack Treynor, author of “What Does It Take to Win the Trading Game?” (1981), ” a third view of market efficiency, which holds that the securities market will not always be either quick or accurate in processing new information. On the other hand, it is not easy to transform the resulting opportunities to trade profitably against the market consensus into superior portfolio performance. Unless the active investor understands what really goes on in the trading game, he can easily convert even superior research information into the kind of performance that will drive his clients to the poorhouse… why aren’t more active investors consistently successful? The answer lies in the cost of trading.”
THEORIES OF BEHAVIORAL FINANCE
Behavioral finance is specifically dedicated to understanding how human interaction and human errors can influence investors and the financial decision-making process. Research proves that the study of psychology can strongly influence the efficiency and predictability of financial markets, as well as explain many stock market anomalies, market bubbles, and periodic crashes.
For example, many researchers say that the outperformance of value investing is the direct result of a financial investor’s irrational overconfidence in innovative growth companies, as well as the result of an investor’s pride in owning growth stocks. These patterns show that human flaws have an impact on the financial market and should be taken into account in decision-making processes.
Many behavioral finance experts believe that human errors are consistent, predictable, and can be exploited for profit.
The Prospect Theory
Amos Tversky and Daniel Kahneman are recognized as experts in the field of behavioral finance. In 1979, the duo coined the phrase “prospect theory,” which suggested that, as opposed to expected utility theory, individuals tended to assign different weights to gains and losses and to different ranges of probability (Kahneman, et al., 1982).
In addition, they discovered that most people become far more upset about prospective losses than they are pleased about equivalent gains. For example, if an investor loses $1,000, he will find this experience twice as distressing as he would find a $1,000 gain pleasurable.
In addition, Tversky and Kahneman (1979) discovered that investors tend to respond differently when presented with equivalent situations, depending on whether the situations involve losses or gains.
According to the duo’s 1979 article, “Researchers have also found that people are willing to take more risks to avoid losses than to realize gains. Faced with sure gain, most investors are risk-averse, but faced with sure loss, investors become risk-takers. (Kahneman, et al., 1982, p. 211).”
Fear of Regret
Meir Statman, a Santa Clara professor, is a renowned expert on behavior, which is known as “fear of regret,”(1988) which studies the human tendency to feel disappointment or sorrow after making an error. According to this theory, individuals who are selling a stock tend to be emotionally affected by the selling price of the stock.
Statman (1988) believes that many investors avoid selling stocks that have decreased in value because they do not want to experience the negative feelings associated with taking a loss on a security. In addition, many investors do not want to admit their human error to themselves, their companies, their accountants or any other parties involved.
Additional research suggests that many individuals, when investing their money, will go along with the majority when making investment decisions, possibly in an effort to avoid feeling regret if their investment prove to be bad ones.
For example, an investor will feel less distressed over an investment loss if it is one that a large group is experiencing, as well. If he invested in a stock that the majority had little confidence in, it will be harder for him to rationalize his mistake.
The same theory applies to money manager and financial investors. Many financial professionals prefer well-known stocks and companies because they fear the ramifications of underperformance.
Irrational Risk-taking Strategies
As a whole, humans take risks based on recent experiences and rely too much on recent trends that have proven profitable. They will often be optimistic and take risks when the market is up but will show hesitation went it is down. However, in many cases, the trends that influence them are at odds with long-term averages and statistical data.
Robert J. Shiller, a professor at Yale, discovered, during a study, that when the Japanese stock market was at its peak, only 14% of investors predicted that there would be a crash (2003, p. 313-314). However, after it did crash, 32% of investors believed that there would be another.
Many financial researchers believe that the majority of investors are too optimistic or too pessimistic about the stock market’s performance, it is a good sign that the opposite of what they believe will occur.
Behavioral finance studies suggest that individuals often see order where there is none and mistakenly view accidental success as the result of skill. For example, Tversky proved that a basketball player with a “hot hand” is not any more likely to make his next shot than he is at any other time (Kahneman, et al., 1982, p. 336). However, despite mathematical statistics, many people find it difficult to accept the fact that luck does not involve skill.
While basketball players may be overconfident in their ability to make the next shot, investors may show overconfidence in the stock market, particularly if they have some knowledge about it. Still, the fact remains that even with increased levels of confidence, there is no greater chance for success.
Many investors, amateurs and professionals alike, fall prey to important logical fallacies and psychological failings (Dreman, 1998, p. 232-250). These psychological pressures have an effect on the decisions of individuals under conditions of uncertainty. They are powerful forces that cause many people to repeatedly make the same mistakes.
Most investors are not good intuitive statisticians, especially when they are making decisions under difficult conditions. They often fail to calculate odds properly when making investment decisions, which leads to consistent errors.
According to Nobel laureate Herbert Simon, people are overwhelmed by too information and react consciously to only some of it. Simon asserted that when bombarded with information, people digest only a small part of it and tend to come to a different conclusion from what the entire information would suggest (p. 238).
Research shows that, rather than calculating the actual odds of a given outcome, people react to an overload of information by taking shortcuts. Psychologists call these shortcuts “judgmental heuristics (p. 240).” For example, when driving along a superhighway, people tend to focus only on operating the vehicle, on opposite traffic, and on traffic signs, rather than taking in everything that is going on around them.
These selective processes are used when dealing with probabilities. When making decisions and judgments, most people are intuitive statisticians who apply mental shortcuts that work well the majority of the time. For example, we assume that we have a better chance of survival when driving 50 miles per hour than we would at 90. We assume that a professional basketball player will outperform an amateur one. There are countless examples of judgmental heuristics.
These simplifying processes can be helpful in many cases. Unfortunately, however, they can lead to systematic mistakes in investment decisions because they make the investor believe the odds are significantly different from what they actually are.
Daniel Kahneman andAmos Tversky refer to one of the most common cognitive biases as “representativeness. (Dreman, 1998, p. 252)” According to the professors, it is a natural human tendency to draw analogies and see identical situations where there are actually many differences.
When playing the stock market, this can cause many human errors. Many people view two companies or market environments as the same when they are actually very different. For example, when the Dow dropped 742 points during the 1987 crash, the media headlines screamed, “Is this 1929? (p. 252)” Without realizing that the two events were very different, people used heuristical bias and pulled out all of their money. However, within weeks, the economy showed signs of improvement, unlike in 1929.
Investors who used the representativeness bias, pulling out their investments, missed out on a great buying opportunity. Within a decade, the market quadrupled from that time.
The representativeness heuristic involves many common decision-making errors. Kahneman and Tversky defined this heuristic as a subjective judgment of the extent to which the event in question “is similar in essential properties to its parent population” or “reflects the salient features of the process by which it is generated.” People tend to judge probabilities “by the degree to which A is representative of B, that is, by the degree to which A resembles B (p. 257).” And B. can represent a number of things. For example, A could be the similarity or representativeness in people’s minds of the 1987 crash to B, which would be the 1929 crash.
Representativeness bias occurs constantly in the marketplace, as investors put undue weight on the similarities between events. As a result, this form of heuristic bias leads to major investor errors in decision-making.
The representativeness heuristic can affect a company or individual stock as much as the entire stock market. In 1993, Dell Computer lost 50% of its value over a period of a few months, dropping from a market capitalization of $4.6 billion to $2.2 billion (p. 259).
It dropped for several reasons, including weak earnings and market repositioning. Because of Dell’s poor performance, investors grew wary of similar industry leaders, namely IBM and Digital Equipment Corporation (DEC), because these companies had weak earnings, too.
Although these three companies were similar in many ways, they were also very different. Yet people saw that all three were in the same industry and suffering. But the three companies had different products and management. It turned out that Dell outperformed all of these companies, turning itself around to become a key player in the personal computer industry. By 1997, its stock grew by nearly sixty times its 1993 price.
The representativeness bias is partially responsible for many other major and repeated errors. All mutual fund organizations operate on the knowledge that investors favor better-performing mutual funds even when research shows that the “hot” funds of one time period can be amongst the poorest of another.
The most recent example of this is the aggressive-growth funds of 1991 to 1997, which caused investors to lose billions of dollars while conservative, blue-chip mutual funds performed well.
Yet investors continue to be drawn to the trendy, “hot” stocks, despite the long-term results (p. 259). As a result, brokers who have had one or two stocks perform extremely well or technicians who make a valuable prediction, are seen by the majority as credible sources.
Another key probability error that falls under the topic of representativeness is referred to, by Tversky and Kahneman, as the “law of small numbers. (p. 259)” Tversky and Kahneman discovered, through extensive research, that researchers systematically overstated the importance of findings that were taken from small samples.
The Law of Large Numbers
According to the statistically valid “law of large numbers,” large samples are usually highly representative of the population from which they are drawn. The smaller the sample used, on the other hand, the more likely the findings are chance rather than actuality.
Tversky and Kahneman study fund that most psychological or educational researchers base their research theories on samples so small that the results are more likely to be based on chance than actuality (Dreman, 1998, p. 260).
These researchers are taking a shortcut, displaying overconfidence in significance of results based on a small sample, despite the fact that they are educated in statistical techniques and should know better.
The majority of people see too much significance in occurrences, even if there are few supporting facts. Limited statistical evidence satisfies intuition, while large amounts of actual knowledge is overlooked.
One example of this is the blind faith investors place in governmental economic releases on employment, industrial production, the consumer price index, and more. These reports have major effects on the stock market, especially if they reveal bad news.
If the unemployment rate drops when it was expected to be unchanged, stock prices can decrease dramatically, despite the fact that the new release was a “flash statistic,” which can be worthless (p. 260).
While professionals usually know to ignore these types of reports, the amateur investor often has a knee-jerk reaction to them, convinced that they have discovered an important trend.
According to Dreman, “An example of how instant news threw investors into a tailspin occurred in July of 1996. Preliminary statistics indicated the economy was beginning to gain steam. The flash figures showed that GDP (gross domestic product) would rise at a 3% rate in the next several quarters, a rate higher than expected. Many people, convinced by these statistics that rising interest rates were imminent, bailed out of the stock market that month. By the end of that year, the GDP growth figures had been revised down significantly (unofficially, a minimum of a dozen times, and officially at least twice). The market rocketed ahead to new highs to August 1997, but a lot of investors had retreated to the sidelines on the preliminary bad news (p. 261).”
Tversky and Kahneman’s research, which has been repeatedly confirmed, is particularly important in understanding stock market errors.
According to the law of averages, many investors may have an excellent record playing popular trends for an extended period of time, only to drastically underperform later in the game. This is a harsh lesson that countless investors have had to relearn with each new supposedly unbeatable market trend.
Overemphasis on Individual Situations
Tversky and Kahneman’s research revealed another human error that reveals man’s inadequacy as an intuitive statistician (Dreman, 1998, p. 262). In the decision-making process, people tend to put too much emphasis on the specific details of a particular situation, neglecting the outcome of similar situations in the past. These past outcomes are known as prior probabilities, and logically should provide guidance for similar choices in the present. However, many times they do not.
When participating in the stock market, people put a great deal of emphasis on the outlook for each exciting initial public offering or concept stock, while there is little information supporting their beliefs. Investors often fail to examine the high probability of loss while focusing on the possibility of great gain. While more than 80% of these stocks proved to be duds, investors kept dumping their money into them, remembering the success stories.
Correlation of Inputs and Outputs
Another heuristic bias that is related to representativeness is the intuitive belief that inputs and outputs are closely correlated (Dreman, 1998, p. 270). If this theory were true, consistent inputs would allow greater predictability than inconsistent ones.
For example, if one student has an A and a C. grade in a class, and another has two B’s, people will be more confident that the student with two B’s will have a consistent B. average, even though this belief is not statistically valid. Similarly, people will put their money on a stock that has a proven record. However, this bias leads to consistent errors in the market.
Investors have a tendency to mistakenly place high confidence in extreme inputs or outputs. Growth stocks in the 1990s were seen as great picks (the input), which was confirmed by prices that increased by up to 20 times (the output). People compared these Internet stocks to the growth stocks (HMO stocks) of the 1980’s, which were other sharp risers. This correlation was attractive to investors, who accepted it as a reliable fact. However, it was not.
Human errors also relate to crash and panic. In this case, earnings estimates and outlooks (inputs) erode as prices decrease. Graham and Dodd had a strong understanding of input-output relationship, stating, “an evitable rule of the market is that the prevalent theory of common stock valuations has developed in rather close conjunction with the change in the level of prices. (p. 271)”
Because investors so often hunger for immediate gratification, they tend to lean more towards trends and fads that seem to be doing well, rather than investing solidly. One of basics of investment strategies involves giving the investment enough time to work. While patience is important in the stock market, there is very little of it among investors.
According to Tversky and Kahneman, availability is a heuristic by which people “assess the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind” (p. 272).
For instance, the majority of people believe that shark attacks cause more deaths in the U.S. than pieces falling from an airplane, probably because shark attacks get more publicity. However, falling airplane parts kill thirty times as many people as shark attacks.
The availability heuristic enables people to simplify more complicated judgments based on their perceptions. In many cases, this heuristic works rather well, as people tend to recall events more easily if they have actually occurred frequently.
However, human recollection is a tricky subject, as it is influenced by many factors, including how recent the events occurred and how emotional the events are.
The bottom line is that availability, like most heuristics, causes investors to frequently misread probabilities, and has a negative impact on the investment decision-making process.
Emotionally charged events have a profound effect on decision-making in the stock market. Statements by experts, crowd participation, and recent experience strongly persuade the investor to follow trends.
When market environments take a turn for the worse, investors begin to question their portfolios, particularly when the market remains unstable for lengthy periods of time (Neil, 2002, p. 17). The last decade has been a roller coaster ride for the stock market.
Between 1998 and 1999, almost all stock investments grew (Neil, 2002, p. 17). Technology stocks were the hot ticket and were setting unprecedented records. Investors dumped money in the stock market, jumping on a bandwagon that seemed to be bottomless. However, in 1999, it crashed and investors lost billions of dollars.
The following table outlines the performance of five stocks during 1928-1929 (p. 18):
When people panicked, as a result of the 1929, they sold their stocks immediately. However, according to these statistics, if they had held on to these quality stocks for just a few more months, their portfolio would have increased.
Often, investors feel that they spend more time managing the emotions of their clients than they spend investing their money. According to brokers, emotions are the dominant force behind financial decisions.
During the 2001 election, many people were referring to particular stocks as “Bush” stocks and “Gore” stocks,” which were speculated to perform according to which presidential candidate won the election (Linger, 2002).
This raised the question: Can the results of an election have a significant effect on a stock’s performance? If the market was truly efficient, investors would take into account a company’s products, management, profit margin, growth rate, and industry outlook, rather than listen to current news and react based on their emotions. However, the 2001 election and the emotional investment strategies it caused reveals that the market is most likely not an efficient one.
According to an article in the AAII Journal, “the average stock had 11% earnings growth per year, but had a 65% annual price range from bottom to top. Therefore, emotions moved stocks six times as widely as fundamentals justified.”
According to Eric Linger (2001) “the reason many investors get off track is because they think there is a correlation between a stock’s performance and the current news and they react emotionally. In fact, this correlation is weak and unimportant.”
Peter Lynch, a famous investor, says, “It always comes down to earnings and assets. Especially earnings.”
The price of a stock increases or decreases over time with its earnings. Because it takes time for change, investors are encouraged to show patience. When the market is doing poorly, stocks that continually show increased earnings are the best bet. However, research shows that the quality of a stock cannot be determined based on its stock price movement. Price movements in the short run tend to be a result of investor emotions rather than the performance of the company.
Familiarity Breeds Comfort recent study by Gur Huberman, a professor at Columbia University, revealed that investors prefer to invest in local companies that they are familiar with (BusinessWeek, 1997, p. 82). For instance, an investor would be more likely to invest in local grocery chain than a similar or better one in another area. This shows that investors favor local or familiar securities over comparable yet unfamiliar ones, even if there is no rational reason for this preference.
In 1996, when Terry Odean, a University of California at Berkeley student, revealed the results of his study of trading in 10,000 discount-brokerage accounts from 1987 to 1993, it became apparent that do-it-yourself investors were chronic underperformers (Business Week, 1997, p. 82).
The stocks that the do-it-yourself investors sold beat the market, according to Odean’s research, while those they purchased did worse. Within a year of the investments, the average investor was nine percent poorer than he was when he started. Two years later, the situation was even worse.
Gur Huberman, a finance professor at Columbia University, released a related study shortly after Odean’s was published (p. 82), suggesting that do-it-yourself investors display signs of overconfidence, as they are sure that they will make more money by trading stocks than they would by doing nothing at all.
In addition, Huberman’s study reveals that one form of this overconfidence may be the investors’ preference for stocks in familiar companies, despite the fact that they may have no rational reason for selecting these stocks.
Huberman’s study stemmed from his curiosity over why global investors tend to favor domestic stocks over foreign stocks. His hypothesis was that investors had a psychological need to invest in familiar and comfortable companies.
To test his hypothesis, Huberman examined stock-ownership records of the seven regional Bell operating companies (RBOCs) (p. 83). He discovered that in all but one state, more people hold shares of the local RBOC than any other, and their holdings average $14,400. For RBOC investors who stray from their local unit, the average is $8,246.
It was obvious to Huberman that not all of these investors could have been correct in their assumptions, as it is impossible for everyone’s local RBOC to be a better investment choice than any of the other six. However, according to Huberman, “people delude themselves into thinking that they know more than they do. (p. 83)”
Odean, who now teaches finance at the University of California at Davis, believes that individual investors inflict several filters when searching through stocks. Some of these filters, such as a below-market price-earnings ratio, are considered rational, while others, such as refusing to buy an unfamiliar stock, are not.
According to Huberman, the overwhelming tendency to favor familiar stocks has a great impact on the stock market’s performance. When investors continually favor familiar stocks, they assume greater risk by diversifying less broadly and also by investing with everybody else. This actually cuts their potential returns. “If people are more willing to buy the familiar,” Odean says, “there is going to be a premium on the price. (p. 83).
A lot of people see the financial decisions of others as the result of individual temperaments or disposition. However, most see their own decisions as rational ones. Many investors, both amateur and professional, make decisions based on information that they believe is superior and relevant when it is not and is fully discounted by the stock market. This results in frequent trading and consistent high volumes in financial markets that is perplexing to researchers.
Frequent Trading Patterns
According to many research studies, the urge to gamble and take unnecessary risks is a basic human trait. Entertainment and ego seem to be major motivations for the tendency to speculate. Research also suggests that people are more likely to remember their successes than their failures, so they tend to show more confidence in investments.
According to John Allen Paulos, in his book Innumeracy, “There is a strong general tendency to filter out the bad and the failed and to focus on the good and the successful.” (2001, p. 87)
The financial decisions of many individuals are often influenced by the way that problems are framed, as well as by comparable, yet often irrelevant, options. For example, when offered a specific amount of cash or a cross pen, most people will choose the cash. However, when offered cash, a cross-pen, or an inferior pen, more people chose the cross pen.
Many researchers say that evidence shows that financial analysts who visit a company show confidence in their stock picking skill, even though there is no evidence to support this added confidence (p. 91).
Human behavior regarding the investment process, culture, and the relationship between investors and their advisors can have a significant effect on the financial decision-making process and resulting investment performance.
Often, investment firms hire brokers and financial advisors even if they are likely to underperform the market. Many researchers believe that firms hired these people to play the role of scapegoat.
In Fortune and Folly: The Wealth and Power of Institutional Investing, William M. O’Barr and John M. Conley (1992) wrote that officers of large pension plans hired investment managers to take the blame for failed investments. This enables them to protect their jobs at the expense of someone else in the event of underperformance. Of course, they will take credit for overperformance.
Journalist Larry Barrett, in January 2001, wrote: “The Nasdaq composite has made a modest recovery from its startling sell-off in 2000, and people are starting to feel good about themselves again. Investors give a lot of lip service to fundamentals and valuations, but the sad truth is, emotion drives the market. It always has, and it always will.”
According to Barrett and several financial analysts, when investors watched the Nasdaq “blast through the 5,000-point threshold in March only to give back half its value by year’s end,” most investors felt the need t re-evaluate his expectations and investing philosophy.
The same group of investors that had dumped endless streams of cash into shaky Internet stocks at unprecedented prices suddenly pulled their money out of the stock market, afraid to buy even some of the leading industry stocks at low prices. This backs up research that states, the majority of individual investors will keep a losing stock too long and sell a winning stock too soon.
According to Meir Statman, a behavioral finance professor at Santa Clara University: “People hold losers too long mainly because they make a distinction between a paper loss and a real loss. The underlying emotion is regret. People don’t want to come to terms with the fact they picked a loser, and in some sense, are a loser themselves. (Berrett, 2001)”
Statman believed that the ebb and flow of trading on Wall Street is a direct reflection of basic human needs. “Investors get wrapped up in these things,” he said. “People prefer beautiful, rich, smart people. If you pick a good stock, you want to tell people about it. And what you’re really telling them is that you’re smart and that you’re rich.”
It seems that even money managers are guilty of human behavior when it comes to the stock market. Throughout history, countless managers have purchased extreme amounts of shares in a trendy, promising company and watched in horror as it crashed.
One of the big problems these days, is that a consumer attitude has permeated stock investing,” according to Tad LaFountain, a financial analyst (Berrett, 2001). “Instead of people saying they are what they eat, they’re now saying that they are what they buy.”
The stock market is a hot topic of conversation in everyday situations, ranging from parties to corporate meetings. People talk about their stocks as if they are talking about their favorite baseball team.
However, when the market takes a turn for the worse, trading volume decreases because investors hold on to their stocks, afraid to make a move.
Another factor that causes stock price fluctuations is life. For example, if a rich man dies and his family must sell a substantial amount of stock to pay off tax debts, large amounts of stock will be sold. If a large corporation hits a financial obstacle, it may also decide to sell a large amount of stock.
However, this increase in stock sales has absolutely nothing to do with the company’s performance. However, suddenly there is a large sell order that ultimately drives the price down. This is an unpredictable occurrence that can drive a quality company’s stock to sell below its value.
According to Warren Buffet, the most common cause of low prices is pessimism. Buffett prefers to do business in such an environment because the prices are lower. According to Buffett, “optimism is the enemy of the rational buyer.”
The stock market has historically overvalued and undervalued common stocks because of the human emotion it is driven by. This pattern can likely be exploited to the advantage of savvy investors, particularly due to modern technology, which enables investors to sort through thousands of stocks and locate the ones that are the most undervalued.
FLAWS OF THE EFFICIENT MARKET HYPOTHESIS (EMH)
Professional investors have, for decades, used psychology as a scapegoat to dismiss market crises, such as manias and herd instincts. Behavioral finance experts are taking this approach a step further, applying psychology to financial markets, to expose the flaws of the efficient market hypothesis (EMH).
Recently, we worked on a project that involved users rating their experience with a computer. When we had the computer the users had worked with ask for an evaluation of its performance, the responses tended to be positive. But when we had a second computer ask the same people to evaluate their encounters with the first machine, the people were significantly more critical. Their reluctance to criticize the first computer ‘face-to-face’ suggested they didn’t want to hurt its feelings, even though they knew it was only a machine. (Gates, 1995)”
This shows the level of emotion that humans often display when making decisions, whether personal, financial or technical.
Challenging the EMH
Many investors have beaten the market, which has caused financial experts to question the validity of the EMH. In the investment industry, there are obvious arguments against the EMH. For example, Warren Buffet, the second richest man in the world, achieved great success and millions of dollars through an investment strategy that focuses entirely on undervalued stocks (Hagstrom, 1995).
There are also scores of portfolio managers that have consistently outperformed others and investment firms that are renowned for their research analysis. Therefore, if these people are profiting from and beating the market, researchers say that the EMH cannot be accurate.
According to William Sharpe, “I do not dismiss the behavioral aspects that Joe Lakonishok and others have argued which is to say that there are all kinds of reasons from cognitive psychology that suggest that a real dog is likely to get underpriced, and maybe people know it’s underpriced and they still don’t want to hold it. (Tanous, 1997)”
EMH skeptics believe that there are consistent patterns in the stock market (Haugen, 1999, p. 42). For example, the “January effect” is a phenomenon that occurs at the end of the year when investors become concerned about taxes and sell stocks that are down to write off their losses against their capital gains. The January effect causes stocks to decrease at the end of the year and go back up when investors buy them again.
The “weekend effect” is another example of an anomaly (p. 48). This term refers to the common occurrence in which stock prices tend to be higher from Friday through to Monday.
Despite strong evidence that securities markets are highly efficient, many researchers have demonstrated long-term historical phenomena in securities markets that disprove the efficient market hypothesis and investor rationality. Such phenomena can be described as stock market anomalies (Gross, 1997).
Behavioral finance seeks for psychology-based theories to explain these stock anomalies. Within the behavioral finance model, it is assumed that the data structure and characteristics of market participants methodically influence their investment decisions, as well as market performance.
Basically, behavioral finance studies how humans interpret and react to information when making informed investment decisions. Research in this field suggests that investors do not always exhibit rational, predictable and unbiased behavior when making investment decisions, as quantitative models assume.
When making financial decisions, investors often make human errors. Individuals may see what they want to see and make irrational decisions. They may interpret accidental success to be the result of their skill. Money managers, advisors, and investors have all been proven guilty of overconfidence in their ability to outperform the market.
According to Merton H. Miller, Nobel laureate in economics (Miller, et al., 2002, p. 211), “Stocks are usually more than just the abstract bundles of returns of our economic models. Behind each holding may be a story of family business, family quarrels, legacies received, divorce settlements, and a host of other considerations almost totally irrelevant to our theories of portfolio selection. That we abstract from all these stories in building our models is not because the stories are uninteresting but because they may be too interesting and thereby distract us from the pervasive market forces that should be our principal concern.”
The EMH has created a huge debate in the financial industry, prompting countless research studies to try to understand whether or not specific markets are efficient. There is much evidence supporting the EMH. Some of the original tests of the EMH focused specifically on technical analysis, challenging its existence. The majority of these tests revealed that technical theories are useless in predicting stock prices.
According to Benjamin Graham, author of the Intelligent Investor (1995, p. 166), “The one principal that applies to nearly all these so-called “technical approaches” is that one should buy because a stock or the market has gone up and one should sell because it has declined. This is the exact opposite of sound business sense everywhere else, and it is most unlikely that it can lead to lasting success in Wall Street. In our own stock-market experience and observation, extending over 50 years, we have not known a single person who has consistently or lastingly made money by thus “following the market.” We do not hesitate to declare that this approach is as fallacious as it is popular.”
Graham’s conviction rested on certain assumptions. First, he believed that the market frequently mispriced stocks. This mispricing was most often caused by human emotions of fear and greed. At the height of optimism, greed moved stocks beyond their intrinsic value, creating an overpriced market. At other times, fear moved prices below intrinsic value, creating an undervalued market. (Hagstrom, 1995)”
Opponents of EMH
Classical economic theory assumes that investors use all available informational rationally and act in an unbiased manner. Research by Amos Tversky (1982), Professor of Behavior Science at Stanford University, showed just the opposite. According to Tversky’s research, investors were commonly biased in many ways.
For example, people tend to be overly optimistic and overestimate the chances of their success and their personal knowledge, resulting in confidence that exceeds their success rates.
In addition, both professional and amateur investors are vulnerable to cognitive illusions because they relate to perceptions that are often tempting even if they are erroneous. Cognitive illusions can take occur in risk attitudes, mental accounting and overconfidence. For example, illusions involving mental accounting involve people who invest funds on one hand and borrow money on the other at a rate which exceeds that which the funds in the investment account are likely to earn.
People tend to be overconfident in their own abilities, in all aspects of life. Investors and analysts are especially overconfident when they have some knowledge of a subject. They often believe that they can outperform the market but usually fail to do so.
A lot of people believe that the market can be consistently timed to work in their favor. However, there is much evidence that proves just the opposite.
Researchers have found some technical anomalies that show that technicians may have an advantage, although transactions costs may eliminate this advantage. Still, the majority of researchers and financial experts do not believe that technical analysis has an effect on the stock market.
Technical analysis is doomed to fail by the statistical fact that stock prices are nearly random; the market’s patterns from the past provide no clue about its future. Not surprisingly, studies conducted by academicians at universities like MIT, Chicago, and Stanford dating as far back as the 1960s have found that the technical theories do not beat the market, especially after deducting transaction fees. It is amazing that technical analysis still exists on Wall Street. One cynical view is that technicians generate higher commissions for brokers because they recommend frequent movement in and out of the market. (Sherden, 1999)”
Buy on the Rumor Strategy
Financial professional often use the term “buy on the rumor and sell on the news” (BRSN) when talking about a strategy for taking advantage of a frequently observed financial market price pattern (Peterson, 2001). BRSN is characterized by security prices rising before positively anticipated events and falling afterwards. Security prices, ironically, tend to decline following an event outcome that superior to expectations.
According to researcher Richard L. Peterson (2001), “investors often gamble both on an event outcome and on the anticipated price appreciation as a result of that positive outcome. Anticipation of reward generates a positive affect state. Positive affect motivates both increased risk-taking and increased purchasing behaviors.
As the anticipated potential reward approaches in time, investors’ positive affect is increasingly aroused. Following the delivery of an expected reward, investors’ affect regresses to neutral. This post-event net decrease in positive affect leads to more risk-averse, protective investing behaviors such as selling.”
Many times, a rumor regarding a particular stock will start in a company. Perhaps the company is going to be acquired by a larger company or is going to launch a new product. This causes people to mentally conjure up the price of the acquisition or projected profit of the product.
They can imagine any price that they want until the rumor turns to fact and is announced. Unfortunately, the rumor is usually more attractive than the fact. Due to the fact that all the best possibilities have already been “priced into” the stock before the announcement is made, it becomes apparent that there are limits to the good news.
One example of BRSN occurred in 1998, when a rumor circulated through Pixar Animation, the producer of Toy Story and A Bug’s Life (Pui-Wing, 2001). Before the company announced A Bug’s Life, the rumor revealed the potential for the film. Based on this speculation, Pixar’s stock increased by $33 before the film opened.
When the movie opened, it outperformed box-office records for an animated film but the stock quickly lost about 40% of its value in just a month and never fully recovered. While A Bug’s Life enjoyed great success, its success was not as great as the rumor expected it to be.
Many amateur investors do not understand that a positive event outcome does not necessarily mean that a stock price will increase (Peterson, 2001). Their high levels of risk exposure may shock them after the anticipated event. This will cause them to behave more cautiously, often resulting in investment repositioning of high-risk positions. When selling increases, negative price pressure is the result. Price decline alone adds to investors’ negative affect and increases risk aversion.
Many things affect BSRN. For instance, when news reports forecast future stock market-related events, a price impact typically occurs. According to the efficient market theory, investors price security-relevant news before the fact. For the BRSN pattern to represent price inefficiency, news about a positive future event must have a delayed impact on investing behavior.
While there is not enough evidence to label existence of the BRSN pattern as an anomaly, it is important to consider it when analyzing the effects of human interaction on the financial decision-making process, as there are a variety of both securities and events that effectively illustrate the BRSN pattern.
For example, there is a BRSN pattern surrounding Apple Computer Inc.’s MacWorld tradeshow in January 2002. The Wall Street Journal published an article four days prior to Apple’s anticipated new iMac unveiling at the trade show. The following was stated in the article (Pui-Wing, 2002):
The Cupertino, Calif., company’s stock increasingly has been caught in a strange cycle: In recent years, the shares have run up strongly in advance of product debuts — and declined thereafter. In a December study from Morgan Stanley, analyst Gillian Munson found that in three of five cases after Apple launched a new computer since 1997, its shares slipped. Of those three occasions, the stock fell an average 19% in the ensuing six months, she noted.
This time around, the peculiar pattern could well be happening again. Apple’s shares have risen steadily in recent weeks, from just under $15 in early October, driven at least in part by anticipation of new products at Macworld. At 4 p.m. Wednesday in Nasdaq Stock Market trading, the shares were up a healthy $1.40, or 6.39%, at $23.30. (Tam, 2002).
Apple’s six-day daily price chart shows the BRSN pattern. AAPL shares peaked at a six-week price high on the morning of the new iMac release at the trade show.
Daily AAPL price chart (Open, High, Low, Close) from January 2 to January 9, 2002.
Note: Information from Bigcharts.com.
While the Wall Street Journal article describes this situational BRSN pattern for Apple shares, it did not stop the pattern from recurring (Pui-Wing, 2002). Apple shares declined more than 15% within five days of the trade show.
There are other stock market anomalies that some researchers say contradict the EMH (Haugen, 1999). When trying to find these anomalies, researchers look for methods or patterns that can be used to outperform passive and buy-and-hold tactics.
When an anomaly is discovered, investors attempting to profit by exploiting the inefficiency should result in its disappearance. Several anomalies that have been documented through this approach have disappeared or proven to be impossible to exploit because of high transactions costs.
Still, many researchers point out that an efficient market depends on disbelief in efficient markets. If everyone believed in the EMH, no one would analyze stocks. As a result, the market would no longer be efficient. Efficient markets depend on the non-believers that continue to try to outperform the market.
This research paper reveals that markets are neither absolutely efficient nor absolutely inefficient. While all markets are efficient in one way or another, some are more efficient than others. Therefore, if educated investors can pinpoint markets with impairments of efficiency, they may have a better chance of outperforming less knowledgeable investors.
For example, government bonds markets are extremely efficient markets, as are large capitalization stocks. Small capitalization stocks and international stocks are considered less efficient markets. Real estate and venture capital, which do not have fluid and continuous markets, are considered less efficient because various participants may not have equal information.
The EMH debate poses many questions in the field of behavioral finance, as it affects the decision-making process regarding active and passive investing. Many researchers believe that less efficient markets give skilled investors the opportunity to outperform the market. Many others say that even the most skilled investors will underperform the appropriate benchmark in the long run despite the efficiency of the market.
Psychology of Investing
It is important to understand that many common human behaviors that have a significant influence on the stock market.
Humans usually do not demonstrate the cognitive ability to properly measure risks and rewards. When investing in the stock market, those who display skill in recognizing risks and rewards will, in most cases, have an advantage in trading.
Often rational investors can recognize that they may not beat the stock market. Many people trust investment managers to effectively manage their portfolios, although even these professionals are often unable to beat the market, because they have the same cognitive irrationality all humans possess (Cohen, 1997). In fact, studying Warren Buffett says that his greatest advantage is not one of analysis, but rather his willingness to be anti-social in his investment strategies.
Professional money managers fail to outperform the market at an average rate of 70% per year (Hagstrom, 1995). The majority of those who manage to outperform the market one year regress to the mean the next year so that 90% of all professional managers fail to beat the market over a decade.
This surprises many people because they see these professionals as having more knowledge and training than the vast majority of investors. However, it does not seem to make a difference in the long run.
Human Characteristics of Money Managers lot of investment managers display overconfidence in their stock picks (Gray, 1971). Perhaps this is because they have access to more information and resources than most people and it is their job to analyze it.
If investment managers need information about a company, they typically have access to all levels of management. Humans tend to show the most confidence in areas in which they have the most knowledge. However, their overconfidence and proximity to the market often causes managers to overtrade, because they truly believe that they can beat the market.
Both proponents and opponents of the EMH say that it is impossible to be completely deductive when playing the stock, so all investors rely on incomplete knowledge and their perceptions. However, most people will seek confirming information and ignore information that does not support their ideas.
Due to the fact that they are human, money managers are far more comfortable with phenomena they can explain. Because capital markets have been around for so long, many experts believe that they have figured them out.
Yet they fail to take into account that these capital markets have advanced at extremely rapid rates during their lifespan. The human mind is simply incapable of developing the ability to explain and rationalize these markets at the same speed.
Still, the human mind longs to links cause to effect. However, while this may be temporarily satisfying, in the stock market, it is usually ineffective. Many business analysts like to believe that the market reacts to certain things but there is no such thing as a simple stimulus-response in the stock market.
In June 2002 (Tessler, 2002), WorldCom revealed that it hid $3.8 billion in expenses over 15 months, shaking the telecommunications industry reeling and causing already shaky investors to lose further confidence in corporate America.
WorldCom, the nation’s second-largest long-distance phone company, faced the largest bankruptcy in U.S. history. Meanwhile, analysts criticized WorldCom’s shady accounting, saying that the company may have committed one of the most serious white-collar crimes in history.
One of the biggest casualties of the WorldCom scandal was the loss of investor confidence in Wall Street and corporate America, as well as the accounting profession, which was assumed to be watching both.
Running in Herds
Human beings have a tendency to seek safety in numbers (Haugen, 1999). Professional advisors are often evaluated based on a 90-day performance period and underperformance is not well received. Because of this, it seems that managers of funds with related objectives all go for the same few stocks in an attempt for self-preservation.
If several managers hold a stock that crashes, the economy can be blamed. On the other hand, if only one manager picked a particular stock and it crashed, his career would be jeopardized. Still, investment managers are not alone. Running in herds is attractive to both institutional and individual investors.
Greed and Fear
The general behavior of people has not changed in hundreds of years. In 1720, Isaac Newton lost a small fortune in the South Sea Trading Company crash (Gray, 1971). While South Sea Trading Company appeared to be a “hot stock,” as investors raved about its potential, it proved to be disastrous. People acted on whims and purchased large quantities of a stock that proved worthless.
Markets invariably move to undervalued and overvalued extremes because human nature falls victim to greed and/or fear. (Gross, 1997)”
Despite the fact that investors have been making rash decisions for centuries, the classic economic and financial theories are based on the assumption that individuals act rationally and consider all available information in the decision-making process.
Many people have said that two human emotions rule the investment decision-making process: greed and fear. These two emotions fuel the desires of people to play the stock market, even if it is not a rational choice for them. These same emotions cause investors to buy overpriced stocks and then turn around and sell them as soon as their value drops.
These human emotions have opened the doors for various research questions, such as: Why do these people behave irrationally? Fear? Pride? Desperation? It is certainly not rational thinking, as the EMH states investment decisions are based on.
The fact that humans make the majority of decisions based on fear and greed is contradictory to fundamental economic theories, which state thate investor decisions are based on trend analysis and reliance on numbers.
The stock market is nothing more than an auction market,” says Goodman, “where people react to various pieces of information about a company (Goodman Institute of Investment Management, 2002).” However, the EMH states that the stock market is valued properly at all times. This is untrue, especially in a bear market.
For example, recently, Nortel’s stock dropped from $120 a share to $20 in short order. The EMH should have kept the stock at a level price but failed to do so. Goodman says that human behavior is the reason for the theory’s failure. ”
The market is a pendulum, which swings with emotion and psychology,” he states. “It swings from being grossly overvalued to being grossly undervalued. The key is the valuation process. That part has not yet made it into the academic world (Goodman Institute of Investment Management, 2002).”
The main problem with the EMH is that it views the stock market as if it were a computer, methodically selecting and processing information, then arriving at a rational price that reflects the correct value of the stock.
The stock market is a wizard at gathering and transferring information. At any given time, the price of the last trade is a reflection of all the knowledge of all the participants in the market. However, while many people think that they are smarter than the market, they never are.
If the EMH is true, how can we explain Benjamin Graham’s “Mr. Market,” the emotional side of every investor? “The Intelligent Investor” by Graham is arguably one of the best books ever written about share market investment. In this book, Graham describes the mythical Mr. Market (1995).
Graham urges his readers to imagine they are partners in a private business with Mr. Market, who approaches them every day with an offer to either buy his stake in the company or sell him theirs.
Mr. Market is a very emotionally volatile man. When he feels optimistic, he wants to buy their share for a generous price, as he feels that the future is great. When he feels pessimistic, he tries to sell his stake in the business at a below-value price.
Graham then tells his readers to imagine that Mr. Market is not an individual but every other investor in the share market and that the readers’ stake is not in a private company but in a large portfolio of public companies.
Basically, the price of stocks reflects a balance between optimistic buyers and pessimistic sellers. When there are more pessimists than optimists, the price decreases and vice versa.
Therefore, the change in a stock price has as much to do with people’s emotions and opinions than the underlying value or earnings potential of the company. Yet millions of people believe in an efficient market where a share price reflects all of a company’s information and is priced based on this.
How the Efficient Market Hypothesis Contradicts Itself
Basically, the Efficient Market Hypothesis (EMH) states that an investor cannot develop a system that consistently picks stocks that will outperform the market over a given period of time. It also states that companies cannot incorporate events or information that misrepresent the value of stocks and bonds.
Recent literature, however, points out that many companies have managed to beat the system, manipulating data to make their stocks seem more attractive than they are. An understanding of the various inefficient “human” factors in the market equation is important when trying to account for the flaws in the EMH.
As stated earlier, the EMH is based on the assumption that, due to the efficiency of information technology and market dynamics, the value of the normal investment stock at any given time is an accurate reflection of the real value of that stock.
According to the EMH, a stock’s price reflects its actual underlying value, so it is impossible for investors to accurately time stock and bond sales to take advantage of insider information. In addition, the EMH states that no matter how many stocks are sold and bought at a particular time, the stock prices will not depress or inflate. The EMH also holds that companies cannot incorporate information or events that will effectively manipulate stock prices.
However, information technology and market dynamics rely on the behaviors, moods and opinions of ordinary people and assorted organizations, neither of which are consistently rational, efficient nor consistent. Therefore, it seems that the EMH is contradictory. How can a theory based on objective mechanical efficiency be correct when applied to subjective human inefficiency?
An Example of the EMH’s Flaws recent case involving AOL demonstrates a specific example of how companies can mislead investors by incorporating events and information that manipulate stock prices. In the past, AOL used an accounting system that effectively altered their statistics and reported misleading figures on the company’s performance.
Rather than accounting for its promotional expenses and costs as a regular expense, as the majority of companies do, AOL spread them out over two years, allowing the company to report annual profits based on revenue figures resulting from denying actual expenses.
This expense deference allowed AOL to report profits of almost $385 million greater than they would have been with a normal accounting system. The company subsequently used these false profits to attract stockholders and investors, which increased its stock price.
AOL’s accounting trick was a legal one and allowed it to keep its true records confidential for two years. Shortly afterwards, AOL announced that its promotion expenses would be charged to earnings as the expenses are incurred, like most other companies do.
AOL, at that time, took a special charge of $385 million for the “deferred” promotion costs. As a result of this schema, AOL’s reported profits were negated and the company was in a negative net cash flow situation. Its stock price dropped to half its value.
This situation demonstrates a significant flaw in the EMH, which is dependent on information as the primary element for determining market value. When the information is manipulated, the EMH does not apply.
Still, as researchers have pointed out, most companies do not use such accounting methods to falsely report its performance. As the EMH asserts: “Fundamental analysis cannot produce investment recommendations that will enable an investor consistently to outperform a buy-and-hold strategy in managing a portfolio (Malkiel, 1990).”
However, it is important to look at the results of the theory. If the EMH is true, the market cannot hurt an investor because the stock value of a poor performer already includes that fact in its price.
The EMH states that the available information would specify that a specific stock was overvalued and subject to decline. The availability of public information eventually forced AOL to come clean with its trickery and change its accounting practices. As a result, the stock’s value was lowered to its true price.
While many researchers cite the AOL case as a perfect example of the EMH’s flaws, others say it is an example of the EMH’s validity. This group argues that EMH was indeed working because the investors were protected from steep loss because the system eventually adjusted the stock price to reveal the actual value of the stock.
According to EMH proponents, AOL’s former high price did specified the value of the stock based on its current accounting practices, however misleading as they were. When AOL made the decision to change its accounting practices, the value of the stock immediately reflected the actual lower value. This could, reasonably, be viewed as a repudiation of EMT.
When the Nasdaq made a modest recovery in 2001, investors regained some of their lost confidence. While many experts touted fundamentals and valuations as the reason for this, others said it just proved that emotion drives the market.
In Piattelli-Palmarini’s Inevitable Illusions: How Mistakes of Reason Rule Our Minds (1994), the author states, “These are errors we commit without knowing that we do so, in good faith, and errors that we often defend with vehemence, thus making our power of reasoning subservient to our illusions.”
According to Piattelli-Palmarini, the way that investors are presented with information largely affects the way that they react to it. He presents an actual case study taken from the field of medicine, in which different groups of doctors are presented with an identical situation: a serious disease has a new form of treatment requiring operation.
The first group is told that there is a 7% mortality rate within five years of the operation, while the second group is told that there is a 93% survival rate within five years of the operation.
As a result of the information given, the first group hesitated to make favorable recommendations, while the second group was more likely to recommend the treatment. This proved that the doctors used framing in their decision-making process.
According to Piattelli-Palmarini, “Our problem here is that we do not compute final ‘assets’, but only departures from a baseline.” The medical case study proves that human nature focuses us on how far we’re departing from a given state or starting point rather than on the reality or actual assets.
In regards to investing, the framing principle can apply in many situations. For example, as a result of mutual funds investing and fast-talking money mangers, many investors have been led to believe that the “baseline” is not the stock market’s average but instead a certain return or hat happened in the past. Brokers may tell a client that a particular fund was up 20% the previous year, instead of saying that the market was up 30%. Statements like this one are “framed” off an incorrect benchmark.
In the world of perception,” Piattelli-Palmarini states, “an illusion is to reality what a fallacy is to reasoning: an argument that is not true but has the appearance of being so. There is always some truth in any illusion; there is always some persuasion in a fallacy. Our business is to distinguish between angels and devils.”
FINANCIAL BUBBLES AND CHAOS
Throughout history, there have been two types of financial bubbles. The first occurs when investors become excited about something that is frivolous. The second occurs when investors become excited about an innovative technological revolution in the economy and overvalue stocks because of it.
The Tulip Craze and the 2000 Dot-com Crash are both examples of bubbles. However, the Tulip Craze is considered a frivolous bubble, while the 2000 Dot-Com Crash is seen as a substantive one. The main difference is that experts say substantive bubbles will likely result in positive results for investors over time, while frivolous ones will not.
Retrieved from Itulip.com.
The above chart shows an actual Nasdaq chart in March 2000. Looking at it now, it is hard to imagine that people could not see a bubble. However, millions did not. Basically, when one is inside a bubble, pricing is normalized to bubble standards. Bubbles are fuelled by their own internal logic and feel that their decisions are rational.
Tulip Bulbs and the Stock Market
In 1559, Conrad Guestner brought the first tulip bulbs from Constantinople to Holland and Germany, and people loved them (Edelman, 2001). Soon tulip bulbs were considered a status symbol. They were rare, beautiful and everyone wanted them.
While the early buyers of tulip bulbs love the flowers, the later buyers were after the money. Tulips generated trading activity, so it was not long before they hit local maret exchanges.
By 1634, Dutch society was in the midst of the “Tulip Craze,” during which merchants competed with one another for single tulip bulbs. The present day value of a tulip bulb was about $35,000. People were selling their homes and livestock to buy tulips, speculating that they would grow even more in value.
By 1936, tulips were established on many European stock exchanges. Spectators and gamblers, as well as ordinary people, liquidated their assets at incredibly low prices in order to speculate in tulip trading.
A whole industry was launched around these tulip bulbs. Tulip notaries and clerks were appointed to record transactions, and public laws and regulations were created to control the tulip craze. However, in 1636, many investors started liquidating their tulip holdings.
At first, tulip prices declined slowly, then more quickly. Investors lost confidence and panic set in. Within six weeks, tulip prices dropped by 90%. Investors defaulted on contracts and liens on owners swept the nation.
When the tulip market first crashed, the Dutch government refused to interfere, advising tulip holders to come up with a plan to stabilize prices and restore public confidence. All plans failed.
As a result, assembled deputies in Amsterdam declared null and void all contracts that were made at the height of the mania. Tulip contracts made after a certain date were nullified if buyers paid just 10% of the prices that they had agreed to pay at the peak period.
Still, tulip prices kept decreasing, despite government efforts to stabilize tulip prices and public credit. In Amsterdam, judges refused to honor tulip contracts, which were now labeled as gambling activities. Payment could not be enforced. Tulip collectors, speculators, and gamblers who had tulips at the time of the collapse lost small fortunes.
Psychologists, economists and market analysts have analyzed the “Tulip Craze” for years (Edelman, 2001). Many have compared it with the dot-com crash that occurred in 2000, in which investors and stockholders lost trillions of dollars on stocks that seemed a sure bet.
Bubbles Throughout History
In addition to the Tulip Craze and the 2000 Dot-com Crash, many other bubbles have been seen throughout history.
During the Roaring 1920’s, a huge bubble was created as the result of an industrial revolution (Cohen, 1997). As new technology introduced cars, radio, utilities and airlines to the mass market in the 1920s, investors were sure that the market could not fail.
However, the Dow Jones industrial average increased from 100 in 1924 to 386 in 1929, and then fell to a low of 40 in 1932. The Great Depression was the result.
The next bubble was seen in the 1960’s, when the U.S. economy was driven by consumer electronics, commercial jet aviation and the interstate highway system. The Dow rose to 995 in 1968, before dropping to 631 in 1970.
After a decade of stability, the 1980’s brought a bubble created by Japan’s economic growth. The country’s urban real estate appreciated in value by more than 5,000%. However, Japan’s relationship of crossholdings between banks and corporations caused a stagnant growth of profits. The 1980’s bubble popped in 1989 and Japan never fully recovered.
Substance and Corruption
The two major factors that determine the outcome of financial bubbles are the degree of substance behind the bubbles and the financial corruption underlying them (Brennan, 2001). Corruption, in this sense, does not simply mean fraud and misdealing, but also a lack of meticulous accountability and regulation.
For example, the tulip craze was a frivolous speculative bubble with virtually no substance and little corruption. However, during the Roaring ’20s, revolutionary technologies saw much financial corruption. Japan in the 1980s also lacked substance because of a corrupt financial system.
The dot-com bubble was similar to the 1960’s bubble in that it was technology-driven with relatively little corruption. Conglomerates, mutual funds and creative accounting inflated the market capitalization of firms; much like day trading and the flexibility of defining revenue did for dot-coms.
Author Martin D. Weiss (2002) claims to know the pitfalls that investors face when they invest in the stock market. Maintaining a close watch over the stock market and other investment vehicles, Weiss provides his clients with valuable information about the stocks they plan to purchase.
Weiss was one of the first to realize that Enron and Global Crossing were practicing corrupt procedures. While other analysts advised clients to “buy” these stocks, Weiss predicted that the companies were headed for bankruptcy.
Weiss’ independent research led him to publish a forecast on the collapse of many savings and loan companies, which was not well received by the investment industry. Yet he stuck to his guns, insisting that some of the nation’s top firms were “cooking the books.” It was not long before the savings and loan industry was exposed.
One of Weiss’ most important revelations was showing investors how Wall Street can promote a company’s stock as a safe one for investors when it is actually a very risky one. Weiss revealed example of how Wall Street and the investment industry can present average investors with misleading information.
At the time of his book’s publication, the Enron and Global Crossing scandals had not been revealed. However, most of what his book talked about happened in these two cases, which made his book a bible for many who feared stock market scams.
Weiss revealed how much of a risk the average investor takes when depending on the buy-and-sell recommendations of money managers and the efficiency of the market. Enron serves as a perfect example.
In March 2000, business correspondent Bethany McLean wrote an article in Fortune magazine, titled, “Is Enron Overpriced?” “It’s in a bunch of complex businesses,” she wrote. “Its financial statements are nearly impenetrable. So why is Enron trading at such a huge multiple? (Weiss, 2002)”
At the time of publication, Wall Street was touting Enron as a safe investment. However, McLean’s story showed that the investment pros were possibly providing misinformation.
At the time, Enron’s stock sold at 55 times trailing earnings. The company bragged that its stock should be selling for $126 a share, and that its profits were skyrocketing. Even the most reputable brokerage houses were buying the company’s hype without looking into what was really going on inside Enron.
McLean stated: “But for all the attention that’s lavished on Enron, the company remains largely impenetrable to outsiders, as even some of its admirers are quick to admit. Start with a pretty straightforward question: How exactly does Enron make its money?”
According to Weiss: “The Stock Market decline of the early twenty-first century was caused neither by terrorists nor war. It was a direct consequence of the Great Stock Market Scam – an elaborate system of deceptions that threatened the retirement savings of millions of Americans over age 50. (p. 196)”
As an example, Weiss pointed out, that in April 1999, Morgan Stanley Dean Whitter plus 18 other Wall Street Brokerage firms recommended that investors buy stock in Priceline.com, which “could have transformed a comfortable retirement into a lifetime of welfare.”
At the time of the recommendation, Priceline’s stock was selling for $104. In February 2003, it sold for $1.25. Weiss blames careless recommendations like these on “misinformation.”
Indeed, the critical information you need to make sound investment decisions was – and is – passed through a series of filters, each removing some piece of bad news, each adding a new layer of hype, distortion, or even outright lies.”
Short Selling Before and After Bubbles
According to a recent article on ResearchStock.com (Wayman, 2002) a revised and less innocent version of short selling has hit the stock market. Known as “short and distort,” it occurs when sellers use misinformation and a bear market to manipulate stocks.
Short and distort is just as illegal as the more popular pump and dump, which is an illegal practice in which a small group of investors buys a stock before recommending it to thousands of investors. As a result, the price rapidly increases then decreases. Those who bought the stock early sell it when the price peaks.
However, short and distort occurs mostly in a bear market, which rarely occurs, so few investors are aware of the dangers and means of protecting themselves.
Unlike short sellers, short and distort traders manipulate stock prices in a bear market by taking short positions and then using false information to drive down the price of the targeted stock.
In most cases, it is easier to manipulate stocks to decrease in a bear market and increase in a bull market. The pump and dump is more publicized because of the long bull market and the media attention it received. The stock market was in an upswing for several years starting in the 1980’s, during which time investors learned about the pump and dump. However, many of today’s investors are inexperienced with bear markets and are unaware of the short and distort.
Many short and distort traders attempt to turn a profit by creating fear amongst investors. They may use online screen names that imply association with the Securities Exchange Commission or Nasdaq or say that they have a foolproof method of determining which stocks are worthless. Short and distort traders basically aspire to convince investors that they are acting in the investors’ best interests.
If these traders are successful, investors who initially bought stock at higher prices sell at low prices because they are convinced that the stock is worthless because of misinformation. At that point, the short and distort traders cover at low prices and keep the profits.
As a result of the Enron scandal and current market conditions, investors are more likely to fall prey to this type of manipulation than they may have been in the 1990’s bull market. Fear causes investors to overreact without checking information. Unfortunately, this affects the stock market’s performance, as both growing companies and investors are getting taken for a ride.
If the market were truly efficient, this would not occur. Investors would have access to accurate information and react to misinformation in a rational way.
Behavioral finance examines the effects of investor psychology on stock prices. Research in this field has shown that there are many predictable patterns in the stock market. For example, investors have a tendency to buy undervalued stocks and sell overvalued stocks. Therefore, in a market with thousands of investors, the market cannot be efficient.
According to Paul Krugman, an economics professor (Haugen, 1999), due to the mass mentality of trendy, short-term shareholders, investors pull in and out of the latest and trendiest stocks. This results in the distortion of stock prices and an inefficient market being inefficient. As a result, the market no longer reflects only all available information in the market. Prices are instead being manipulated by profit-seekers.
The EMH accepts the possibility that anomalies in the market may result in greater profits. The EMH does not require prices to be equal to fair value all of the time. Prices can be over or undervalued only in random occurrences, so they eventually resort back to their average value. Because of this, the deviations from a stock’s fair price are random, and investment strategies that result in outperforming the market are not believed to be consistent phenomena.
The EMH states that a successful investor who outperforms the market is lucky, not skilled. The laws of probability state that, when there are large numbers of investors in a given market, some will overperform, some will under-perform, and some will maintain the average.
For a market to become efficient, there must be investors that believe it is inefficient and can be beaten. Investment strategies intended to manipulate inefficiencies work to keep a market efficient. In addition, a market must be large and liquid. In addition, here has to be a good deal of information available to all parties.
According to the EMH, transaction costs must be less expensive than the expected profits of an investment strategy, and investors must have enough funds to take advantage of inefficiency until it disappears again.
Richard Minsky, in a 1999 article, wrote, “I was sitting in front of my computer last December when an item came on the Business Wire “MBT International Prepares To Launch Online Auction Applications For $300 Billion Agricultural Industry.” I clicked a few buttons and bought 2000 shares at $4i. An hour later it was up to $8 and I sold it. I should have held on — “it went almost to $14 before it pulled back to close at 8.
As an economist, though, I couldn’t help but wonder: “What’s really going on here, and how will this impact the economy?” The first inkling I had that something was happening was just a year ago, when my Russian immigrant auto mechanic, Gary, called me. “Richie,” he said excitedly, “Serge is on the cover of Forbes Magazine, I have a copy for you.” I had been keeping my 18-year-old Lincoln running, thanks to Gary’s continuous attention, and we had become close friends. I had known his son Serge Milman since he was 10 years old. When Gary complained to me that all Serge wanted to do was play computer games, I told Gary “get him a faster computer.” Even though I always believed that those games would build skills for success, I never imagined how Serge would apply them. By the age of 25 he was among the first of the “SOES Bandits” – stock traders who would use the Small Order Execution System to profit from the spread between the buy and sell positions of a stock, buying above the high bid and selling below the ask price in a few seconds. The person who clicks the button the fastest gets the trade, which is where the eye-click training of video games becomes critical.”
As online trading grows more and more popular, average people can now become traders instead of investors. However, as they enter the world of trading, they do not realize that two of the biggest emotions a successful trader must get past are fear and greed.
When these inexperienced traders see a trade turn a profit, they become greedy and do not know when to sell the stock. Many of these traders lose respect for the actual value of a dollar, much like gamblers, who start to see money as chips instead of real dollars.
When greed and fear penetrate the minds of investors, the stock market performance is significantly affected. With greed, a bull market is the outcome. One example is the 2000 technology boom. However, this market is generally doomed for failure. When the market crashes, the feeling of greed is replaced with one of fear.
This fear becomes the dominant emotion in the market, switching it to a bear market. Fear decreases confidence in the market, whether that fear is of accounting scandals or poor performance.
In July 2002, the market indices fell in the range of 25-30%, hitting five-year lows. This drop was undoubtedly caused by a lack of confidence in the market.
Fear and the Market
International investor Raj Rajaratnam described fear and market in a recent interview: “What drives the emotional side of stock markets is greed and fear. When markets are in fear it is time to be greedy and when markets are greedy it’s time to fear. When the market is in euphoria it is the best time to sell.”
For markets to efficiently set prices and value, they must have willing buyers and sellers, who are not under pressure to sell. In addition, these buyers and sellers must possess equal and complete knowledge. If one investor has more information than another, it would man that he would have an advantage.
The stock market is at the center of the capitalistic system, which sets prices, determines how goods and services are distributed, and encourages further growth of the system with benefits for all involved. Therefore, the stock market should be a fair system.
In a perfect market, there would be an abundance of buyers and sellers, standardized products, perfect knowledge, and real-time information. In this perfect market, prices would be determined by the independent judgment of all of the buyers and sellers in the market. Everybody would have equal information and there would be no advantage. This market would be perfectly efficient.
In a perfectly efficient market, an investor would not have access to additional information that other investors did not have. Every investor would know the latest data regarding every stock and its economic prospects. Individual investors would not need sophisticated institutions, as they would have little chance of underperforming.
The existing stock market is not a perfect one. Therefore, researchers argue that it cannot be an efficient one. While the classic economic theory does a fair job of predicting prices in simple buying and selling transactions, it fails to account for the influence of traders’ experience on a market’s efficiency.
When it comes to markets, human tendency leans more towards irrational exuberance than rational, informed decision-making processes.
The Theory of Chaos
The efficient market lacks an explanation for speculative bubbles that lead to stock crashes. Chaotic theories aim to show a pattern behind the mass hysteria seen in bubbles. These models are deterministic mathematical models that describe every nuance of the behavior of the variables in question.
The observations that result from chaotic theories have the following properties (Keane, 1988, p. 36-138):
They appear random, even if they are subject to sophisticated statistical analysis. In many studies, stock prices have been proven completely random.
No pattern repeats itself. Therefore, even with infinite data, no two patterns can ever be identical. Even after years of studying past patterns, technical analysts have not been able to systematically beat the market.
The time series of chaotic theories is subject to sharp and extensive breaks in the typical pattern, which is completely undetermined by past events. Therefore, a series of observations with a high degree of volatility and an upward trend can be quickly replaced by a flat downward pattern.
The qualitative behavior of a chaotic time series is subject to total upheaval in response to even the smallest changes in the values of underlying parameters. Perhaps this is why a justifiable cause for Black Monday cannot be found
According to many researchers, chaotic models are non-random, and completely predictable. While these models aim to replace the EMH, they remain untested and demand further empirical research into this area.
In June 2000, Celera Genomics made a public announcement that they had completed a draft map of the human genetic code, an extraordinary achievement, and investors sent Celera’s stock into a downward spiral immediately (Davey, 2000). In turn, Celera’s competitors plunged, as well.
The reason for this was that investors knew about the announcement prior to the fact. “Momentum investors started running the stocks up two weeks ago in anticipation of this big announcement,” said Rod Raynovich, a biotech consultant with Raygent Capital, in a Red herring article (2000). “It was a momentum phenomenon that was sparked by the media.”
In a matter of days, Celera’s stock dropped about $50 per share. “It’s a classic buy-on-the-rumor and sell-on-the-news mentality,” said Andrew Milne, an analyst with Dain Rauscher (Davey, 2000). “There was a lot of enthusiasm priced into many of these stocks.”
In today’s information age, investors have a variety of tools that encourage them to participate in this buy-on-the-rumor and sell-on-the-news mentality. There are several Web sites that actually make rumors their stock in trade. Investors can enter a ticker symbol to see the supposed whisper number, or rumored earnings figure, for a specific stock.
After getting the whisper number, investors can view a company’s previous quarters and see if it has come out with positive or negative earnings surprises. After finding a pattern, they can invest based on this information.
According to market fundamentalists, it is possible to predict stock market direction by understanding the fundamentals of the market, including earnings, and interest rate. On the other hand, technical analysts say that the market’s direction can best be determined by looking at price, volume and other indicators of current market activity.
Technical analysts do not believe that fundamentals cannot cause markets to move. Instead, they believe that fundamentals are already factored into a stock’s price. Therefore, watching price and volume is the best way to outperform the market.
On Wall Street, they say, “Buy on the rumor, sell on the news.” In many cases, a stock will rise on rumors of high earnings and other growth prospects.
This saying is based on the premise hat when the news comes out, it is usually too late to do anything about it. In most merger cases, heavy buying starts long before the merger is announced. While insider trading is illegal, rumors cannot be stopped.
Investing in the stock market is a very emotional process for most people. The more that they invest, the greater their emotional involvement. Every time their stocks increase in value, they experience joy. When their stock decreases in value, they feel sorrow.
Most people lose money in the market because they rely on the market’s efficiency without understanding that the market is motivated by reasons other than making money or avoiding losses. These reasons include conversations with peers, panic over imagined events and many others.
A sharp increase in price makes people feel optimistic. As a result, they buy or hold. A sharp decrease in price makes them feel pessimistic. As a result, they want to sell but do not want to take the loss. In many cases, there is too much ego involved in the financial decision-making process. These emotional swings suggest that the market cannot be efficient.
The following data was taken from a dissertation survey conducted in January and February 2003. Two financial editors were consulted to offer revisions to the questionnaire. When the survey was ready for distribution, it was sent to 30 financial professionals, including investment managers, financial analysts and financial writers. The participants were guaranteed that their identities would remain anonymous.
The survey had two qualifying questions: 1) Are you a full-time professional in the finance industry, and 2) Are you familiar with the efficient market hypothesis (EMH)? Affirmative answers to these questions allowed the respondents to continue answering questions. Those who answered “no” to either question were asked to return the questionnaire. A total of 10 respondents qualified for and agreed to participate in the survey.
In the questionnaire faculty respondents were encouraged to contact the researcher to participate in a telephone interview with the surveyor, which would allow for additional information to be gathered. Four of the 10 participants responded to the request and were subsequently interviewed. The remaining six filled out a written questionnaire.
Part 1 and 2– Survey Participant Profile
Number of Participants
Years of Experience
Part 3– Respondents report whether or not they are convinced that the EMH theory is accurate.
Part 4– Respondents report whether or not they believe that the existing paradigm of the EMH should be revised.
Part 5– Respondents report whether or not they believe that psychological behaviors, such as human error, panic, hindsight bias and using insider information in trading stocks, have a significant impact on the performance of the stock market.
Part 6– Respondents report whether or not they believe that the EMH allows for human interaction as a key decision-making process that directly affects the performance of financial markets.
Part 7 — Respondents report what sort of emotions they believe drive people to invest.
A. Optimism (often seen when the stock market goes up)
Part 8 — “Respondents are asked if peer pressure plays a role in investing.
Part 9 — “Respondents report if they believe people are more likely to invest in stocks that they are familiar with, without regarding available information.
Part 10 — “Respondents were given explanations of each of the following anomalies and asked to check the ones that they felt had a strong influence on the performance of the stock market.
Small Firm Effect
P/E Ratio Effect
Human Errors and Behaviors
Part 11– Respondents were asked to identify whether they believed professional investors were more or less likely to fall prey to important logical fallacies and psychological failings when making investment decisions.
Part 12– Respondents were asked to identify whether they believed investors were more or less likely to make informed decisions utilizing all available information than make irrational decisions based on pieces of information.
Part 13– Respondents were asked if they though investors had a tendency to draw analogies and see identical situations in situations where there were actually many differences.
Part 14– Respondents were asked if they though investors had a tendency to place too much emphasis on specific details of a particular situation, while neglecting the outcomes of similar situations in the past.
Part 15– Respondents were asked if they though investors were more or less likely to buy a stock that has a proven record of past performance that one that has greater growth potential but is less known.
Part 16 — “Respondents were asked to determine how often they thought investors acted rationally based on careful consideration of all available information.
Part 17 — “Respondents were asked to determine how often they thought investor behavior was completely rational.
Part 18 — “Respondents were asked to determine how much of traditional financial theory is based on the assumption that people will act rationally when making investment decisions.
Part 19 — “Respondents were asked to determine if they believed that investors avoided selling stocks purely because they wanted to avoid feeling a sense of loss.
Part 20 — “Respondents were asked whether or not they agreed with the following statements.
A. Increasing levels of confidence have not been proven to show correlation with greater success.
B. Many investors believe that they can consistently time the financial markets even if evidence shows that they cannot.
C. Investors tend to place too much weight on recent experience.
D. People have a tendency to view other people’s decisions as the result of disposition but view their own choices as rational.
E. Markets often fail to act as they should if trading were actually dominated by fully rational investors.
F. Deviations from a stock’s fair price are random, and investment strategies that result in outperforming the market are inconsistent phenomena.
G. A successful investor who consistently outperforms the market is lucky, not skilled.
H. Investment strategies intended to manipulate inefficiencies work to keep a market efficient.
I. Transaction costs involved in technical analysis are usually more expensive than the expected profits of an investment strategy.
J. Stock prices can be over or undervalued only in random occurrences, so they eventually resort back to their average value.
Part 21– Respondents report whether or not they believe that the stock market always processes new information quickly and accurately.
Part 22– Respondents report whether or not they believe that it is possible for stocks to be overvalued or undervalued.
Part 23– Respondents report whether or not they believe that the stock market always processes new information quickly and accurately.
Part 24– Respondents report whether or not they believe that investors have a strong tendency to “buy on the rumor, sell on the news.”
Part 25– Respondents report whether or not they believe that insider information has a long-term effect on the stock market performance.
Part 26– Respondents report whether or not they believe that it is possible to consistently outperform the stock market.
Part 27– Respondents report whether or not they believe that misinformation, such as unusual accounting procedures, has a long-term effect on the stock market performance.
Part 28– Respondents report whether or not they believe that technical analysts can beat the market
Part 29– Respondents report whether or not they believe that the stock market will someday be completely figured out.
Part 30– Respondents were asked if they though investors were more or less likely to take risks when they were about to lose money than when they stood to make a profit.
Part 31 — “Respondents were asked to read the opinions of famous economists and decide whether or not they agreed with them.
A. According to Peter Bernstein (1992), “it is doubtful” that stock prices are predictable. In his book, he dedicates an entire chapter to the subject, titled “Are Stock Prices Predictable?,” showing that the EMH is dependent on the unpredictability of prices.
The question of whether capital market prices are predictable or not is the focus of the debate on the so-called efficient market hypothesis, where advocates of the EMH seemingly saying that prices are not predictable and the detractors saying that they are. However, this is not precisely what, in its modern form, is meant by the EMH, i.e., it is called the “efficient market hypothesis” and not the “prices are not predictable hypothesis,” because these words are expressing different notions rather than using different words to express an identical notion.”
B. According to Meir Statman (1987): “You have to think about not so much the emotions but first those cognitive biases that people have. People think that they understand the market. Very often they think that they can tell where the market is going to go, based on where the market has been and so very often people extrapolate.” market that has gone up gives them the impression that it will continue to go up. They become euphoric, they double and triple their investment, the market that goes down has gone down gives them the impression that it will continue to go down. In fact, the evidence suggests that if anything markets tend to defy investors; that when investors are euphoric, markets are more likely to go down than to go up.”
C. According to Nobel laureate Herbert Simon, people are overwhelmed by too information and react consciously to only some of it. Simon asserted that when bombarded with information, people digest only a small part of it and tend to come to a different conclusion from what the entire information would suggest.
While the extensive research on the EMH have provided great value and insight into investor research and have furthered our basic understanding of the stock market, there is a great deal of evidence suggesting that the theory is incomplete.
A limited survey of existing research on the EMH and behavioral finance indicates that the EMH fails to account for a variety of key factors when explaining the stock market performance. Researchers have provided substantial evidences that psychological factors, trends, misinformation and more may directly and strongly affect stock prices.
While this research paper does not suggest that the EMH paradigm be completely abandoned, it does address the need for a revision of the theory that will allow for the psychological and speculative aspects of the stock market.
The following is a list of investor characteristics that the survey respondents ranked as most important in determining future stock performance:
The Disposition Effect: This describes the tendency of investors to hold on to losing stock and let go of winning stocks. The disposition effect is fueled by human desire to avid pain and loss. If an investor does not drop his losing stocks, he avoids the feeling of loss and can remain optimistic about future performance. If, like the efficient market theory states, the investor looked at all available information, he would make a rational decision and drop the stock. However, most investors are guilty of the human error known as the disposition effect.
Hindsight Bias — “This human error refers to the way investors perceive the past. While good investments are seen as inevitable, bad ones require blame. Most investors do not give themselves much credit when they make a good decision yet place a lot of blame on themselves when they make a bad one. Furthermore, when investors make a bad investment, they tend to either shy away from the market or dump more money into it, which has a significant affect on the stock market performance.
Overconfidence — Many stocks overtrade due to overconfidence, which is an irrational and innate human trait. Human beings have a basic instinct that makes us desire control over the uncontrollable. Many people rely on their imagined superiority of knowledge, rationality, and ability to process information that will help them choose above-average stocks. Unfortunately, it is this same human trait that works as a disadvantage. People often make bold and irrational decisions, as they cannot predict the dangers that the future may have in store for them. Humans have a natural tendency to react instinctively rather than rationally. When we feel safe, we take greater risks. When we feel insecure, we proceed with caution.
Magical thinking: Magical thinking refers to subjective speculation about how markets will behave. It is hard to predict how well a particular stock will perform when making financial decisions. Therefore, most investors will rely on their feelings or intuitions that certain stocks will perform well even if logical statistics tell them that this is impossible. Research shows that people will place larger bets on a coin that has not yet been tossed than on a coin that has already been tossed, even if outcome of the toss has yet to be revealed.
The results of this survey show a need to incorporate human behavior into the efficient market paradigm. As a result of this research, I suggest a simple revision to the traditional model of market behavior. The market should not be viewed as a computer but a living thing that consists of the human intellect and emotions of all its investors.
This living thing should be expected to constantly change, as a result of rapid growth during a bull market and panic and caution during a bear market. It should be seen as a constantly evolving entity that changes every time money is added or taken from it. It must assume that its investors will open new accounts, close existing ones or hold onto bad ones.
EMH proponents may argue that the traditional theories account for all of this. However, my proposed system will be expected to change constantly, as its investors will be expected to act based on their emotions. This theory will assume that the price of stocks will be influenced by both new information about the stock and levels of fear or greed among its investors.
This model is similar to Mr. Market, as it fits its criteria, yet it also aims to explain long market cycles. While markets have memories, its memory is collective and constantly changing, as new players enter the market and new ones leave it. My model assumes that the market is more affected by things that yesterday’s events than events of decades past.
The efficient market theory must be revised to include the emotional attachment most investors feel toward rising and falling stock prices. The efficient market theory must also take into account the human errors, heuristic bias, use of misinformation, psychological tendencies, in determining future expected performance and obtainable profits.
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