From the Efficient Market Hypothesis Essay

From the Efficient Market Hypothesis to Behavioral Finance How Investors’ Psychology Changes the Vision of Financial Markets by ADAM SZYSZKA Poznan University of Economics Poland adam. [email protected] poznan. pl I. Introduction The efficient market hypothesis (EMH) has been the key proposition of traditional (neoclassical) finance for almost forty years. In his classic paper, Fama (1970) defined an efficient market as one in which “security prices always fully reflect the available information” [p. 383].

In other words, if the EMH holds, the market always truly knows best. Until the mid-1980s the EMH turned into an enormous theoretical and empirical success. Academics from most prestigious universities and business schools developed powerful theoretical reasons why the efficient paradigm should hold. This was accompanied by a vast array of early empirical research – nearly all of them supporting the EMH. The idea that the market knows best was promoted in business press and taught at various MBA and other courses.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now

It strongly influenced the investment community (increased popularity of index funds and the buy-and-hold strategy), but luckily not everybody. From the beginning of the 1980s, and more and more in the 1990s, new empirical studies of security prices have reversed some of the earlier evidence favoring the EMH. The traditional finance school named these observations anomalies, because they could not be explained in the neoclassical framework. In the response to a growing number of puzzles, a new approach to financial markets has emerged – behavioral finance.

It focuses on investors’ behavior and the decision making process. In the contrary to the classical paradigm, behavioral finance assumes that agents may be irrational in their reactions to new information and make wrong in investment decisions. As a result, markets will not always be efficient and asset pricing may deviate from predictions of traditional market models. Electronic copy available at: http://ssrn. com/abstract=1266862 This paper confronts the main foundations of the neoclassical theory of the capital market and asset pricing with allegations of behavioral finance.

Cornerstones of the traditional theory are discussed in the first section. It is followed by a brief presentation of the behavioral approach. Further, the paper discusses consequences of the new view of finance to capital market practitioners – investors, corporate finance, and policy makers. The paper concludes with final remarks and some thoughts on the future development of the capital market theory. II. The Traditional view The EMH rests on three assumptions. Each of them is progressively weaker.

First, investors are assumed to be rational and hence to value assets rationally. They should value each security for its fundamental value: the net present value of future cash flows, discounted by a rate appropriate to the risk level. When investors learn something new about future cash flows or risk attached to a particular security, they should quickly and appropriately (no under- and no over-reaction) respond to the new information by bidding up prices when the news is good or bringing them down when the news is bad.

As a consequence, asset prices should incorporate all the available information almost immediately. If one would like to consistently make more money than the average on the market based only on publicly available information, one would have to react always quicker to new than the rest of market participants, and this is obviously not possible every time. However, markets may remain efficient even if not all investors are rational and some of them make mistakes in perceiving and reacting to information.

In such a case, it is assumed that irrational investors in the market trade randomly. When their trading decisions are uncorrelated, their impact is likely to cancel each other out. Altogether they will not generate a market force that could influence the equilibrium prices. Their transactions will only increase the trading volume. This argument relies crucially on the lack of correlation in the behavior of irrational investors. But even if irrationality becomes common for a relatively large group of investors who act in a correlated manner, and therefore are able to ove prices away from fundamental levels, it is assumed that rational arbitrageurs will quickly notice the mispricing and act appropriately. By selling the overpriced asset on one market and buying the same or similar asset on the other cheaper market, they will create additional market forces that will bring asset prices back to equilibrium levels. It is assumed that there are many rational arbitrageurs who act quickly and without any constrains. Electronic copy available at: http://ssrn. com/abstract=1266862 The argumentation in favor of the EMH seems quite appealing.

In short, it follows like that: When all people are rational markets are efficient by definition. When some people are irrational, their behavior is usually uncorrelated and the impact of their trades is too weak to influence prices. Finally, when sometimes irrational investors behave in a correlated manner (like a herd) and they sometimes have enough of a market force to drive the prices away from fundamentals, then active and unlimited trades of rational arbitrageurs will countervail and bring the prices back to right levels.

The EMH is closely related to two other cornerstones of neoclassical financial economics: the Capital Asset Pricing Model (CAPM) developed independently by Sharpe (1964), Lintner (1965) and Mossin (1966), and the portfolio theory of Markowitz (1952). If market is efficient and all available information is correctly reflected in asset prices than investors should not expect to achieve in a long term higher returns than the level justified by the amount of systematic risk attached to a particular security.

The CAPM states that the relationship between the expected return and the amount of systematic risk is linear. Early empirical tests of the CAPM gave relatively good results, despite the fact that the model had been derived under many rigorous and unrealistic theoretical assumptions. However later studies, covering longer and wider time series of data, are far less convincing and rather contradict the original version of the CAPM. This leads to so called dual hypothesis problem. If the empirical tests do not confirm the CAPM we cannot be sure if the model is wrong or maybe the market is not efficient.

The current view within the school of traditional finance attempts to defend market efficiency suggesting that there might be other factors, beside the beta – that measure the amount of undiversifiable market risk. The three-factor model of Fama and French (1992, 1993, 1996) is the best known example in this vein. The main problem with these new models is that they are based on regressions that are designed to fit the data. Their theoretical background is very discussible. The same models, but interpreted differently, are often used by the behavioral school in the argumentation against market efficiency.

But let us stay at this point of the paper still in the traditional view. If the EMH is true and the market pays returns only for the amount of undiversifiable systematic risk, then investors should construct their investment portfolio according to the theory of Markowitz (1952). Each investor should hold a well-diversified efficient portfolio – this means a collection of assets that altogether have a minimum covariance with the market portfolio (minimum systematic risk) for a given level of expected return.

Alternative approach assumes maximization of expected return for a set level of systematic risk. As a consequence of the Markowitz portfolio theory, investors should not look at the amount of risk of each individual security if held in isolation, but rather should concentrate how this particular security will influence their total portfolio risk. In other words, it is important to look at the covariance of a security with other assets that are already in possession, and to seek assets that held together minimize the total covariance between the investor’s portfolio and the market.

The traditional school of financial economics has one main advantage – It is of a normative character. The key elements of the theory are coherent and allow deriving predictive models that might be tested. It also has one main disadvantage – It has been based on many unrealistic assumptions. The building blocks of the traditional finance rely mainly on investors’ rationality (the concept of homo economicus) and on strength of the self-correcting mechanism of arbitrage (the notion of perfect market). However, these features are not always confirmed in true life.

The empirical studies show in many cases that the reality is far from what theoretical models predict. Observations that are difficult to explain in the traditional framework of financial economics have been named anomalies or puzzles. But quite often they are not as anomalous as they may seem. They usually emerge from underestimating the fact that markets are made by people who behave not always rationally and sometimes make common mistakes. On the other hand, the correcting power of rational arbitrageurs is often overestimated, because there are practical limits to arbitrage. III. The Behavioral Approach

Behavioral finance is an area within the finance discipline that focuses on investors’ behavior and the decision making process in order to understand anomalous pricing of assets and other puzzling observations taken empirically from capital markets. It has emerged in the response to the difficulties faced by the traditional theory in explaining some financial phenomena. In the contrary to the classical paradigm, behavioral finance assumes that agents may be irrational in their reactions to new information and investment decisions. The sources of irrationality are psychological biases and heuristics of a human mind.

It can be difficult for rational traders to undo the mispricing caused by irrational investors due to existing limits of arbitrage. As a result, markets will not always be efficient and asset pricing may deviate from predictions of traditional market models1. Thaler (1993, 2005) edited two collections of most significant papers in the area of behavioral finance. Books by Shefrin (2000, 2005), Shleifer (2000) and Szyszka (2007) are also good sources for readers interested to find out more about the behavioral approach to finance. 1 III. 1. Investor’s Psychology Psychological sources of irrationality may be categorized in a following way.

First, people make mistakes when they perceive information and form their beliefs. Extensive evidence shows that individuals are overconfident in their judgments (Odean (1998), Barber & Odean (2001)). They are typically also overoptimistic and see things better than they really are. Sometimes their optimism comes from wishful thinking. Generally overconfidence and overoptimism make investors trade too much and too intensively. In the result they take too much undiversified risk and lose money on heavy transaction costs. This also may cause market to overreact to new information. Further, people have problem with epresentativeness, sample size and understanding the law of return to the mean (Shefrin 2000). This leads to difficulties in drawing correct conclusions based on available information. Among other things, it increases the belief in trend continuation or reversal of direction in which prices change. Once people have formed an opinion, they often stick to it and inadequately update their beliefs in the lieu of new information (Edwards (1968)). The initial value may sometimes be even suggested subconsciously and still strongly influence the agent’s opinion (so called anchor – Kahneman & Tversky (1974)).

Conservatism, belief perseverance and anchoring slow down the reaction of the market to new information. Second important source of irrationality comes from unstable preferences that may vary depending on a context in which the alternatives are presented. Logically the same decision problems may be solved differently by the same people when the situation is described in another way. This contradicts the axioms of the standard utility theory. Kahneman and Tversky (1979) propose the prospect theory in which utility is defined over changes of wealth comparing to a given reference point rather than over final wealth positions.

The main finding of the prospect theory is that people are risk-averse over gains and risk-seeking over losses. This means that they usually prefer a certain gain than a gamble of the same expected value with a chance for much higher win. On the other hand, when faced with a choice between a certain loss and a gamble of the same negative expected value (that potentially may lead to even a greater loss, but also gives a chance to avoid the loss), people usually prefer to take the risk and to gamble. Kahneman and Tversky argue that the sensitivity to losses is greater than the sensitivity to gains.

In other words, a loss of 1000 US$ is more painful than the satisfaction from a gain of 1000 US$. The prospect theory explains so called disposition effect – eagerness of people to sell an asset that has just brought profit and strong reluctance to close a position that has been bringing losses. The disposition effect may be responsible for market underreaction to new information, particularly for slower reflection of bed news in prices. The third cause of irrationality lays in human emotions and moods.

Generally people who are in good moods are more optimistic in their choices and judgments than those in bad moods. Investors in good moods are ready to accept higher risk. Bad moods are associated with more scrutiny and criticism when evaluating new information (Petty, Gleicher & Baker (1991)). People are often influenced by weather conditions – they feel happier on sunny days than on rainy days. Studies by Saunders (1993) and Trombley (1997) suggest that this may have a direct implication to capital markets – on average market returns are higher on days of good weather than on days with heavy clouds or rain.

Shefrin (2000) points at two kinds emotions – greed and fear – that have contradictive influence on investors’ risk approach and strongly influence the way they construct their investment portfolio. Greed pushes people to treat stocks as lottery tickets – they want to win as much as possible and as quickly as possible. In the result, they do not diversify and take risky positions in two-three assets hoping to earn high returns if their picks are right. People are usually not interested in relatively low returns. They want to win high enough to significantly improve their consumption and to move them up at the social pyramid.

On the other hand, fear is like breaks in a speeding car. It gives limits to greed. People usually care about the future and are afraid of unexpected negative events that could dramatically lower the level of their consumption. They tend to hold some proportion of their wealth in very safe assets (cash deposits or T-bonds) that serve like a security policy (“just-in- case…”). In other word, a combination of greed and fear leads to wrong diversification of investment portfolios. Investors do not use the Markowitz’s theory and overlook the covariance between assets.

They isolate mentally the few risky assets and the “just-in-case” safe investment they hold. Finally, social influence and interaction with other people also may cause irrational behavior. Investors may make common mistakes in a correlated manner as the result of their learning process in a society, direct interpersonal communication, influence of social groups in which they live, and – most of all – because of the force of media news. People often behave like sheep – they follow each other like in a herd. But what is interesting – herding does not always have to be irrational.

Rational traders may also decide to follow the group if they rationally calculate that making money “on the wave” is more likely than fighting against the flow of irrational players. Herding leads to a situation when investors concentrate more on predicting what other market participant think than on real information related to a particular security. It starts to be less important if the fundamentals of the company are good or not. It is rather important if other investors like the stock or not, and if they are prepared to pay for it in the near future even more than its current market price.

Such a way of thinking facilitates asset mispricing. When important information related to securities is disregarded, and investors are pronoun to various fashions and fads, market quotes may deviate far from fundamental values (see the internet bubble). III. 2. Limits to arbitrage Behavioral finance does not negate the arbitrage mechanism per se and its pricecorrecting ability. However, it argues that not every deviation from fundamental value created by actions of irrational traders will be an attractive investment opportunity for rational arbitrageurs.

Even when an asset is widely mispriced, arbitrage strategies designed to correct the mispricing can be risky and costly, rendering them unattractive, and sometimes can be even impossible to conduct at all. As a result, the deviation from fundamental value may remain unchallenged for a relatively long time. When arbitrageurs discover an asset that is wrongly priced on a market, they need to find the same asset priced correctly on another market or a perfect substitute of this asset, in order to take opposite arbitrage positions.

When they are not able to do so, they face the fundamental risk – the risk that some new information comes to the market and changes the fundamental value of the asset in the undesired direction. Even when arbitrageurs are able to hedge the fundamental risk completely and take a long position in the asset where it is cheaper and a short position in the same asset on the other market where it is more expensive, they still face so called noise traders risk. This is the risk that irrationality on the arket may become stronger and may drive the mispricing to even a greater extent (DeLong Shleifer, Summers & Waldmann (1991), Shleifer & Vishny (1997), Shleifer (2000)). As the mispricing increases, the gap between long and short positions gets wider and against the strategy of rational arbitrageurs. If such a tendency continuous over time, arbitrageurs – whose investment horizon is usually relatively short and who often borrow money and securities to put on their trades – may be forced to close their positions before the mispricing is corrected.

If this is a case, they will suffer losses. But a single arbitrageur who spots the mispricing faces not only the noise traders risk, but also the risk of synchronization of actions of other rational traders (Abreu & Brunnermeier (2002)). Typically a single arbitrageur does not have enough of market force to correct the mispricing individually. He needs other arbitrageurs who will follow his strategy. However, he does not know if and how quickly other rational traders notice the same arbitrage opportunity and take adequate positions.

Waiting might be costly and each arbitrageur has a finite time and cost limits. Arbitrage is costly because of commissions, bid-ask spreads, fees charged for borrowing stocks to take a short position and the necessary amount of research needed to find and to learn about the mispricing. Arbitrageurs may also face other implementation barriers, usually related to taking a short position. There is simply sometimes no-one willing to borrow stocks, especially if the company’s capitalization is relatively small and its stocks are illiquid.

There can be also legal constrains: for a large fraction of asset managers – in particular pension funds, insurance funds, and mutual funds managers – short selling is simply not allowed. Limits to arbitrage are confirmed empirically by cases of obvious mispricing that remain unchallenged for a relatively long time, although they are clearly noticeable for investors, especially professionals. These include so called twin stocks (Royal Dutch and Shell or Unilever N. V. nd Unilever PLC) that are perfect substitutes to each other, but still trade at price levels that allow – at least theoretically – easy arbitrage profits (Froot & Dabora (1999)). Other examples come from so called carve-outs – transactions when a publicly listed mother company sells a minority stake in its daughter company in the Initial Public Offer (IPO). In some extreme cases the market value of stocks offered in the IPO was higher than the market capitalization of the whole mother company holding a majority stake in a daughter company (Lamont & Thaler (2003)).

Yet another puzzle comes from closed-end funds. Funds units, representing investors’ rights to the assets held by a fund, often trade with a substantial discount to the Net Asset Value (NAV) whereas NAV is really an equivalent of the fundamental value of a unit (Lee, Shleifer & Thaler (1990, 1991)). A closer look at those anomalies shows that in all these cases rational arbitrageurs face risks, costs or problems with shorting, which make arbitrage unattractive or even not feasible. IV. Consequences to market practitioners Behavioral finance changes the way we should look at capital markets.

This new approach has significant consequences not only directly to investors, but also to corporate finance, market regulators and policy makers. IV. 1. Consequences to investors The EMH rules out the possibility of repeatable investment strategies based on currently available information that have expected returns in excess of the market expected return for a particular level of systematic risk. In other words, an average investor – whenever an individual or professional – should not hope to consistently beat the market.

In a short term achieving abnormal returns is possible, but only as a simple result of luck, and not due to whatever trading strategy used or resources spent on analysis. In the light of the EMH the best investment strategy is the passive “buy & hold” approach – investors should hold welldiversified portfolios, allowing only for the systematic risk in the amount adjusted to a subjective degree of risk aversion and expectation of returns. Often changes to the portfolio are not recommended, as active trading only generates transaction costs and cannot help at all to achieve long-term abnormal returns.

Behavioral finance challenges this view, what is a natural consequence of confronting the EMH. According to the behavioral approach market is not always efficient and investors who make a better than average use of available information are able to make abnormal returns. In this light, it might be worth to seek good investment opportunities and to spend resources on investigation of the mispricing that occur from time to time on the market. Active trading strategies might be indeed better in some cases than passive “buy & hold”.

This is a rationale for various hedge funds, so called opportunity funds, and other active portfolio management. However, active investors should bear in mind that they also may be a subject of behavioral biases and heuristics. Therefore, achieving higher returns is possible not only thanks to better analysis and strategies, but also requires a better self-control. Behavioral finance does not rule out completely the utility of traditional analytical tools and pricing methods derived from traditional finance.

However, these models should not be treated dogmatically as the only precise way to judge investment choices. In the end, they are only a simplification of complex processes ongoing in reality on capital markets. Traditional finance should be seen more like a theoretical benchmark that needs to be enriched by various aspects of investors’ psychology and human actions. Behavioral market models concentrate on predicting deviations from traditional models. They focus on investors’ irrationality and attempt to identify factors responsible for its direction and strength.

When mispricing is noticed investors should ask themselves about the reasons for the situation and should try to predict its future development. If behavioral analysis indicate a high probability of further increase of irrationality that potentially may lead to even a bigger mispricing and at the same time there are limits to arbitrage, than also for a rational investor it might be worth to “hop on a train” and to buy assets that according to traditional valuation methods might seem overpriced.

In the lieu of traditional finance such a decision would be irrational, but in the framework of the behavioral approach it is acceptable. It might bring abnormal profits as long as the investor is able to sell these assets for a higher price before irrationality gets weaker and finally stocks are brought back to fundamental levels. Obviously such practices of rational speculators do not serve well market efficiency and stabilization. IV. 2. Consequences to corporate finance If markets are efficient, than the cost of equity is always priced correctly.

Current market situation should not influence corporate capital structure. Companies should not be extra motivated to make additional equity offerings in a bull market – when they are potentially overpriced, nor to buy-back their stocks in a bear market – when they seem to be undervalued. Behavioral finance offers a different view. High market valuations are motivation for increasing equity. Relatively cheap equity often lowers total weighted average cost of capital (WACC) for the company. This may boost investment, as more projects have positive net present value (NPV).

In bad times the company will tend not to make new equity offerings. New investment projects will be financed with a higher leverage or put on hold. More debt will be allowed in the capital structure. Low market valuation may also stimulate the company to buy-back its stocks. Behavioral approach may help to choose an optimal moment for a new offering or a buy-back transaction. It is also helpful when planning a takeover of another firm in a public tender offer. Knowledge of investors’ preferences is necessary when structuring the transaction and to set the price right.

For example, even if a price in a tender offer is higher than a current market price (takeover premium), but the tender offer takes place after a series of negative returns, the reply to the offer may not be sufficient. This may happen, because investors are stopped by a strong aversion to losses, if the tender price is set below their reference point that usually is their buying price. Psychological aspects are also important when communicating with the market. The way the news is put into words or numbers may influence the strength of market reaction to it.

People usually overreact to good information and underreact to bad news. They pay more attention to a descriptive report than to statistical or numeric data. They are sensitive to the context in which the information is given. For example, assume that the current firm’s performance is better than last year, but worse than earlier forecast and market expectation. News like “The current profit is higher than the last year’s profit by …” will be definitely better received than the same information formulated “The current profit is lower than expected by …”.

Finally, we should not forget that corporate managers may also be a subject to behavioral biases. Wrong judgment of probability accompanied by overconfidence may lead to underestimating risk of an investment project. Particularly strong and dangerous inclination is associated with so called sunk costs. Decision makers are usually unwilling to give up a project that has already consumed a lot of money and effort. Even if it becomes more and more obvious that the project has little chance to be profitable, managers are often ready to spend more and more money on it.

They do not want to admit their mistake and attempt to delay the moment they have to report a loss on the investment. This is similar to the disposition effect observed among stock market investors. The sunk cost effect and the disposition effect have both their roots in the strong human aversion to accept final losses. IV. 3. Consequences to market regulators and policy makers Rejection of the efficient market paradigm results in a serious challenges for those who are responsible for the market infrastructure and regulations.

It clearly turns out that the self-regulating market mechanism is imperfect and requires proper regulations that take into account a possibility of irrational human behavior. The aim of regulators and policy makers should focus on creation of such conditions in which behavioral inclinations have minimum impact on asset pricing and the market behaves as close as possible to the idealistic predictions of the neoclassical theory. First, a wide-scale educational action is needed. Individual investors should be taught about psychological traps, in particular they should be warned about all sorts of manias, fads and other cases of herding.

The more investors are aware about possible sources of price deviation, and the more they search for cases of mispricing to use them for their own profits, the higher the market efficiency. Second, the sector of institutional investors should be shaped in the way that accounts for possible behavioral biases of professional asset managers. Among other things, there should be incentives for professionals to think more in a long-term perspective, and not only to pay attention to relatively short reporting periods. Window dressing practices should be iscouraged by closer evaluation and audit. Compensation structures should be designed with consideration and should offer deliberately higher bonuses for being above the average than penalties for results below the benchmark. Benchmarks should be set appropriately Finally, regulators and policy makers should work hard on minimizing limits to arbitrage, at least in cases where it is reasonable. Support of stocks’ liquidity, unproblematic possibility to short all assets, low borrowing fees and other transaction costs, easy access to information are among most straightforward postulates.

Fewer limits to arbitrage both for individuals and professionals enhance the self-regulating market mechanism and reduce the impact of behavioral biases on asset pricing. V. Conclusions Behavioral finance has changed the neoclassical vision of financial markets and shaken its foundations. It argues that investors not always are able to value correctly the utility of decision alternatives, cannot estimate and updated probability of events, and do not diversify properly as suggested by Markowitz’s portfolio theory. Irrationality of a large group of market participants acting in a correlated manner may influence asset prices.

Arbitrage turns out to be both risky and costly and cannot guarantee that the self-regulating market mechanism will work at all times. As a result, the mispricing not always is corrected quickly and sufficiently. The Efficient Market Hypothesis (EMH) does not hold. This conclusion has major consequences for the entire finance community: investors, corporate finance, as well as for regulators and policy makers. At the current stage of development behavioral finance is not yet a new unified theory of financial markets.

Although a great deal of literature has been published in this area, the character of most of papers is selective and relatively of a narrow scope, explaining usually only one or two effects at the time. Behavioral finance does not substitute neoclassical finance, but rather adds to the traditional view, modifies it, and fills some gaps. However, there have been already some attempts to elaborate on this basis more formal and integrated behavioral theory and to create behavioral market models at more general level (Shefrin (2005), Szyszka (2007)). Notwithstanding if ehavioral finance is able to transform definitely into a new complete theory or it is only an addition to the neoclassical school, its importance is already undisputable. It offers explanation to many controversial empirical observations that could not be explained in the traditional framework. Most of all, it serves better understanding of complex processes happening on capital markets and helps to avoid psychological traps.

Bibliography Abreu D. , Brunnermeier M. (2002), “Synchronization risk and delayed arbitrage”, Journal of Financial Economics, Vol. 66, 2-3, p. 341-360 Barber B. , Odean T. 2001), “Boys will be Boys: Gender, Overconfidence, and Common Stock Investment”, Quarterly Journal of Economics, Vol. 141, 2, p. 261-292 De Long B. , Shleifer A. , Summers L. , Waldmann R. (1991), “The Survival of Noise Traders in Financial Markets”, Journal of Business, Vol. 64, 1, p. 1-19 Edwards W. , (1968), “Conservatism in Human Information Processing”, in: Klienmutz B. (red. ), Formal Representation of Human Judgment, New York: Wiley, p. 17-52 Fama E. (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work”, Journal of Finance, Vol. 25, 2, p. 383-417 Fama E. , French K. 1992), “The Cross-Section of Expected Stock Returns”, Journal of Finance, Vol. 47, 2, p. 427-465 Fama E. , French K. (1993), “Common Risk Factors in the returns of stocks and bonds”, Journal of Financial Economics, Vol. 33, 1, p. 3-56, Fama E. , French K. (1996), “Multifactor Explanations of Asset Pricing Anomalies”, Journal of Finance, Vol. 51, 1, p. 55-84 Froot K. , Dabora E. (1999), “How Are Stock Prices Affected by the Location of Trade? ”, Journal of Financial Economics, Vol. 53, 2, p. 189-216 Kahneman D. , Tversky A. (1974), “Judgment Under Uncertainty: Heuristics and Biases”, Science, 185, p. 124-1131 Kahneman D. , Tversky A. (1979), “Prospect Theory: An Analysis of Decision Under Risk”, Econometrica, Vol. 47, 2, p. 263-292 Lamont O. , Thaler R. (2003), “Can the Market Add and Subtract? Mispricing in Tech Stock CarveOuts”, Journal of Political Economy, Vol. 111, 2, p. 227-269 Lee C. , Shleifer A. , Thaler R. (1990), “Anomalies: Closed-End Mutual Funds”, Journal of Economic Perspectives, Vol. 4, p. 153-164 Lee C. , Shleifer A. , Thaler R. (1991), “Investor Sentiment and the Closed-End Fund Puzzle”, Journal of Finance, Vol. 46, 1, p. 76-110 Lintner J. 1965), “Security Prices, Risk and Maximal Gains from Diversification”, Journal of Finance, December Issue Markowitz H. (1952), “Portfolio Selection”, Journal of Finance, Vol. 7, 1, p. 77-91 Mossin J. (1966), “Equilibrium in a Capital Market”, Econometrica, October Issue Odean T. (1998b), “Volume, Volatility, Price, and Profit When All Traders Are Above Average”, Journal of Finance, Vol. 53, 6, p. 1887-1934 Petty R. , Gleicher F. , Baker P. (1991), “Multiple Roles for Affect in Persuasion”, in: Forgas J. (ed. ), Emotion and Social Judgments, Oxford: Pergamon, p. 181-200 Saunders E. 1993), “Stock Prices and Wall Street Weather”, American Economic Review, Vol. 83, 5, p. 1337-1345 Sharpe W. F. (1964), “Capital Asset Prices: A Theory of Market Equilibrium”, Journal of Finance, September Issue Shefrin H. (2000), Beyond Greed and Fear. Understanding Behavioral Finance and the Psychology of Investing, Boston, MA, Harvard Business School Press Shefrin H. (2005), A Behavioral Approach to Asset Pricing, Elsevier Academic Press Shleifer A. (2000), Inefficient Marketp. An Introduction to Behavioral Finance, Oxford University Press Shleifer A. , Vishny R. 1997), “The Limits of Arbitrage”, Journal of Finance, Vol. 52, 1, p. 35-55 Szyszka A. (2007), A Behavioral Approach to Financial Marketp. How Psychological Biases Influence Asset Pricing, published in Polish by the Poznan University of Economics Press, in print in English Thaler R. (1993), Advances in Behavioral Finance, (ed. ), Russell Sage Foundation, New York Thaler R. (2005), Advances in Behavioral Finance, Vol. II, (ed. ), Russell Sage Foundation & Princeton University Press Trombley M. (1997), “Stock Prices and Wall Street Weather: Additional Evidence”, Quarterly Journal of Business and Economics, 36, p. 11-21