A Literature Review on Capital Market Efficiency
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1-1 Capital market efficiency:
The concept of efficiency is central to finance. Primarily, the term efficiency is used to describe a market in which relevant information is impounded into the price of financial assets (Dimson & Mussavian, 2000). The market is found to be somewhat inefficient and simple wagering strategies are identified that result in profitable returns (Woodland & Woodland, 2001). Considerable research in economics and finance has been devoted to the investigation of the efficient markets hypothesis. An issue that is the subject of intense debate among academics and financial professionals is the Efficient Market Hypothesis (EMH) (Higgins, 1992). The fundamental question is whether prices fully reflect available information. If not, then in financial markets, it would be possible for an investor to devise a strategy that would earn above-average returns (Woodland & Woodland, 2001).
1-2 The Efficient Market Hypothesis
EMH evolved in the 1960s from the Ph.D. dissertation of Eugene Fama. According to Fama (1965), an efficient market is defined as a market where there are large numbers of rational, profit-maximizes actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. Fama (1965) adds that in an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value.
Moreover, Fama (1965) and Achelis (2003) state that security prices correctly and almost immediately reflect all information and expectations fully reflect all available information. EMH says that one cannot consistently outperform the stock market due to the random nature in which information arrives and the fact that prices react and adjust almost immediately to reflect the latest information (Achelis, 2003). Therefore, it assumes that at any given time, the market correctly prices all securities; and the result is that securities cannot be overpriced or under priced for a long enough period of time to profit there from Achelis (2003).
Most individuals buy and sell under the assumption that the securities they are buying are worth more than the price that they are paying, while securities that they are selling are worth less than the selling price (Fama, 1965). But if markets are efficient and current prices fully reflect all information, then buying and selling securities in an attempt to outperform the market will effectively be a game of chance rather than skill (Higgins, 1992).
1-3 Levels of Market Efficiency
1.3.1The Weak form
Fama (1970) made a distinction between three forms of EMH: the weak form, the semi-strong form, and the strong form. The weak form of the hypothesis suggests that past prices or returns reflect future prices or returns (Russel & Torbey, 2003). It also asserts that all past market prices and data are fully reflected in securities prices, therefore, technical analysis is of no use (Higgins, 1992).
The inconsistent performance of technical analysts suggests that this form holds (Russel & Torbey, 2003). However, Fama (1991) expands the concept of the weak form to include predicting future returns with the use of accounting or macroeconomic variables. Russel and Torbey (2003) state that the evidence of predictability of returns provides an argument against the weak form.
1.3.2 The Semi-strong form
Fama (1991) states that the semi-strong form of EMH asserts that security prices reflect all publicly available information. (Higgins, 1992) says that this form asserts that all publicly available information is fully reflected in securities prices so fundamental analysis is of no use. In addition, according to Russel and Torbey (2003), there are no undervalued or overvalued securities and thus, trading rules are incapable of producing superior returns. When new information is released, it is fully incorporated into the price rather speedily. The availability of intraday data enabled tests which offer evidence of public information impacting stock prices within minutes (Patell & Wolfson, 1984; Gosnell, Keown & Pinkerton, 1996). The semi-strong form has been the basis for most empirical research on the tests of market efficiency; however, recent research is including the weak form on the test (Russel & Torbey, 2003).
1.3.3 The Strong form
The strong form suggests that securities prices reflect all available information, even private information (Fama, 1991). According to Higgins (1992), this form asserts that all information is fully reflected in securities prices; as a result, even insider information is of no use. Seyhun (1998) provides sufficient evidence that insiders profit from trading on information not already incorporated into prices. Hence the strong form does not hold in a world with an uneven playing field (Russel & Torbey, 2003).
1-4 Some Common Misconception about Market Efficiency
Much of the criticism of the EMH has been based on a misunderstanding of the hypothesis says and dose not says, Clarke (2000) present some of the most persistent “Myths” about the EMH below.
1.4.1 Myth 1 EMH claims that new information is always fully reflected in market prices. Yet one can observe prices fluctuating (sometimes very dramatically) every day, hour, and minute. Therefore, EMH must be incorrect.
The constant fluctuation of market prices can be viewed as an indication that markets
Are efficient. New information affecting the value of securities arrives constantly, causing continuous adjustment of prices to information updates. In fact, observing that prices did not change would be inconsistent with market efficiency, since they know that relevant information is arriving almost continuously.
1.4.2 Myth 2 EMH claims that financial analysis is pointless and investors who attempt to research security prices are wasting their time. There are two principal counter-arguments against the equivalency of” dart-throwing” and professional analysis strategies.
First, investors generally have different “tastes” –some may, for example, prefer to put their money in high-risk “hi-tech” firm portfolios, while others may like less risky investment strategies. Optimal portfolios should provide the investor with the combination of return and risk that the investor finds desirable. A randomly chosen portfolio may not accomplish this goal.
Second, and more importantly, financial analysis is far from pointless in efficient capital markets. The competition among investors who actively seek and analyze new information with the goal to identify and take advantage of mis-priced stocks is truly essential for the existence of efficient capital markets.
In fact, one can say that financial analysis is actually the engine that enables incoming information to get quickly reflected into security prices.
1.4.3 Myth 3 EMH does not imply that investors are unable to outperform the market. They know that the constant arrival of information makes prices fluctuate. It is possible for an investor to “make a killing” if newly released information causes the price of the security the investor owns to substantially increase. What EMH does claim, though, is that one should not be expected to outperform the market predictably or consistently.
1.4.4 Myth 4 EMH presumes that all investors have to be informed, skilled, and able to constantly analyze the flow of new information. Still, the majority of common investors are not trained financial experts. Therefore, EMH must be incorrect.
This is an incorrect statement of the underlying assumptions needed for markets to be
Efficient. Not all investors have to be informed. In fact, market efficiency can be
Achieved even if only a relatively small core of informed and skilled investors trade in the market, while the majority of investors never follow the securities they trade.
Finally, we can show some notes about common mistaken beliefs about efficient market as the following:
1-Market are inefficient due to only a small fraction of the total number of shares in the market is traded each day (this nonsense because there is little incentive to buy or sell if systematic abnormal profits are impossible due to market efficiency, especially as trading is costly.
2-Prices fluctuate daily (this is nonsense because they would expect prices to fluctuate in response to the arrival of new information).
3-If market is efficiency it does not matter which shares they invest in. (this is nonsense because they could find themselves with an unbalanced, e.g. very risky under versifies portfolio or a portfolio which is tax- inefficient).
4-If markets are efficient investor must be stupid (this is nonsense because efficiency assumes investor quickly and accurately interpret information and are not easily fooled).
The following part will be reviews the emergences of behavioural finance it will be cover the evidence against and the evidence for market efficiency then the researcher discuss structure of section “the goal of behavioural finance” and the end of this part (two) I would like to show lessons of market efficiency.
2.1 Behavioural Finance
“Behavioural” finance has recently become a subject of significant interest to investors. Because it is a relatively new and evolving field in economics and consequently not well defined, a legitimate question is: “What exactly is “behavioural” finance?” Russell (2000) describes “behavioural” finance in the following ways:
v “Behavioural” finance is the integration of classical economics and finance with
Psychology and the decision-making sciences.
v “Behavioural” finance is an attempt to explain what causes some of the anomalies.
v “Behavioural” finance is the study of how investors systematically make errors in judgement, or “mental mistakes.”
All economic models make simplifying assumptions about both market conditions
And the “behaviour” of market participants. Sometimes the simplifying assumptions
Underlying the model is explicitly stated and sometimes the assumptions are implicit: the latter is often the case regarding the “behavioural” assumptions underlying the model.
To illustrate, it is useful to consider the efficient market hypothesis (EMH), an economic model of considerable importance to investors. The simplifying assumptions regarding market conditions that underlie the EMH frequently include, among others, assumptions such as:
v Transaction costs are zero.
v Markets are not segmented.
v Easy (even unlimited) entry into the security markets exists.
The “behavioural” assumptions that underlie the EMH can be expressed as:
v Investors act, in an unbiased fashion, to maximise the value of their portfolios.
v Investors always act in their own self-interest.
The first “behavioural” assumption is frequently stated as investors are “rational expectations wealth maxi misers” – this means that investors form unbiased expectations of the future and given these expectations, they buy and sell in the securities markets at prices which they believe will maximise the future value of their portfolios.
“Behavioural” finance questions whether the” behavioural” assumptions underlying the EMH are true. For example, there is an assumption that individuals always act in their economic self-interest.
This appears to be violated by “social investing” such as arbitrarily deciding not to invest in tobacco stocks or deciding to overweight environmentally clean industries, etc. Such “behaviour” is not consistent with pure wealth maximisation, if for no other reason that opportunities for forming better-diversified portfolios are foregone.
Why investors might engage in non-wealth maximising “behaviour”, and what are the implications of such “behaviour” for security pricing, are areas of inquiry in “behavioural” finance.
Another aspect of “behavioural” finance concerns how investors form expectations regarding the future and how these expectations are transformed into security prices. Researchers in cognitive psychology and the decision sciences have documented that, under certain conditions, people systematically make errors in judgement or mental mistakes. These mental mistakes can cause investors to form biased expectations regarding the future that, in turn, can cause securities to be mispriced.
By considering that investors may not always act in a wealth maximising manner and that investors may have biased expectations, “behavioural” finance may be able to explain some of the anomalies with respect to the EMH that have been reported in the finance literature. Anomalous returns such as those associated with “value” stocks, earnings surprises, short-term momentum and long-term price reversals are fertile ground for researchers in “behavioural” finance.
2.2 Emergence of Behavioural Finance
Many investors have long considered that psychology plays a key role in determining the “behaviour” of markets. However it is only in recent times that a series of concerted formal studies have been undertaken in this area. Slovic's (1972) paper on individual's misperceptions about risk and Tversky and Kahneman's papers on heuristic driven decision biases (1974) and decision frames (1979) played a seminal role. The results of these studies were at variance with the rational, self-interested decision-maker posited by traditional finance and economics theory.
Although several definitions of “behavioural” finance exist, there is considerable
agreement between them. Lintner (1998) defines “behavioural” finance as being `the study of how humans interpret and act on information to make informed investment decisions' (p.7). Thaler (1999) defines “behavioural” finance as `simply open-minded finance' claiming that `sometimes in order to find the solution to an [financial] empirical puzzle it is necessary to entertain the possibility that some of the agents in the economy behave less than fully rationally some of the time' (p. xvii). Olsen (1998) asserts that “behavioural” finance does not try to define `rational' “behaviour” or label decision making as biased or faulty; it seeks to understand and predict systematic financial market implications of psychological decision processes.' (p.11). It should be noted that no unified theory of “behavioural” finance exists at this time. Olsen (1998) points out that most of the emphasis in the literature thus far `has been on identifying “behavioural “decision making attributes that are likely to have systematic effects on financial market “behaviour” (p. 12).
2.3 Rational man
Under the paradigm of traditional financial economics, decision makers are
Considered to be rational and utility maximising. In contrast, cognitive psychology
Suggests that human decision processes are subject to several cognitive illusions.
These can be grouped into two classifications, illusions due to heuristic decision
processes and illusions caused by the adoption of mental frames.
2.4 Heuristic decision processes
Heuristics refer to rules of thumb which humans use to made decisions in complex,
Uncertain environments. The decision making process is not a strictly rational one
Where all relevant information is collected and objectively evaluated, rather the
Decision maker takes mental `short cuts' in the process (Kahneman and Tversky
1974). There may be good practical reasons for adopting a heuristic decision process, particularly when time available for decision making is limited. Researchers in evolutionary psychology have suggested that many human decision making heuristics have their roots in human evolution (Barrow 1992). However, as shall be seen, heuristic decision processes may result in poorer decision outcomes. Typical examples of illusions resulting from the use of heuristics include:
v Representative ness
v Gambler's fallacy
v Availability bias
2.4.1 Representative ness
This heuristic is the source of the adage, "if it looks like a duck and quacks like a duck, it probably is a duck." With respect to forming expectations, people evaluate the probability of an uncertain future event by the degree to which it is similar to recently observed events. Representative ness can cause investors to overreact to new information, i.e., investors give new information too much weight in forming their expectations about the future.
Representative ness refers to the tendency of decision makers to make decisions based on stereotypes that is to see patterns where perhaps none exist. Representative ness also arises in the guise of the `law of small numbers' whereby investors tend to assume that recent events will continue into the future. In financial markets this can manifest itself when investors seek to buy `hot' stocks and to avoid stocks which have performed poorly in the recent past. This “behaviour” could provide an explanation for investor overreaction, an effect which was suggested by DeBondt and Thaler (1985).
People are grossly overconfident regarding their ability and their knowledge. For example, when people say that they are 90 percent sure that an event will happen or that a statement is true, they typically are correct less than 70 percent of time. Overconfidence can cause investors to under react to new information.
Overconfidence leads investors tend to overestimate their `predictive' skills and
Believe they can `time' the market. Studies have shown that one side effect of investor overconfidence is excessive trading. Overconfidence is by no means limited to individual investors. There is evidence that financial analysts are slow to revise their previous assessment of a company's likely future performance, even when there is notable evidence that their existing assessment is incorrect.
Psychologists have documented that when people make quantitative estimates; their estimates may be heavily influenced by previous values of the item. For example, it is not an accident that a used car salesman always starts negotiating with a high price and then works down. The salesman is trying to get the consumer anchored on the high price so that when he offers a lower price, the consumer will estimate that the lower price represents a good value. Anchoring can cause investors to under react to new information.
Anchoring arises when a value scale is fixed or anchored by recent observations. This can lead investors to expect a share to continue to trade in a defined range or to expect a company's earnings to be in line with historical trends, leading to possible under reaction to trend changes.
Gambler’s Fallacy arises when people inappropriately predict that a trend will reverse. This tendency may lead investors to anticipate the end of a run of good (or poor) market returns. Gamblers' fallacy can be considered to be an extreme belief in regression to the mean. Regression to the mean is found in many human systems and implies that an extreme trend will tend to move closer to the mean over time. Sometimes regression to the mean is incorrectly interpreted as implying that, for example, an upward trend must be followed by a downward trend in order to satisfy a law of averages.
Availability Bias Emerges when people place undue weight on [easily] available
Information in making a decision.
Although the above examples of cognitive illusions are widely observed, “behavioural” finance does not claim that all investors will suffer from the same illusion simultaneously. The susceptibility of an individual investor to a particular illusion is likely to be a function of several variables. For example, there is suggestive evidence that the experience of the investor has an explanatory role in this regard with less experienced investors being prone to extrapolation (representative ness) whilst more experienced investors commit gambler fallacy (Shefrin 2000, p.52).
2.5 Prospect theory
The second group of illusions which can impact on decision processes are conveniently grouped in Prospect Theory (Kahneman and Tversky 1979). This theory proposes a descriptive framework for the way people make decisions under conditions of risk and uncertainty and embodies a richer “behavioural” framework than that of subjective expected utility theory which underlies many economic models. Prospect Theory may be represented in a number of ways but in essence, it describes several states of mind that can be expected to influence an individual's decision making processes. The key concepts addressed by the theory include
v Loss aversion
v Regret aversion
v Mental accounting
v Self control
2.5.1 Loss aversion
Loss aversion is based on the idea that the mental penalty associated with a given loss is greater than the mental reward from a gain of the same size. If investors are loss averse, they may be reluctant to realise losses. This can explain the sunk cost effect whereby decision makers persist in including past costs when evaluating current decision alternatives. Loss aversion need not imply that investors are consistent in their attitude to risk. A key assumption of economic theory is that investors are risk averse. This may not always hold true in the real world. There is evidence that people play safe when protecting gains but are willing to take chances in an attempt to escape from a losing position.
2.5.2 Regret aversion
Regret aversion arises because of peoples' desire to avoid feeling the pain of regret resulting from a poor ([investment] decision. Regret aversion embodies more than just the pain of financial loss. It includes the pain of feeling responsible for the decision which gave rise to the loss. This aversion can encourage investors to hold poorly performing shares as avoiding their sale also avoids the recognition of the associated loss.
The wish to avoid regret may bias new investment decisions of investors as they may be less willing to invest new sums in investments or markets which have performed poorly in the recent past. The wish to avoid regret may provide a partial explanation for the dividend puzzle, why do firms pay dividends? In the absence of tax considerations, investors should be indifferent as to whether a firm pays a dividend or retains earnings internally as they could manufacture dividends, if required, by selling stock. However, selling stock exposes the investor to the risk of regret if the stock price were to later rise.
The notion of regret aversion may encourage investor herding “behaviour”, for
Example, to invest in `respected companies' as these investments carry implicit
Insurance against regret (Koening 1999). This aversion may also impact on the
“Behaviour” of professional fund managers who may sell loss making stocks before the end of a quarter to avoid having to explain to investors why they are holding funds in poorly performing shares.
2.5.3 Mental accounting
Mental accounting is the name given to the propensity of individuals to organise their world into separate `mental accounts'. Investors tend to treat each element of their investment portfolio separately. This can lead to inefficient decision making. It has been noted that people are often not consistent in making their investment decisions. For example, an individual may borrow at high interest to buy a consumer item whilst simultaneously saving at lower interest rates for a child's college fund. The tendency to adopt mental accounting has implications for portfolio rebalancing whereby investors may be less willing to sell a losing investment because its `account' is showing a loss.
Another aspect of mental accounting relates to observations that people vary in their attitudes to risk between their mental accounts. Investors may be risk averse in their downside protection accounts and risk seeking in their more speculative accounts. Framing wealth into separate mental accounts has the drawbacks noted by Markowitz, covariances between accounts are ignored and investment portfolios lie below the efficient frontier.
2.5.4 Self control
This framing may be explained by imperfect investor self-control. As noted by Tahler and Shefrin (1981), investors are subject to temptation and they look for tools to improve self-control. By mentally separating their financial resources into capital and `available for expenditure' pools, investors can control their urge to over consume
2.6 Potential implications for financial Markets and the EMH
Shefrin (2000) contends that `heuristic driven bias and framing effects cause market prices to deviate from fundamental values' (p. 5). Olsen (1998) suggests that “behavioural” finance may offer an explanation for empirical evidence which casts doubt on existing financial models. DeBondt and Thaler (1985) argued that because investors rely on the representative ness heuristic, they could become overly optimistic about past winners and overly pessimistic about past losers and that this bias could cause prices to deviate from their fundamental level. Anchoring and overconfidence may lead analysts not to adjust their earnings estimates sufficiently when surprises occur. This could lead to subsequent price adjustments as analysts revise their incorrect estimates.
If the tenets of behavioural finance are correct, several implications may arise
Regarding possible “behavioural” patterns in financial markets. There may be:
v Over or under-reaction to price changes or news
v Extrapolation of past trends into the future
v Lack of attention to fundamentals underlying a stock
v Focus on popular stocks
v Seasonal price cycles
If such patterns exist, there may be scope for investors to exploit the resulting pricing anomalies in order to obtain superior risk adjusted returns. On a theoretical level, if exploitable pricing anomalies exist, the current credibility of the EMH is undermined.
The inherent difficulties involved in testing strict hypotheses regarding the EMH
Would make it difficult to reject the hypothesis outright, as supporters of the
Hypothesis could argue that “behavioural” finance had indeed uncovered some
Interesting insights but the potential to build a trading system which relies on these
Vanishes once significant attention is focused on them. At present there is no detailed framework incorporating the varying strands of “behavioural” finance. In the absence of this, there may be scope to develop models which incorporate “behavioural” explanatory variables which outperform traditional financial models. In essence, these models would generate `new' information which had not previously been incorporated in investors' decision models.
2.7 Counter arguments of traditional financial theorists
Traditional financial theorists have undertaken a strong defence of the EMH model. It has been suggested that observed market anomalies may arise, not because of “behavioural” issues, rather because of mis-specified systematic risk (for example through the use of incorrect asset pricing models) or because of data snooping. If a sufficient number of empirical tests are performed on a complex system, some will naturally contain surprising results due to chance. Fama (1998a) argues that `apparent overreaction of stock prices to information is about as common as under-reaction' and suggests that this finding is consistent `with the market efficiency hypothesis that the anomalies are chance events' (p.16).
If cognitive illusions are to have implications for market “behaviour”, it would seem reasonable to conclude that they must occur systematically through time and across cultures. Tversky considered that the illusions did occur systematically because they arose from heuristics which people employed in making decisions in complex, uncertain environments.
Evidence which casts doubt on this arose in Michaud et al. (1996). This study tested several popular stock market anomalies, using data drawn from several stock markets and found that none of the factors had consistent impact on the security returns across all markets at all times. Within specific markets, certain factors were found to have a significant impact at certain times but not at others. These findings do not support Tversky's claim that cognitive illusions result in systematic biased decision making over time and across cultures.
It should also be remembered that markets are essentially auction places. For every seller there must be a buyer if a trade is to be consummated. The EMH does not require that all investors necessarily act in a rational manner. The principles of
Arbitrage, if arbitrage can be undertaken efficiently, would quickly drive prices to
Their `correct' level if one of the parties was rational.
The “behaviour” of markets which are composed of both rational and noise traders is not well understood. Thaler (1999, p. xvii) suggests that in a world inhabited by both rational and noise traders, assets widely held by noise traders may impound an additional risk premium, the risk that noise traders will become less optimistic about the future. Consequently, rational traders may demand a risk premium to bear this additional risk. This may partly explain the closed-end fund puzzle, whereby the market value of such funds is often at a notable discount to their underlying asset value. This risk factor is not considered in most asset pricing models. Most of the research underlying “behavioural” finance has been performed at individual investor level. Financial markets reflect the results of the “behaviour” of a large number of individuals. In summary, an implicit assumption of “behavioural” finance is that their findings at individual level are scaleable to market level. This is unproven as yet.
2.8 Evidence that should worry efficient market Advocates
Thaler (1999) briefly discusses five areas in which behaviour in the real world seems most at odds with the theories in textbooks.
Standard models of asset markets predict that participants will trade very little. The reason is that in a world where everyone knows that traders are rational A knows that B IS rational, B knows that A is rational, and A know that B know that A is rational), if A IS offering to buy some shares of IBM Corporation and B IS offering to sell them, A has to wonder what information B has that A does not, Of course, pinning down exactly how little volume should be expected in this world is difficult, because in the real world people have liquidity and rebalancing needs, but it seems safe to say that 700 million shares a day on the NYSE is much more trading than standard market models would expect. Similarly, the standard approach would not expect mutual fund managers to turn over their portfolios once a year.
In a rational world, prices change only when news arrives. Since Shiller’s early work was published in 1981, economists have realised that aggregate stock prices appear to move much more than can be justified by changes in intrinsic value (as measured by, say, the present value of future dividends). Although Shiller’s work generated long and complex controversy, his conclusion is generally thought to be correct: Stock and bond prices are more volatile than advocates of rational efficient market theory would predict.
Modigliani and Miller (1958) showed that in an efficient market with no taxes, dividend policy is irrelevant. Under the U.S. tax system, however, dividends are taxed at a higher rate than capital gains and companies can make their taxpaying shareholders better off by repurchasing shares rather than paying dividends. This logic leaves us with two major puzzles, one about company “behaviour” and the other about asset prices. Why do most large companies pay cash dividends? And why do stock prices rise when dividends are initiated or increased? Neither question has any satisfactory rational answer.
2.8.4 The equity premium Puzzle
Historically, the equity premium in the United States and elsewhere has been huge. For example, a dollar invested in U.S. T-bills on January 1, 1926, would now be worth about $14; a dollar invested in large-cap U.S. stocks on the same date would now be worth more than $2,000. Although one would expect returns on equities to be higher, because they are riskier than T-bills, the return differential of 7 percent a year is much too great to be explained by risk alone (Mehra and Prescott 1985). However, it is significant that recent longer term studies have recalculated the figure to nearer to 3 per cent (Dimson Marsh and Staunton (2001)
Benartzi and Richard (1995) argued that the equity premium can be explained by a combination of “behaviours” called “myopic loss aversion.” Loss aversion refers to the observed tendency for decision makers to weigh losses more heavily than gains; losses hurt roughly twice as much as gains feel good.
They added the adjective “myopic” because even investors with long-term horizons appear to care about short-term gains and losses. They found that if investors evaluate their portfolios once a year, loss aversion can explain much of the equity premium.
Barberis, Huang, and Santos (1999) extended this idea in an ambitious new approach. They tried to explain the equity premium within a full equilibrium model that incorporates consumption as well as returns. They could do so only by adding another “behavioural” factor: the “house money effect.” The house money effect captures the intuition that when gamblers are ahead (playing with what they refer to as the “house’s money”), they become less loss averse and more willing to take risks. Similarly, investors who have recently earned high returns will be less risk averse.
In an efficient market, future returns cannot be predicted on the basis of existing information. Thirty years ago, financial economists thought this most basic assumption of the efficient market hypothesis was true (Fama 1970). Now, everyone agrees that stock prices are at least partly predictable (see, for example, Fama 1991) on the Basis of past returns, such measures of value as price-to-earnings or price-to-book ratios, company announcements of earnings, dividend changes, and share repurchases and seasoned equity offerings.
Although considerable controversy remains about whether the observed predictability is best explained by mispricing or risk, no one has been able to specify an observable, as opposed to theoretical or metaphysical, risk measure that can explain the existing data pattern (see, for example, Lakonishok, Shleifer, and Vishny 1994). Further more, the charge that these studies are the inevitable result of data mining is belied by the fact that the authors have covered every important corporate announcement that a company can make. Academics have not selectively studied a few obscure situations and published only those results. Rather, it seems closer to the truth to say that virtually every possible trigger produces apparent excess returns.
2.9 Lessons of Market Efficiency
As a financial manager, one should be aware that the market can’t be easily outguessed nor predicted given that security prices are fair. (Brealey and Myers 2003) the way financial managers act in some cases is a consequence of predictability, and forecasting price changes in the future. This in some cases may be done only by relying on previous price information, as a result they may tend to hold onto stock until prices start increasing again, this in turn may not always be the same.
The following illustrates the basic principles by which an efficient market operates together with further examples of the different ways financial managers may act in order to achieve further gains.
2.9.1 Random Walk
As briefly described above it is agreed and known that price fluctuations do not generally follow a certain set pattern and thus is said that “stock prices follow random walk” or “the market has no memory”. Nevertheless it can be observed that financial managers frequently assume the existence of a pattern in price are low similarly they tend to opt for equity rather than debt financing after an abnormal price rise i.e. they are always keen to catch the market on a high.
As such, acting in such a manner seems to be illogical, as this depends on a pattern in market prices which does not actually exist.
In some cases the financial manager’s actions may be justified as the managers may have inside information regarding the firm’s stock is overprice or under priced, which is not known to others in the market. News, which may affect share prices for example, I known by a financial manager, he/she may decide to wait until the” good news” appears, then selling when share prices reach a high.
2.9.2 Exploiting Appearances
Dividend and stock splits; stock price run up before a splits
Ideally in an efficient market investors should only be interested in a firm’s cash flow, and that which will be their return as a result. So for example they would only follow stock dividends and stock splits as factors that affect cash flow.
This is not always the case as firms employ different methods to give an illusion of increasing review and/ or earning. This can be achieved using accounting methods called” creative accounting “; an example of using creative accounting to stabilize and increase earning is by using different methods to calculate the cost of goods taken out of the inventory. There are two ways to calculate this; the first is called the first -in, first-out method (FIFO), using this method the cost of goods first placed in the inventory is deducted.
The other method is called the last -in, last -out method (LIFO), using this method the price of the latest good is deducted.
Suffice to say that using LIFO, earning seem to be less than those calculated using FIFO; therefore a company is only allowed to use one method to calculate its earnings as well as its tax.
Nevertheless a switch from one method to the other is possible and would indicate a significant change in earning. As an example if a company changes from LIFO to FIFO this could indicate a share rise price even though earnings may appear to be less when calculated under the new method.
Financial managers should always consider whether it is cheaper for the company or the actual investors to bring about change.
The effective way to bring about change in an efficient market would be achieved if investors do not pay for change that they could bring about themselves cheaper than the company would but the same desired affects.
As a result mergers for example will not occur if the desired effect was to bring more diversifying and stability and the stakeholders were able to diversify when they hold the shares for both companies.
Again when issuing a debt a financial manager may find that it is cheaper for the stakeholders to take out loans their own personal accounts thus maintaining financial leverage and avoiding risky stock. This however may not always be feasible and companies may still issue debt, being a well calculated more or a mistake on their behalf by not asking themselves whether the investors can bring about the desired change.
2.9.4 Over and under- Pricing
in efficient market, there is no way for most investors to achieve consistently superior rate of return, Financial managers are sometimes seen to take huge risk as they act on a “hunch” or an expected outcome in share price, currency rates or interest rates. The probability of the market price being undervalued is nevertheless almost always 50:50; more often than not it will be the correct value.
Such risks which depend on a change in interest rates, currency rate or share prices
May still be fruitful wins but still remains a risk and should not be taken especially when a company may incur a large loss as a result.
It can therefore be said that in a perfect market a company cannot expect constant high returns.
2.9.5 Seeds of Success and Failure
In an efficient market information regarding the financial market and the situation of different companies is directly linked to the price. A financial manager can work out future events by reading the entrails and security prices.
Returns of companies’ bonds can indicate its bankruptcy for example if these where offering a higher yield than average. Financial statements as a result can be used to workout and assess a company’s future in the financial market.
Assessing the future can enable investors to decide on the rates of interest they will prefer to wait before they make long-term loans also the long- term rate of interest will have to be higher than the one-year rate
2.9.6 Elasticity of Demand
Demand for stocks should be highly elastic; this will insure the sale of large blocks of stock close to the market price. However this is not always the case as investors may suspect a ploy by which the selling company may be trying to sell a large block of stock due to the fact that it has some information which indicate that the commodity’s price is about to drop in the near future, such a message may by perceived due to the slightly lower offering price by the selling company. As a result offers may be revised and the stock value will fall, resulting in a downward shift in the elastic demand curve. Elastic demand therefore only ensure the sale of a large stock block but dose not ensure a price return close to the market price unless the offering company manages to assure the investors and persuade them that it has no hidden information.
An example of this can be seen in the sale of BP shares in 1977 where share prices dropped and the buyers had to take a risk that the price of BP would not fall.
Finally, Markets have no memory means:
* The efficient market theory assumes that past price contain no information about future price.
* Financial managers often act as if they did not accept such a hypothesis.
- Managers are reluctant to issue stock after a decline, waiting for a rebound.
- Managers favor the issuance of equity over debt after an increase in equity values.
- Managers are reluctant to sell equity if favourable announcements are to be made in the future.
* Inside information has nothing to do with past prices, only the future of the firm.
There are no financial illusions mean:
* Investors are concerned with cash flows and are unconcerned. By there allocation across financiers.
* Research indicates that creative accounting adds no long term value.
-Only information related to future cash flows are “value relevant” information to the market.
There are no free lunches on Wall Street mean:
* Market prices can be trusted in what is an efficient market.
- There is no better deal tomorrow except luck or inside information.
* Term structure differences in interest rates offer no deal for today or tomorrow.
- The market’s expectations of future interest rates determine the rate differences over time.
- choosing short of long-term rates for financing or investment will likely yield or cost the same over the long term.
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