Critical Literature Review of Stock market efficiency and Behavioural finance

P58836: Finance Research Project

Assignment 2: Critical Literature Review of Stock market efficiency and Behavioural finance

Student name: Chong Zhang Student number: 13007758 Submission date: 23 May 2014

Stock market efficiency and Behavioural finance

1. Introduction

Dated back to 1900, Bachelier found out the based concept of market efficiency, which indicates that „all levels of events are reflected in market price while there is no any obvious relation in its changes ‟. The term „efficiency‟ has been a cornerstone to finance, which is used to describe how is the relevant information fully and correctly reflected in the price of financial assets (Elroy and Massoud, 1998). Nowadays, market efficiency still remains a popular subject in the financial academic world. Efficient market hypothesis (EMH) addressed by Fama (1970) states that the prices in such this market will reflect all the relevant information, which was divided into three forms based on the different levels of strong, namely weak form efficiency, semi-strong form efficiency and strong form. According to the EMH, the market will adjust so quickly since the new information came out. It means that no one would be allowed to get above-average returns without bearing above-average risks (Malkiel, 2003). The argument is like the old story about $100, the professor of economics taught his student that does not bother since it is not the real. Therefore, in this kind of market, most investors will be indifferent and rational. And also, Malkies (2003) indicates that since new information arises, the information will spread quickly then was fully respected in the stock price without any delay. Therefore, in this investment process, all the investors always keep rational attitude even if some of them are irrational that will eventually be offset by others. This is because the irrational investors will overvalue or undervalue a stock that they were bound to make loss and diminished in the stock market (Spyrou, 2003). Therefore, this is a relatively stable and efficient market without any arbitrage opportunities.

However, as more and more stock market anomalies came out, the EMH was queried and criticized by the economists and start to lose its prestige among the

scholars and stock market due to emergence of B.F (Anastasios –et al., 2012). Behavioral Finance is the study that the „psychology‟ factor effects human‟s behavior on market investment decisions, no matter for the individual or group level (Sewell, 2010). In this literature review, it will evaluate the tenets about the EMH and BF that then analysis the extent to whether the stock market „anomalies‟ that are either “small departures from the fundamental truth of market efficiency” or “call into question the basic underpinnings of the entire efficient markets theory” (Shiller, 2003). Before the evaluation between EMH and BF, the meaning of stock market efficiency and its importance will be analyzed firstly. And the tents of EMH and BF will be separately discussed in the following two parts. Eventually, the review will critically focus on the reasons of stock market anomalies analyzing based on the two parts above.

2. The meaning of Stock Market Efficiency

Usually, the meanings of term „efficiency‟ are twofold: one is to show how efficiently the resource is developed in the capital market by reflecting in the prices (Dow and Gorton, 1997) while another one is to describe how the information is impounded into the price of assets (Elroy and Massoud, 1998). Currently, stock market efficiency has been a long term popularly controversial financial theory due to the publication of Fama‟s theory in the past few decades (Harrison and Moore, 2012). Like other ideas of modern finance, EMH was first addressed by Samuelon (1965) whom indicates that the price movement cannot be predicted if it is properly anticipated. That is to say, this efficient market has fully incorporated all the information and expectations by stock prices (Mishkin, 1997). It seems impossible that each investor know all the information and analysis what it indicates in the stock market. Nevertheless, Sttiglitz (1993) states that in such an efficient market, it does not require all participates should know about the information. It is not important for all the investors that know and analysis the information and has a rational investment decision. It requires a few

group of people have that information once a few investors gain the information about the price movement the whole market will be well informed (Mishkin, 1997). Lately, the moving rapidly stock prices in the market will reflect all the information that no one can beat the average gains of this market. Therefore, if all relevant information can be reflected in the determinations of a stock price that is to say the stock market is efficient (Malkiel, 2011). In such level of market, the stock price will be unaffected by the issued information to the participants. And it is impossible that the information set cannot be made economic profits by the trade of this information (McKinley & College, 1999). Based on the consideration of differences within information set, the market efficiency was distinguished into three forms tests (Roberts, 1967), which became the basic taxonomy in Fama‟s theory (1970). 2.1 Importance for stock markets to be efficient

Market efficiency matters for several reasons. The „fairness‟ plays a vital role in market efficiency, which matters to investors because correct and fair pricing would encourage all stock market participates‟ confidence to invest in a stock and get the profit from sales as well (Harrison and Moore, 2012). It does not mean that the markets would over or underreact to the information, but it is unbiased and makes investors feel fair to their participation of the stock buying. Therefore, there are no arbitrage opportunities existing with market efficiency (Herschberg, 2012). Moreover, market efficiency is also important for the company managers because prices of financial assets in markets will combine the effect of decisions on improving shareholders‟ wealth. The indicator of price would continually stimulate the managerial decisions that seeking for the strategies on shareholders‟ wealth enhancement (Harrison and Moore, 2012). Furthermore, market efficiency would affect the whole economy since the policy maker have to act based on the level of efficiency. The degree of allocated efficiency in a stock market will be indicated by the signals of a reliable and accurate stock. Fama (1970) illustrates that capital

resource would be widely and accurately allocated in a suitable way when the markets are efficient. This fact is highlighted by the European Bank for Reconstruction and Development (1998, p.101) who indicates that a stock market would deliver an efficient way to resource allocation if the market intend to provide an efficient distribution network of resource when the information of a good and service can be exchanged widely and reliably without relying on the relationship between buyer and seller. In addition, the market efficiency is good for the emerging economies because information efficiency would indicate a vital link between the growths of emerging economies and stock market, which also give a guide to the police makers in those countries (Bekeart and Harvey, 1998). Therefore, it is obvious that why stock market to be efficient is important, no matter for a single market or a national economic development.

2.2 The tenets of the efficient markets hypothesis

Like other famous theories of finance, the concept of efficient market hypothesis (EMH) has been defining for a long period of time and it still remains the core of modern financial theory, which is widely utilized in the investment decision research (Anastasios et al., 2012). Samuelson (1965) addressed that the prices in efficient stock cannot be forecasted due to the market runs as a random walk. Roberts (1967) found that incorporation of information in the stock prices leads to the explanation of what is called as EMH. Lately, Fama (1970) analyzed the pervious theories then illustrates that the security prices in an efficient market can fully reflect all available information. In this efficient market, stock market participates cannot be allowed to make abnormal profits without bearing the same level risks (Malkiel, 2003). Moreover, EHM generally holds that the efficiency of stock market, which are involving the overwhelming news, information or other kinds of communication activities. Based on the Fama (1970), efficient market is a market that there is a huge numbers of rational

and intelligent participates seeking for maximizing returns with predicting future value of stock by the all the freely available information. And also, the market as a whole is very efficient that accurately integrates the newly-rising information to the stock prices and spreads this news quickly without delay (Malkiel, 2003).

In addition, EMH has three assumptions, which are involved into its tenets (Yalçın, 2010). Based on Anastasios –et al. (2012), EMH theory asserts that the investors are rational to their investing decisions making. They just utilize their knowledge to react to a stock price movement. Even though, some of them are irrational that their investing strategies may trend to be uncorrected and random and will be counterbalanced with each other. Therefore, this deviation is provisional that the irrational reactions will be canceled in the market. Moreover, even if those irrational investors‟ activities are not canceled out since their decisions are coroneted. Their activities were diminished by some professional arbitragers because of the contemporary prices were under or overpriced (Shleifer, 2000). Therefore, the market is always rational and efficient by the prices equilibrium and efficiency, even if the investors were irrational (Anastasios –et al., 2012).

According to the different levels of available information set, the tenets analyse of EMH theory was divided into three perspectives (Rabbani –et al., 2013).

2.3 Three forms of tenets and empirical evidence

2.3.1 Weak Form Market Efficiency

Weak efficiency mean that the future stock price cannot be predicted by the past prices movement (technical) analysis because all the past information was fully reflected in current stock price. It requires that the price in market must be adjusted quickly. Otherwise the delay of equilibrium value would be a profitable chance to be

exploited by the investors. Mandelbrot (1966) states that, as the news cannot be predicted, the stock prices in each day are changing independently, which means that stock prices commonly acts as random and unpredictable as well as Lo & Hasanhodzic (2010). It can be obvious that the weak form EMH must hold though not vice versa once the random work holds (Copeland and Weston, 1983). It shows that all the evidences of random walk are being the backbone of the weak form EMH theory. This fact is highlighted by bachelier (1900) who found the stock prices movement follows a random walk while Kendall (1953) addressed that serial correlation between each two changes of stock prices is almost zero as well as Osborne (1959) found that the price change is independent due to the price movement acts like the random Brownian motion. And also, in the later few years, some economists consisted on utilizing other techniques and information to verify the randomness of successive prices changes, such as Granger and Morgenstern (1963) that cannot find any valid patterns about prices change. It is the same to the finding of Solnik (1973) who found the investment strategies cannot be formulated by any small findings based on the serial correlation coefficient analysis. Those empirical work prove again that the efficient market stock just run follow random work and do not leave any opportunities to be exploited to the profitable investment strategies.

Even though, most of studies of financial market widely supported the finding of randomness, the random walk theory remained to be questioned and does not always hold (Malkiel, 1989). Some studies inconsistent with random walk theory, especially the short periods of time for the tendency of price change. Lo and Mackinlay (1988) indicated that there is a positive serial correlation between the stock price for weekly and monthly holding period based on a long time price observation. It seems that the random walk model do not work in this study. Nevertheless, this situation just exists in some small companies with very little trades then it would be induced and factored by other information in the stock market.

Therefore, these findings do not affect the efficiency in this market. In contrast, to the long term horizons, such as more than one year of time that the market would display negative serial correlation between 1926 and 1986, (Poterba and Summers, 1988; Fama and French, 1988). It seems that the contrarian investment strategy can bring an opportunity to get abnormal returns when buying a company stock with a recently poor performance that would be expected to produce more returns recently than buying a relatively performed-well company stock (De Bondt and Thaler, 1985). Nevertheless, in fact, the serial correlations (mean reversion) after 1940 in the researches (Poterba and Summers, 1988; Fama and French, 1988) are quite a bit lower than it in earlier periods. In addition, the mean reversion in Therefore, the time varying required rate of return is an essential indicator that should be involved to those findings. Moreover, the return reversals for the entire market would be consistent with the market efficient functioning (Malkiel, 2003). This is because the stock market condition would be affected by volatility of interest rates and tendency of interest rates to be mean reverting. That is to say, the prices of stock and bond will go down while interest rates were arisen due to the stock return must be completive with bond returns. Therefore, this pattern will generate return reversals by the time of interest rate revert to the mean. However, there is by no means that investors can profit if return reversals exhibited by a single stock. Fluck, Malkiel and Quandt (1997) found that within 1980s to 1990s, the stock with high returns would tend to have a lower return in next few years while stock with low return would have a relatively higher return in the coming few years. Therefore, there is an obvious pattern of return reversals, but it cannot indicate that investors can make abnormal profit by market efficiency.

2.3.2 Semi-Strong Form Efficiency

The current prices in the market with semi-strong form efficiency that incorporate all the publicly available information, which are involving the listing company announcements, financial balance sheets (Ross et al. 2008). Even though, the fundamental analysis was widely accepted by the public investment strategies, it still remains not likely a superior performance since the public information was integrated into the market quickly. It means that the semi-strong form of EMH holds.

Several empirical studies have measured the speed of integration in the prices with the new information. Even though, spilt cannot bring the economic benefit to the market, it is standing for a confidence of a good future aspect of the managements in the company, which would rise the attraction to the stock purchasing. Fama et al. (1969) found out that investors can make substantial returns before the split announcement came out of the companies, but due to quickly and fully adjusted by market that there is no more profitable opportunities. It means that all the publicly positive information would boost its stock price, but it would be integrated to the prices by the market immediacy as well. This conclusion was verified lately by Dodd (1981) who found the stock prices will not change unconventionally since the merger announcement was publicly released. As well as the findings of Patell and Wolfson (1984), based on the analyzing of the time of adjustment to the announcement, they found that the stock market responses the new information so quickly, which just costs within 5 to 15 minutes since the information was published.

However, there are some findings found by the economists challenging this level of EMH. Ball (1978) states that the stock prices do not completely react to the earning announcements and the abnormal adjusted-risk returns still exist after information published. Moreover, Rendleman et al. (1982) address that there is a relationship between abnormal returns and unexpected quarterly returns from shares after

announcement. In addition, Roll (1984) found that some futures prices cannot reflect all the information due to the daily prices fluctuation was limited in the exchange regulations. Nevertheless, these small anomalies cannot affect the overwhelming evidence of semi-strong form EMH supporting, which was widely accepted (Malkiel, 1989).

2.3.3 Strong Form Efficiency

In this level of efficient market, the stock prices fully reflected all the information includes the public, individual, even confidential news that do not allow the market participates to seek for the abnormal returns. Mikiel (1989) states that, some information like dividend policy adjustment, M&As activity announcements and stock splits will do a significant effect to the stock prices. It seems that the insiders could trade on this information before they were noticed publicly (Jaffe, 1974). Even though such activity is forbidden, the fact that information can be partially forecasted basis of the sign of market dynamics or anticipated in the market that causes the competitive advantage in the investment strategy. That is to say, such this strong form efficient market will not be true. Nevertheless, some empirical evidence prove that the market could be closely strong efficient. Those empirical studies mainly focus on the analyzing records of investment managers. Cowles (1933) failed to correct any evidence about the significant performance of the investment in the market on the basis of the financial services and the investors as well as Friend –et al. (1962) who lately found that there are no obvious differences between performance of the average mutual fund and performance of randomly selected unmanaged portfolio with the same investing assets. Even though, Jensen (1969) found that the mutual fund seems could be exploited to make abnormal money due to the risk-adjusted performance measurement, it still causes management fee by relative advantages

from the managers. And also, some small abnormal profit as a motivation of acquiring information will not be eliminated by the EMH (Malkiel, 1989).

3. Behavioral Finance

According to Shefrin (2001), Behavioral Finance is the study that research how psychology influence the behavior of financial decision making then directly affect the financial market, which can be defined as the „open-minded‟ finance (Thaler, 1993). Behavioral finance theory intents to find how human behavior affects the financial strategies based on the research of relationship between human factors and the investing decision making. Sewell (2005) indicates that BF is the research of psychology on the investors and impacts bought by markets. It means that some investors‟ different levels of irrational behaviors would cause the financial effects, such as the cognitive differences, bias and psychological reactions (Barberis, 2007). Therefore, that is to say, investors cannot be the optimal decision makers due to each decision would be heavily influenced by their psychological processes (Alexakis and Xanthakis, 2008).

According to Ritter (2002), there are two main tenets in the behavioral finance theory, namely cognitive psychology and limits to arbitrage. The „cognitive psychology‟ is to describe the type of irrationality based on the experimental evidence of the people‟s beliefs and references on the prospects of investing decisions making (Thaler and Barberis, 2002). Herschberg (2012) indicates that the term „Limits to arbitrage‟ is to find out the reasons why the existence of arbitrage opportunities will not disappear quickly.

3.1 Cognitive Biases

Prospect theory and Loss aversion

Kahneman and Tversky (1979) found out prospect theory, which is a mathematically-formulated alternative theory and points out that people prefer to assign high weight to certain event rather than the uncertain event with high return. That is the study of behavioral finance on finding the reasons why investors prefer to lose-averse rather than risk-averse, which seems the pain of losses is larger than gains. Barberis –et al. (2001) indicates that lose-averse means that investors regards the wealth loss as more unacceptable than equivalent or more wealth gain. Therefore, market participants always seek for the ways to reduce the possibility of loss in an uncertain situation even the possibility is small. As well as Tversky (2001) states that, people hate losing rather than uncertainty. That is clearly to say, people intents to be afraid of the loss, and they prefer to choose an uncertain way with higher risk.

According to the prospect theory, people tend to separate several mental accounts to guide their financial decisions making based on the different financial goals, which called the mental accounting. As usual, one of two accounts is for covering low risks and the one is to seek for the upward potential with high risks that is the reason why people seek and hedge risks (Friedman and Savage, 1948). A new financial asset is purchased implies that a new mental account is created (Thaler, 1980). Mental accounting is important since it is involving the loss-aversion and multi-dimensional risk attitude, which called „framing effect‟. It implies that people will choose the risky outcome when they facing loss. On the other hand, people tend to avoid the risk when they facing winner.

Overconfidence and Self attribution

Gervais -et al. (2002) indicates that overconfidence is a belief that people tents to believe their judgments based on their knowledge rather than the objective situation. The same as the investors in the market, they overestimate their sensation about the market events then make loss due to they take pointless risks by their overconfidence (Nevins, 2004). In another similar investors‟ psychological process, they regards the facing success as their abilities while they regards the failures as bad luck, which called „self-attribution‟ (Subrahmanyam, 2007). Both of psychological process would cause the cognitive bias to the investors that cannot correctly react to the stock prices movements.

Overreaction and Underreaction

DeBondt and Thaler (1985) found that, there is a significant overturn happening in the stock market. A underperform stock price will rise to the mean while a better stock intents to fall in a long term of period. That is the „Reversal Effect‟. One of the main factors behind reversal effect is the market overreaction, which means that investors would overly react to random occurrences. In addition, due to the conservatism bias, people may trend to underreact when something change happened (Ritter, 2003). It seems that people always tent to be laggard when new information came out or changes happened. And also, once the time is enough for the reaction, they may adjust to it and cause the overreaction happened.

Herd Behavior

Due to the humans get used to live in a crowd, the cohesion of the social environment will cause the assimilation to the humans with the same way of think and behaviors. It means that the people tents to act similarity at similar times and react similarly to the information then they will correct their so called „wrong‟ ideas due to the judgment of a large of others are seems to be right. That is to say, when

individuals found their judgments are different while others are unanimous that others‟ always be right (Shiller, 2000).

3.2 Limit to arbitrage

Sharpe and Alexande (1990) states that Arbitrage is a strategy, which selling and buying the same objectives in different market at the same time to gain returns from mispricing then lead the prices back to the general value then the market turn back to be efficient. However, even though arbitrage opportunity is the second foundation of the EMH assumptions, which has risks and limits to the real operations (Shleifer, 2000). Sheifer and Vishny (1997) pointed out that the arbitrage was limited due to the cost is much. It means that the arbitrageurs would be required to cost much capital due to the price diverges further and further from their efficient values. And also, Daniel et al. (2001) indicates that, arbitrageurs cannot remove the systematic mispricing since they have to bear the pressure of risk-aversion. And also, based on the research on the reason why arbitrage opportunities cannot be utilized in the market, Thaler and Baberis (2002) found out four risks and costs to explain this question, namely Fundamental risk, Noise Trader Risk and the Implementation Costs.

3.3 Empirical evidences about Behavioral Finance

Prast (2004) points out that the experienced financial markets were hard to explained by the any traditional economic, which only can be explained by the insight of psychology. That is to say, the behavior is a main factor that affects the market as a whole, which were prove by the financial puzzles.

3.3.1 Loss aversion and mental accounting

Winner/loser puzzle

Based on the studies of Barbor and Odean (2000), we can obviously found that, in each year, investors tend to sell the winning stocks (be profitable) instead of selling the losing stock (be loss), which shows there is 70% of willingness of investors selling winner stock within the large numbers of samples. This phenomenon seems to be counterintuitive, because the losing stock should be more attractive to be sold. In fact, most investors prefer to sell the winner as soon as possible while the losing one would be held for a long time (Shefrin and Statman, 1985). According to the results of Shefrin and Statman (1985) delivered on the basis of prospect theory research, the reason why selling winner and hold losers is that investors are predisposed to be lose-aversion and mental accounting to close one of mental accounts by selling the one which will be won or loose. The findings are also proved lately by Odean (1998a).

Dividend puzzle

Miller and Scholes (1982) found out that, investors have a bias of dividends. In general, cash dividends will cause a tax disadvantage and investors can gain more returns if company decide to cancel the dividends payment in this year. In fact, investors prefer to the get cash dividends rather the higher returns. Based on the prospect theory Kahneman, D., and A. Tversky (1979), the gains from dividends and capitals are different. This is because investors have separated both of them as two independent mental accounts, which are the dividend account with relatively low-risky and capital account with higher-risky. When prices fall, it can be recognized as the loss in capital account. When company cancels the dividends, it would be regarded as the loss in the dividends account. Moreover, this puzzle can be explained by loss-aversion (Barberis –et al., 2001). When stock prices fall, dividends can be regarded as a „silver lining‟. On the other hand, when prices rise, the dividend gains can be seen as the access gains.

3.3.2 Conservatism and representativeness heuristic

Asset price Over- and underreaction

Based on the empirical studies, the exchange rate and asset prices seems to act as under- and overreaction once the news risen (Prast, 2004). Based on the research of the returns on stock following earnings announcements, Bernard (1992) found out that the price will remain a tendency of higher rising since the news announced. De Bondt and Thaler (1985) indicates that overreaction is caused by the results of inefficient pricing in the markets. Jegadeesh and Titman (1993) found out that, in a past period, the return on a stock with superior performance remains exceed an underperformance one. And De Bondt and Thaler (1985) found that it holds in a short period while it is opposite in the long terms. Barberis et al. (1998) attempt to use conservatism to analysis the situation of under- and overreaction while Dainiel et al. (1998) utilize the overconfidence and biased self-attribution to define it. Barberis et al. define the underreaction as a situation when return following good news remains higher than it would have a bad one. The rising information will be processed immediately in the efficient market. Therefore, the prices would not be currently affected by this initial information in the later period of time. However, after this beneficial news released, the prices still keeps rising that is the underreaction. In fact, once the reaction was sufficient, the prices will start to fall gradually and return to the fundamental value, this is the overreaction. Daniel et al. found out that since the investors feel overconfident to their findings (hot tip) will bring advantage information to them while others do not know. Therefore, if the information is favorable that all the investors are willing to buy more by convincing to this news were not reflected in the prices. This action will lead the market to overreaction. Besides, if the private information will be corroborated publicly that would increase their confidence. If not,

the investor could blame at others. Therefore, such the investors‟ overconfidence will not be reduced, but increased.

3.3.3 Overconfidence

Excessive trading and the gender puzzle

Based on the collecting records of trading and returns in 66,000 accounts between investors and stockbrokers, Barber and Odean (2000) found out that half of sample shows that investors trend to get higher returns if they trade relatively less. And also, they found the net return of investors who trade less is more than those who trade more 7% percentage point. It means that the investors can gain more return when they trade relatively less. In other words, some investors attempt to beat the market as a whole by excessively trading due to their overconfidence may contribute to success (Taylor and Brown, 1988). In addition, Barber and Odean (2001) found out the differences on the investing behaviors between women and men, which shows that men generally trade more than women by 1.5 times in frequency but make a return less than women by 1 percentage point. This gap will be larger when researching on the aims of singles, which shows significantly that single men trade much more than single women and realize a 1.5 percentage point lower return in the end. As psychological research indicated that, usually, men trend to be more confident than women. That is to say, the reason why men trade so much is their overconfidence effect. From the empirical evidence above, overconfidence is one of factors behind behavioral finance that affects investors‟ decisions making.

3.3.4 Limits to arbitrage

Twin Shares

Based on the research of Froot and Dabora (1999) and the later explanation of Thaler and Barberis (2002), it is obvious that the theory of limits to arbitrage holds. Royal Dutch (RD) and Shell Transport (ST) are two independent companies and they decide to merger based on the 60:40 interests. If the prices equal to the fundamental value that market value of RD is 1.5 times value of ST. In fact, trading as 35% underpriced or 15% overpriced happened in RD, which indicates that the theory of limits to arbitrage holds by this existing mispricing. And also, in such this case, due to the shares can be used to hedge and there is no implantations cost when buying is easily, the only risk can be found is the noise trade risk. This is because the price would be kept undervaluing in the following periods, which means there is no opportunities for accessing profits.

Index Effects

Shleifer (1986) indicates that, once a stock is included in an index, prices normally rise by 3.5 percent. It is a dramatic phenomenon that Yahoo has jumped by 24 percent point when it was adding to the index. It is an obvious empirical evidence of limits to arbitrage. This is because the when arbitrageur utilize the mispricing they have to short the added stock and buy a good substitute. However, this will bring a relatively high fundamental risk since such this kind of stock is not easy to find as the substitutes and the noise trader risk included in this stock would boost the initial stock prices further in a short term. The combination of fundamental risks and noise trader risks is the main reason why theory of limits to arbitrage holds.

4. EMH theory against Behavioural Finance 4.1 Market Rationality 4.1.1 Limits to Arbitrage

Based on the three forms of EMH (Fama, 1970) and its assumptions (Anastasios –et al., 2012), it is obvious that market participates remains a rational attitude with risk-aversion. The prices in the market equal to fundamental value and fully reflect all the information, which act follow random walk. Once the irrational investors arises, they will be eliminated by the arbitrageurs due to the prices were mispricing (Shleifer, 2000). However, Black (1986) argues that the irrational activities is like a „noise‟ affect the prices movements, which creates a risk to heavily impacts the willingness of arbitragers to against the irrational activity due to they have to bear with the pressure of profit requiring of the customers (De Long et al., 1990). Therefore, the real arbitrage is limited by considerable risks and costs (Shleifer and Vishny, 1997). This is because the arbitrageurs should spend more and more capital to correct the mispricing when prices more and more diverge from their fundamental value. And also, due to the risk-aversion, arbitrageurs may give up to remove the mispricing (Daniel et al. 2001). It means that rational investors are usually powerless while irrational investors led the mispricing happened. In contrast, Hirshleifer et al. (2006) argue that the irrational agents can get a considerable profit when stock prices affect corporate investment. Since the agents act as likely to the irrational traders who push the prices by the information of noisy, they can get more profits than rational ones in the market. That is to say, the irrational trades cannot fully diminished by the arbitrageurs, therefore the irrational investors are existing. As usual, based on the different reactions to the new information in the stock market, the cognitive biases can be separated in several types, namely Prospect theory and Loss aversion, under- and overreaction, overconfidence and Self attribution, and Herd Behaviour. In addition, there is no direct evidence proving that herb behaviour is a main cognitive

bias causes the anomalies in such the efficient market. However, the herd behaviour would bring a „bandwagon effect‟ that contribute to make other cognitive biases much significantly happened in the market.

4.1.2 Prospect theory and loss-aversion

Some economists has extended the framework of EMH since the EMH was addressed by Samuelson (1965) and Fama (1970), which states that all investors are risk-averse because they have an rational expectations for their return in such efficient market. However, Mehra and Prescott (1985) addressed that the premium differences between risky and risk-free security was about 6% and the coefficient of relative of risk-aversion exceed 30 rather than 1 to the equity premium. Benatzi and Thaler (1995) argues that the behaviour of prospect theory is suitable to solve this puzzle. This is because psychological influence in the investing decision of individual investors is extremely strong and the major market participates, institutional investors‟ investing psychological process was affected by regular portfolio evaluation from their clients. That is to say, most participates in the market is lose-aversion rather than the risk-aversion, which can also explains that the reason why pension fund is unfailing since its profit is steadily increasing with relatively less trading in stock. Even though the historical equity risk premium is significantly inconsistent with the real situation measured by statistic, it does not mean that the market is not full rational (Malkiel, 2003). In fact, U.S. stock market is special since it is a market which remained to operation within a period of world war. The statistic risk premium results were collected from „survivorship bias‟, which should be distinguished carefully between the expected risk premium and this historical result with bias. And also, Fama and French (2002) indicates that some unexpected capital gains would be created by the high average realized return, which means it is not irrational once it came true (review by malkiel, 2000).

4.1.3 Under- and overreaction

As mentioned above, De Bondt and Thaler (1985) suggests that investors tend to behave as overreaction when they experienced unexpected information or events, which caused long term „reversal effect‟. It means that due to the seeking of forming expectation, most investors put too much attention in the past performance of the prices without realizing that the contemporary performance will come up a mean-reversion. And also, De Bondt and Thaler (1985) states that overreaction can be a predicted pattern to the behavioural decision, which rejects the EMH that the stock cannot be forecasted by analysing the past information (Kahneman and Tversky, 1982). Lakonishok –et al. (1994) argues the reason why market has a poorer earnings growth when ratios of earnings to price, book to market and cash flow to price are higher and vice versa. This is because the market overreacts to the past information, which would be unexpected when the earnings growth mean-reversion came out. And also, due to the conservatism bias, investors may trend to underreact when something change happened (Ritter, 2003). Bernard and Thomas (1990) argue that when the stock prices respond to earnings announcement after a year since it was published that is the under-reaction. It means that the stock prices will generally remain its tendency of rising or falling until three or six months, which called the „momentum effect‟ (Jegadeesh and Titman, 1993). Therefore, not only the under-reaction and overreaction would prove the investors are irrational, but they also against the random walk theory that the pattern can be predicted and exploited to make abnormal returns. However, the market is still rational and efficient due to some factors against to this phenomenon. Odean (1999) argues that the investors of momentum cannot make excess returns since such this trader would do worse than normal buy-and-hold trades when the momentum opportunities exploitation would cost a large transaction. That is to say the small excess returns from economic

significance when the stock market was not a mathematically perfect random walk will be diminished by such high transaction cost. And also, Fama (1998) states that the frequency of under-reaction to information apparent is the same to overreaction, which means that the abnormal returns from continuous tendency of „momentum effect‟ will be eliminated by the reversal in post events with the same frequency of apparent. In addition, Malkiel (2002) found out that due to the serial correlation of stock price movement is uncertain, since it appeared to be positive in 1990s and it was negative during 2000. It shows that the price pattern is likely impossible to be exploited when investors seeking for the abnormal returns. Therefore, even though the anomalies exist, they are still consistent with efficiency of the market as a whole.

4.1.4 Overconfidence and Self-attribution

As mentioned above in Chapter 3, Odean (1998) argues that some investors overvalue their knowledge and awareness about the market and financial assets prices that lead them to be more unrealistically optimistic about the unexpected information and get an inconsistent return with high risk. And also, their confidences will not be weakened by a loss result because they will blame at other factors rather than personal reason that is called self-attribution. It seems that some of market participates are less than fully rational. Odean (1998) also argues that overconfidence is not always consistent with market efficiency since traders will overestimate themselves and follow the trend of a market of noise traders even the market will be efficient eventually. Barber and Odean (2001) states that the women trends to get a better return than men, since men trend to be more confident that trade excessively. Then same to the agents, they also trend to buy overvalued assets since they think to sell with extreme beliefs (Scheinkman and Xiong, 2003). Moreover, some irrational agents seem to get large expected returns since they would end up suffering for most risks (Delong et al, 1991). However, Daniel, Hirshleifer, and

Subramanyam (DHS 1997) states that overconfidence would exaggerate the expected performance of private signals about the value of a stock while self-attribution will lead the public signals of stock price to be underweighted, especially when the public information is inconsistent with the private one. Therefore, it will result in a short-term momentum effect of stock return with a long term reversion happening eventually when investors trend to overreact to the private information and under-react to the public information. There is no doubt that the public information will overcome to the public information in the end that the market as a whole will be not affected.

Moreover, some studies found that the return of „value‟ stock is higher than the one of the „growth‟ stocks, which usually measured by two methods, namely price-earnings ratios (P/E ratios) and price-to-book-value ratios (P/B ratios). The rate of returns from a stock with relatively lower P/E ratio is larger than one with higher P/E ratio. Nicholson (1960) found and Basu (1983) confirmed lately that it is caused by the view of behaviourists. Some investors seem to be overconfident that overestimate their ability to predict a high earnings growth and hence overpay for the „growth‟ stocks. Due to the overreaction to the stock with overvalued price, the price will have a mean-reversion eventually. This is similar with the result of Graham and Dodd (1934) who also shown that price/cash flow ratio, where cash flow is the sum of earnings and depreciation and amortization.

The P/B ratio is defined as a vital predictor of the expected returns, where a firm‟s net asset divided by number of shares. Low P/B can be recognized as the „value‟ in equity and is consistent with investors who trend to purchase the „growth‟ stock since investors‟ overconfidence but get an unexpected result in the end. Fama and French (1993) indicates that the size and price-to-book-value can explain the returns movement since both of them were taken account that would show the extra affect to

the P/E ratio. And also, they argue that the P/BV effect is essential in each world stock market.

It seems that those findings queried the market efficiency if the CAPM holds (Lakonishok et al., 1994). However, they are unable to prove inefficiency since they may imply the failure of CAPM to measure the risks. Fama and French (1993) indicate that some extra risks shown by P/B ratio is priced into the market rather than captured by CAPM. Some companies trend to sell a stock with low price when they are suffering with the financial distress (Milkiel, 2003). Fama and French (1993) also argue that the three-factor asset-pricing model can be used to measure those anomalies when the P/B value and size were taken account that the expected returns are consistent with actual market returns. Therefore, markets still remain the efficiency and hence the irrational investment cannot bring any negative impacts to the market.

4.2 Random walk

4.2.1 Predictable pattern from financial statistic

In the original empirical evidence, the stock prices move as randomness, which shows that there is no memory in such this market. That is to generally say, the price cannot be predicted based on the past movement (Cootner, 1946). However, Lo and MacKinlay (1999) found out that short-run serial correlations are not zero and there are so many significantly successive moves existing with the same direction, which against the hypothesis that stock prices behave as true random walks. A short term momentum happened in the market prices and hence there is a pattern that can be recognized by the „technical analysts‟ based on the prices signals. However, Malkiel (2003) argues that the empirical evidence just only show statistical significance when market does not follow as a mathematically perfect random walk. To the economic

significance, the statistical dependencies giving rise to momentum are extremely small, which seems not allow investors to make abnormal returns. Moreover, some predictable patterns always to disappear since they were found and found. Schwert (2001) argues that this is because the patterns will trend to be unprofitable and then disappear since they were excessively exploited by practitioners. And also, Malkiel (2003) found out that just like „January effect‟, it seems not disappear since it was published. It is belong to a day-of-the-week effect, which has a high return in first two weeks in a year. However, it might self-destruct in the future since it received enough publicity (Malkiel, 2003). As well as the predicted pattern of short-term interest rates and the future stock return (Fama and Schwert, 1977) and the pattern of stock returns forecast by interest rates spreads (Keim and Stambaugh, 1986), even though such predictable patterns can be found by the financial statistics, they always cannot be used for the investing decision due to those patterns are not robust in different periods of time and they can get profit by taking the extra risks. That is to say, the market remains act as from a random walk.

4.2.2 Predictable pattern from firm characteristic

In addition, not only the predictable patterns can be found by the financial statistic method above, but also can be found by the firm characteristic. Keim (1983) found out that the annual rates of return in a small-size company stock are more than 1% point than return of a large company stock. While Fama and French (1993) point out that the portfolios from smaller stocks can get a higher monthly return on average than the one of larger stocks. That is the size effect and hence the returns of a relatively small firm can be regarded as a predictable pattern to the investors that gets an abnormal return. Based on the CAPM, the measure of risk to the financial assets is the „beta‟ in the CAPM formula, which represent the coefficient of variation within the return of a stock and return of entire market. The size effect can be seen

as an anomaly that affects the market efficiency since the CAPM cannot explain the reason why portfolios of smaller stocks can get risk-adjusted returns. However, Fama and French (1993) argue that the size can be a better alternative of beta for risk measure and hence these findings cannot prove that the market is inefficient and predictable.

4.3 The Performance of Professional Investors

There is a direct way testing the whether market is efficient or not is that evaluating the performance of professional fund managers in the market since they are the main market participates (Malkiel, 2003). Managers can beat the market once the market prices was determined by irrational traders and deviated from rational prediction of the value of a firm, and some many predictable patterns can be found in the returns predicting. The performance of the managers can represent the result of whether the market is efficient or not. In fact, there are many evidence can be found to suggest that no professional investors have a superior performance in the market by stock hold and buy strategies. Jensen (1968) states that mutual fund managers fail to add value and underperform the market by the equal amount of cost. Moreover, some funds with poor performance trend to be merged into other fund, which means that the fund with record of underperformance will be purchased again. Besides, managed funds are usually regularly outperformed by the index, even though it can make excess returns, it can do the same thing in the next time. The persistence in performance is not permanent. All of these evidence shows that there is no professional managers can continually get abnormal returns by the irrationalities exploitation or existing predictable patterns.

5. Limitations

In this literature review, there are a few limitations. The data used in the review is secondary data and the theories utilized were old, which affect the accuracy of the arguments. Moreover, there is no fundamental framework on the behavioral finance research, which means all the theories are abstract without any tangible proofs.

6. Conclusion

Even though there are so many evidence shows that investors are not fully rational since they were affected by different psychological biases, the market still remains to be efficient because those anomalies were self-destructed or cancelled by other anomalies. That is to say, the markets as a whole is still efficient, because of the anomalies just appear in short term period and are corrected in the long term period. Therefore, the stock market „anomalies‟ is only a „small departures from the fundamental truth of market efficiency’.

Reference:

Alexakis, Ch. and Xanthakis, M., (2008), Behavioral Finance, Stamoulis Publications, Greece

Anastasios K., Androniki K, George B. and Maria E.V.,(2012), „ Efficient Market Hypothesis To Behavioural Finance: Can Behavioural Finance Be The New Dominant Model For Investing?‟, issued: University of Pitesti in its journal Scientific Bulletin - Economic Sciences,P16-26

Burton G. Malkiel (2011), „Is the Stock Market Efficient?‟, Published by: American

Association for the Advancement of Science, Science, New Series, Vol. 243, No. 4896 (Mar. 10, 1989), pp. 1313-1318

Bekaert G and Harvey C R (1998) 'Capital Markets: An Engine for Economic Growth', The Brown Journal of World Affairs, 5(1), 33-53.

Benartzi, S. and R. Thaler (1995), Myopic Loss Aversion and the Equity Premium Puzzle, Quarterly Journal of Economics, 110, pp. 73-92

Barberis, N. and Huang Μ., (2007), The Loss Aversion / Narrow Framing Approach to the Equity Premium Puzzle, in Mehra R. ed., Handbook of Investments: The Equity Risk Premium. Elsevier. Amsterdam.

Barberis, N., A. Shleifer and R. Vishny (1998), A model of investor sentiment, Journal of Financial Economics 49, pp. 307-343

Barberis, N., M. Huang and T. Santos (2001), „Prospect theory and asset prices‖‟, Quarterly Journal of Economics 116, pp.1−53

Bachelier, Louis (1900) trans. James Boness. “Theory of Speculation”, in Cootner (1964) pp. 17-78

Ball, R. (1978), Anomalies in Relationships Between Securities' Yields and Yield-Surrogates, Journal of Financial Economics 6, 103-26.27.

Black, F. (1986), “Noise”. Journal of Finance. Vol.41, No.3, pp. 529-543

Bernard, V. L. and J. K. Thomas, (1990), Evidence that stock prices do not fully reflect the implications of currebt earnings for future earnings, journal of Accounting and Economics 13, 305-40.

Barber, B. and T. Odean (2000), Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors, Journal of Finance 55, pp. 773-806 Barber, B. and T. Odean (2001), Boys Will Be Boys: Gender, Overconfidence and Common Stock Investment, Quarterly Journal of Economics 116, pp. 261-292

Basu, S. (1983), “The Relationship Between Earnings‟ Yield, Market Value and the Returns for NYSE Common Stocks: Further Evidence.” Journal of Financial Economics. June, 12:1, pp. 129–56.

Copeland, T.E. and J.F. Weston (1983), Financial Theory and Corporate Policy, 2nd edn, Addison Wesley Publishing Inc., California

Cowles A., (1933), „Can Stock Market Forecasters Forecast‟, issued: Econometrica, Volume 1, Issue 3 (Jul., 1933), 309-324

Cootner, Paul, ed. (1964),‟The Random Character of Stock Market Prices‟, Cambridge, Mass.: MIT Press.

Dow, J., & Gorton, G. (1997), Stock Market Efficiency and Economic Efficiency: Is There a Connection?. Journal Of Finance, 52(3), 1087-1129.

De Bondt, W.F.M., Thaler, R., (1985), Does the stock market overreact? Journal of Finance 40 (3),793-805.

De Long, B. J.; A. Shleifer.; L. H. Summers.; R. J. Waldman. (1990), “Noise Trader Risk in Financial Markets”, Journal of Political Economy, Vol.98, No.4, pp. 703- 738

DeLong, J. B., Shleifer, A., Summers, L. and Waldmann, R. J. (1991), ―The survival of noise traders in financial markets, Journal of Business, Vol. 64, 1991, pp. 1–20. Daniel, K., D. Hirshleifer and A. Subrahmanyam (2001), Overconfidence, arbitrage and equilbrium asset pricing‖, Journal of Finance 56, pp.921−965

Elroy Dimson and Massoud Mussavian (1998), „A brief history of market efficiency‟, Published in European Financial Management, Volume 4, Number 1, March 1998, p 91-193 European Bank for Reconstruction and Development (1998) Transition Report: Financial Sector in Transition, London: EBRD.

Fama, E. (1970). Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25(2), 383-417.

Fama, E. and k. French (1988), Permanent and Temporary Components of Stock Prices, Journal of Political Economy, 246-273

Fama, E. , Fisher L., Jensen M., and Roll R. (1969), „The Adjustment of Stock Prices to New Information,‟ Int. Econ. Rev. 10, 1-21

Fama, E. and G. W. Schwert, (1977), “Asset Returns and Inflation”, Journal of Financial Economics, November, 5:2, pp. 55–69.

Fama, E. and K. French. (1988), “Permanent and Temporary Components of Stock Prices” ,Journal of Political Economy, 96:2, pp. 246–73

Fama, E. and K. French. (2002),“The Equity Premium.” Journal of Finance. 62:2, pp. 637–59 Friedman, M. and L.J. Savage (1948), The Utility Analysis of Choice Involving Risk, Journal of Political Economy 56 (4), pp. 279-304

Froot, K., and Dabora, E., (1999), “How are Stock Prices Affected by the Locationof Trade?”, Journal of Financial Economics 53, 189 -216.

Granger, C. W. J., and O. Morgenstern, 1963, “Spectral Analysis of New York Stock Market Prices”, Kyklos, 16(1), 1-27.

Harrison, B., & Moore, W. (2012), Stock Market Efficiency, Non-Linearity, Thin Trading and Asymmetric Information in MENA stock Markets, Economic Issues, 17(1), 77-93. Hirshleifer, D., Subrahmanyam, A. and Titman, S. (2006), Feedback and the success of irrational traders‖, Journal of Financial Economics, Vol. 81, pp. 311–388

Herschberg M (2012), Limits to Arbitrage: An introduction to Behavioral Finance and a Literature Review, issued: Palermo Business Review | Nº 7 | 2012, available: http://www.palermo.edu/economicas/PDF_2012/PBR7/PBR_01MiguelHerschberg.pdf Lo, Andrew W. and MacKinlay, A Craig, (1988), „Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test‟, Review of Financial Studies, Spring 1988, 1, 41-66

Lo, A. and Hasanhodzic, J., (2010), The Evolution of Technical Analysis: Financial Prediction from Babylonian Tablets to Bloomberg Terminals, Bloomberg L.P. New York.

Lo, Andrew W. and A. Craig MacKinlay (1999), A Non-Random Walk Down Wall Street. Princeton:Princeton University Press.

Lakonishok, J., Shleifer A., and Robert W. V. (1994), „Contrarian investment, extrapolation, and risk‟, journal of finance 49, 1541-1578

Jaffe,J.F. (1974), Special Information and Insider Trading 47 J. Bus. 410

Jegadeesh, N. and S. Titman (1993), Returns to buying winners and selling losers: implications for stock market efficiency, Journal of Finance 48, pp. 65-91

K. McKinley & E. College (1999), Stock Market Efficiency and Insider Trading, Issues in Political Economy, available at: org.elon.edu/ipe/mckinley.pdf

Kahneman, D., and A. Tversky (1979), Prospect theory: an analysis of decision under risk, Econometrica 47, pp.263−291.

Keim, Donald B. and Robert T. Stambaugh. (1986), “Predicting Returns in Stock and Bond Markets.” Journal of Financial Economics. December, 17, pp. 357–90

Keim, Donald B. (1983), “Size-Related Anomalies and Stock Return Seasonality: Further Empirical Evidence.” Journal of Financial Economics. June, 12, pp. 13–32

Nevins (2004), Goals-based Investing: Integrating Traditional and Behavioral Finance‖, The Journal of Wealth Management, Spring.

Nicholson, S. F. (1960), “Price-Earnings Ratios.” Financial Analysts Journal. July/August, 16, pp.43–50

Malkiel, B., (2003), The Efficient Market Hypothesis and Its Critics, Journal of Economic Perspectives, Vol.17, No 1, pp. 59–82.

Malkiel, B., (1989), „Is the Stock Market Efficient?‟, Source: Science, New Series, Vol. 243, No. 4896 (Mar. 10, 1989), Published: American Association for the Advancement of Sciencepp. 1313-1318

Malkiel, B. (2000), “Review of Robert J. Shiller‟s Irrational Exuberance.” Wall Street Journal. April 4.

Mishkin, F. (1997), The Economics of Money, Banking, and Financial Markets. New York, NY: Addison-Wesley, 1997

Mehra, R. and E. Prescott (1985) The Equity Premium: A Puzzle, Journal Of Monetary Economics, pp.145-61

Miller, M. and M. Scholes (1982), Dividends and taxes: Some empirical evidence, Journal of Political Economy 90, pp. 1118-1141

Mandelbrot, B. (1966), „Forecasts of Future Prices, Unbiased Markets and „Martingale‟ Models‟, Journal of Business, January, 242–55.

Kendall, M.G. (1953), „The Analysis of Economic Time Series I‟, Journal of Royal Statistical Society, Series A, Vol. 116, 11–25.

Osborne, M.F.M. (1959), „The Brownian Motion in the Stock Market‟, Operations Research, March-April, 145–73

Odean, T. (1998a), Are Investors Reluctant to Realize their Losses?, Journal of Finance 53, pp. 1775-1798

Patell, J. and M. Wolfson, (1984), The intraday speed of adjustment of stock prices to earnings and dividend announcements, Journal of Financial Economics 13, 223-252 Poterba, J. M. and Summers L. H. (1988), „Mean Reversion in stock Prices: Evidence and Implications,‟ Journal of Financial Economics, Octber 1988, 22, 27-59

P. Dodd (1981), \"The effect on market value of transactions in the market for corporate control,\" Proceedings of Seminar on the Analysis of Security Prices, Center for Research in Security Prices, University of Chicago, Chicago, May 1981.

Prast, H., (2004), “Investor Psychology: A Behavioural Explanation of Six Finance Puzzles”, Research Series Supervision

Ross, S., Westerfield, R., Jaffe J., Jordan B., S (2008), Modern Financial Management, 8th edition, McGraw Hill, New York.

Roberts, H.V. (1967). “Statistical versus clinical prediction of the stock market”, unpublished paper presented to the seminar on the Analysis of Security Prices, University of Chicago. Spyrou, S. (2003), Introduction to Behavioral Finance, Benou Publishing Company, Greece Ritter, J.R. (2003), “Behavioral Finance”, Science Direct-Pacific Basim Finance Journal 2-12. Rendleman, R., C. Jones, and H. Latané (1982). “Empirical Anomalies based on Unexpected Earnings and the Importance of Risk Adjustments,” Journal of Financial Economics, 10, 3, 269-287.

Roll, R., (1984), Orange juice and weather. American Economic Review 74, 861–80 Sewell, M., (2010), “Behavioural Finance”, Available online at: http://www.behaviouralfinance.net/behavioural-finance.pdf

Sewell, W., (2005), Logics of History: Social Theory and Social Transformation. The University of Chicago Press, Chicago.

Shiller, R.J. (2003) „From efficient markets theory to behavioural finance‟, Journal of Economic Perspectives, 17(1):83-104.

Shiller, R. (2000), Irrational Exuberance‖, Princeton: Princeton University Press. Shleifer, A. (2000), Inefficient Markets: An Introduction to Behavioral Finance, (Oxford University Press)

Shefrin, H., and M. Statman (1985), The disposition to sell winners too early and ride losers too long: Theory and evidence, Journal of Finance XL (3), pp. 777-792

Stiglitz, Joseph E. (1993), Economics. New York, NY: W. W. Norton & Company, Inc., pg. 266-271.

Shefrin, H., (2001), Behavioral Corporate Finance, issues: National Bureau of Economic Research, Vol.14, No 3. pp 21-33.

Shleifer, A., and R. Vishny (1997), The limits of arbitrage, Journal of Finance 52, pp.35−55. Scheinkman, J., and W. Xiong (2003), „Overconfidence and speculative bubbles‟, Journal of Political Economy, forthcoming

Sharpe, W., and G. Alexander, (1990), „Investments‟, 4th edition, issued by: Prentice Hall, Englewood Cliffs, N.J

Samuelson, P. (1965). Proof that properly anticipated prices actuate randomly. Industrial Management Review Spring 6, 41-49.

Subrahmanyam A., (2007), Behavioral Finance: A review and Synthesis, European Financial Management, Vol. 14, No. 1, pp.12–29

Rabbani S., Kamal N., Salim M. (2013), Testing the Weak-Form Efficiency of the Stock Market: Pakistan as an Emerging Economy, Journal of Basic and Applied Scientific Research

Thaler, R. (1980), Toward a positive theory of consumer choice, Journal of Economic Behavior and Organization I, pp. 39-60

Thaler, R., (1993), „Advance in Behavioral Finance‟, Princeton University Press. New Jersey. USA.

Taylor, S. and J.D. Brown (1988), Illusion and well-being: A social psychological perspective on mental health, Psychological Bulletin 103, pp. 193-210

Thaler, R., and Barberis, N., (2002), A Survey of Behavioral Finance, Handbook of the Economics of Finance, National Bureau of Economic Research

Solnik B., (1973), „Note on the validity of the random walk for European stock prices‟, The Journal of Finance 28 (5), 1151-1159

Shleifer, A. (1986), „Do Demand Curves for Stocks Slope Down?‟ Journal of Finance 41,579 -590

Shleifer, A. (2000), Inefficient Markets: An Introduction to Behavioral Finance. 1st edition, Oxford University Press, USA

Gervais, S., Heaton, J.B., Odean, T. (2002). The Positive Role of Overconfidence and Optimism in Investment Policy (pp. 1-36): The Rodney L. White Center for Financial Research.

Yalçın, K., C., (2010), \"Market Rationality: Efficient Market Hypothesis vs. Market Anomalies \Jensen M (1969), Risk the pricing of capital assets and the evaluation of investment portfolios, J Bus 42:167–247

Rendleman, R., C. Jones, and H. Latané (1982). “Empirical Anomalies based on Unexpected Earnings and the Importance of Risk Adjustments,” Journal of Financial Economics, 10, 3, 269-287.

Roll, R., (1984), Orange juice and weather. American Economic Review 74, 861–80