Capital Market Anomalies: Explained by human´s irrationality

Academic Paper 2013 82 Pages

Business economics - Economic and Social History


Table of Contents

1. Introduction
1.1. Problem Specification
1.2. Objective
1.3. Structure

2. Theoretical Basis of Behavioural Finance
2.1. Heuristics
2.1.1. Availability Heuristic
2.1.2. Representative Heuristic
2.1.3. Anchoring Heuristic
2.2. Behavioural Anomalies/Irrationalities
2.2.1. Information Perception Anomalies Framing Effect Risk Sensitiveness Selective Perception
2.2.2. Information Processing Anomalies Reference Point Effect Mental Accounting Loss Aversion
2.2.3. Decision Making Anomalies Cognitive Dissonance Regret Avoidance Overconfidence Bias

3. Capital Market Anomalies/Phenomena
3.1. Calendar Anomalies
3.1.1. Weekend Effect
3.1.2. January Effect
3.1.3. Turn-of-the-Month Effect
3.2. Figure Anomalies
3.2.1. Size Effect and Neglected-Firm Effect
3.2.2. Book-to-Market-Ratio Effect
3.2.3. Price-Earnings-Ratio Effect
3.3. Market Efficiency Anomalies
3.3.1. Index Effect
3.3.2. Bubbles and Crashs
3.3.3. Home Bias
3.3.4. Over-reaction and Under-reaction
3.3.5. Momentum Effect
3.3.6. Mean Reversion Effect
3.3.7. Announcement Effect
3.3.9. Closed-End Fund Puzzle

4. Empirical Evidence to the Capital Market Anomalies/Phenomena
4.1. Empirical Evidence to the Calendar Anomalies
4.1.1. Weekend Effect evidenced on International Markets
4.1.2. Other Studies to the remaining Calendar Anomalies
4.2. Empirical Evidence to the Figure Anomalies
4.2.1. Size Effect and Neglected-Firm Effect evidenced on the SDAX and DAX
4.2.2. Other Studies to the remaining Figure Anomalies
4.3. Empirical Evidence to the Market Efficiency Anomalies
4.3.1. Index Effect evidenced on the S&P
4.3.2. Bubbles and Crashs evidenced on the Tulipmania

5. Conclusion
5.1. Critical Acclaim
5.2. Target Achievement
5.3. Perspective


1. Introduction

1.1. Problem Specification

Why do small caps achieve higher risk-adjusted yields than large caps ? Why do stock prices increase or decrease upon an index entry respectively deletion ? Why does January records higher yields than the remaining months of the year ? These as well as other observed capital market anomalies respectively phenomena could insufficiently be explained by the classical capital market theory, which proceeds on the assumption, that all correspondent information are reflected in the stock prices, all negative effects are directly balanced on the market level and efficiency of arbitrage principle exists as well as all market participants are acting rational, i.e. optimizing their benefits in the sense of the homo oeconomicus. This motivated some economists and psychologists to research the influences on the formation of prices on the capital market while including behavioural scientific findings. Hence in 1980s Behavioural Finance has been developed, which challenges the homo oeconomicus and came to the conclusion, that humans are not only acting rational, but that they are influenced by emotions, knowledge as well as experiences, i.e. are irrational. Thus this new scientific behavioural oriented theory, which is today a separate branch of research, contradicts the classical capital market theory and supplies explanations for the observed phenomena on the capital market.

1.2. Objective

The aim of this thesis is to demonstrate how human behaviour influences the development on the capital market respectively Behavioural Finance serves as explanation for the empirically observed capital market anomalies.

1.3. Structure

This thesis begins with the introduction of the theoretical basis of Behavioural Finance respectively its emergence, tasks as well as aims will be explained in detail. Subsequently human’s heuristics as well as anomalies respectively irrationalities in their decision making process will be demonstrated. In the third chapter the capital market anomalies respectively phenomena as well as their rational respectively economical reasons and irrational respectively behavioural reasons for their existence will be described. The fourth chapter covers empirical evidence for their existence as well as for the insufficient explanatory power of the classical capital market theory. Concluding a critical acclaim, target achievement as well as perspective concerning Behavioural Finance will be given.

2. Theoretical Basis of Behavioural Finance

There are many definitions explaining the term Behavioural Finance. The three most commonly known definitions are as per the economists Thaler, Shefrin and Sewell. Thaler defines Behavioural Finance as an just open minded finance whereas Shefrin describes it as a fast-growing area that concerns with the influence of psychology on the behaviour of financial investors. The last economist Sewell determines it as a study, which researches the question to which extent psychical factors influence the behaviour of the market participants and their reactions the development of the financial markets. However, all definitions express the same meaning, namely that it is a behaviour-oriented financial market theory.[1]

Behavioural Finance has been developed, due to the insufficient explanatory power and predictive efficiency of classical capital market theories concerning capital market’s behaviour and its phenomena. Thus its task is to explain these capital market anomalies and its phenomena e.g. bubbles, as well as its final occurrences on the financial markets e.g. overreaction und thus the pricing and performance of stocks e.g. short terms stock volatilities and to search for reasons of market inefficiencies, while including the human behaviour, i.e. psychological and sociological aspects.[2]

Not the substitution, but a paradigm shift, i.e. the further development of the existing neoclassical capital market theory – in which all information are priced into the stock prices, error compensation on the market stage and efficiency of arbitrage principle exists as well as all market participants are acting rational, i.e. optimizing their benefits in the sense of the homo oeconomicus – is in the front of this theory respectively the development of an expectation development and information processing theory. This paradigm shift includes the replacement of the homo oeconomicus by human’s bounded rationality. Thus Behavioural Finance tries to create a connection between existing economical models and the reality.[3]

The target of Behavioural Finance is to identify factors, which influence human’s decision making process, which consists of three steps, namely the information perception, information processing and the decision making itself. In this way Behavioural Finance disclose a set of heuristics and systematic behavioural anomalies, which lead to faulty decisions, due to restricted information level caused by information costs, limited cognitive abilities caused by complex decisional situations and psychical stress, i.e. irrationality. This bounded rationality leads to faulty behaviour, which influences the capital market.[4]

2.1. Heuristics

As already explained in point two, in reality humans do not act in the sense of the homo oeconomicus, but are rational bounded. This rational bounded behaviour is reflected in the daily decision making process, where uncertainty exists, time, knowledge and information are limited and the complexity is high. In order to be able to make decisions under such suboptimal conditions, humans apply to heuristics.[5]

The term heuristic derives from the Greek word heurisco, which denotes to find. It is a cognitive method or strategy to solve problems, i.e. to come to decisions. Easily explained, they are mental shortcuts or rules of thumb, which facilitate and accelerate the solution of problems, i.e. the decision making process, if the above mentioned basic conditions are given.[6]

Heuristics will be applied conscious or unconscious. There is no clearly differentiation between conscious and unconscious heuristics. Conscious heuristics can become unconscious, if they will permanently be used whereas unconscious heuristics can be made aware und thus become conscious.[7]

The application of heuristics saves resources and time, which in turn will be used for other decisions. Hence they increase the efficiency of the thinking process.[8]

The results of heuristics are often correctly, but they also lead to wrong results, i.e. systematic judgemental bias, due to too strong complexity reduction and the herewith connected neglect of information.[9]

There exist three types of heuristics, which are the availability heuristic, representative heuristic and anchoring heuristic. Some authors do not classify them, but subsume them as judgmental heuristics. In contrary, others classify them as heuristics, which serve to reduce the complexity – availability heuristic – and heuristics, which serve to accelerate the decision making process – representative heuristic and anchoring heuristic – .[10]

These heuristics will be explained in the following.

2.1.1. Availability Heuristic

In order to make rush decisions humans apply to the availability heuristic by estimating the occurrence probability respectively the frequency of an event. Thereby they refer to already existing information in their minds, which represent the results of their made experiences. The easier humans remember an event and the more examples are available, i.e. the ease with which they come into mind the more probable and frequent it will be estimated. This process is also known as cognitive availability, which serves to reduce complexity, which in turn involves the neglect of information, which are not easy accessible and available.[11]

This heuristic leads to the overvaluation of information, which indicate a high subjective availability ratio, i.e. updated, frequent, easy accessible, very conspicuous, illustrative and easy understandable information. This in turn results in systematic biases in the decision making, errors and cognitive deception, i.e. it influences the estimation of the occurrence probability respectively the frequency of an event and hence the decision.[12]

This will be illustrated by the research done by Tversky and Kahneman:

They read two lists to test persons. The first list covered 19 names of famous men and 20 names of less celebrated women. The second list covered 20 names of famous women and 19 names of less celebrated men. The test persons should estimate, if the lists covered more women or men. The result showed, that over 50 percent of the participants remembered better the famous names and approximately 80 percent overvalued the number of this gender, who bears the famous name, i.e. they overestimated the names of the men indicated in the first list and the names of the women indicated in the second list.[13]

This example shows, that it is easier for humans to make decisions, based on the factor famous (easy accessible), as famous persons are often (frequent) presented on TV or magazines (updated, illustrative, easy understandable), either in a negative or positive way (very conspicuous), which in turn results in wrong estimation of the number of the genders.

2.1.2. Representative Heuristic

Representative heuristic is the second rule of thumb, which humans apply to in order to come to a rush decision. It is human’s tendency to think, estimate, evaluate and judge in patterns of thinking, i.e. in schemes. More precisely, they generalize persons, objects, events or phenomena based on cursorily characteristics, experiences or observations, which they made in the past. This generalization is based on similarities, e.g. between a sample and population, an element and a category or a cause and an effect. This process is also known as inductive conclusion, which serves to accelerate the decision making process, which will be reached by this generalization.[14]

This heuristic leads to biases in probability estimations and hence overvaluation of information or events, the higher characteristics, previously made experiences and observations correspond to the actual situation, i.e. if they suit to an existing scheme respectively are typical. That in turn results to wrong decisions.[15]

This heuristic involves several expressions, which are gamblers fallacy, also known as Monte-Carlo-Effect or law of small numbers, conjunction fallacy, conditional probability fallacy and ecological fallacy. In order not to extrapolate the frame of this thesis only the first two expressions will be explained in detail. Gamblers fallacy is human’s belief, that chances for something with a fixed probability increase or decrease depend on recent occurrences. Conjunction fallacy is human’s tendency to breach probability axioms. More detailed, they overestimate the probability of two connected events than the probability of each individual event.[16]

Gambler’s fallacy will be exemplified based on investigations done in a casino by Tversky and Kahneman: They observed roulette players and examined, if ten times black came up, most of the players tend to bet on the red for the eleventh drawn, as is it not typical eleven times to came up black.[17]

The investigation shows, that the probability of the first option has been overestimated whereas both options include the same probability.

The conjunction fallacy will be exemplified by their experiment, in which test persons shall make their estimations about a hypothetical person, based on the following information. The hypothetical person is a women, 31 years old, very intelligent and doesn’t mince matters. She studied philosophy and during her study period she dealt with matters such as social justice and discrimination. Additionally she participated on the demonstration again the nuclear power plant. After these basic information the test persons shall estimate which of both further personal traits are more probable. The first information was, that she is a bank clerk and the second information was, that she is a bank clerk and engaged in the women movement. The result showed, that the test persons estimated the second trait as more probable as somebody who studied philosophy and dealt with social and discrimination matters must also be engaged in women movement.[18]

This example shows, that humans overestimate the probability of two connected events whereas the probability of two connected events is never higher than the probability of a single event.

2.1.3. Anchoring Heuristic

The anchoring heuristic is the last heuristic, which will be demonstrated in this thesis. Just like the representative heuristic it serves to accelerate the decision making process. This will be reached by orientation on a reference point – in this regard a so called anchor, which can be an existing information or opinion – if humans make their decisions, forecasts or estimations. This anchor will afterwards be adjusted by newly obtained information.[19]

This heuristic leads to biases in decision making, due to drag on of the anchor adjustment. This occurs as humans tend to adhere to their previous anchors, even though the new information contradicts already existing anchor. Hence they make their decisions, forecasts and estimations close to their previous subjective anchor, which has incompletely or incorrectly been adjusted, which in turn leads to a partly or totally neglect of new information.[20]

This will be illustrated by an investigation done by Tversky and Kahneman:

Two groups of students obtained an arithmetic problem, which they should solve, i.e. estimate the solution within five seconds. The task of the first group was to provide an estimated solution for the arithmetic problem 1*2*3*4*5*6*7*8 and the second group should provide an estimated solution for the arithmetic problem 8*7*6*5*4*3*2*1. The first group estimated a result of 512 and the second group estimated a result of 2250.[21]

This example shows, that both groups used the first digit as their anchor. Hence the first group obtained a lower result than the second group. It evidences, that the final decision depends on the firstly set anchor, which in turn influences the decision.[22]

The described heuristics are explanations for the behavioural anomalies, which arise in the decision making process and which will be described in the following.

2.2. Behavioural Anomalies/Irrationalities

The human decision making process involves three stages, which are the information perception, information processing and decision making. In all of those three stages behavioural anomalies arise. These irrationalities will be described in the following.

2.2.1. Information Perception Anomalies

The information perception is the first stage of the decision making process. As humans have bounded information processing capacities, they try to filter the most important information already in this stage. Arising anomalies during the information perception are framing, risk sensitiveness, selective perception and adoption of authoritarian opinions. In order not to extrapolate the frame of this thesis, the focus will be laid only on the first three mentioned anomalies.[23] Framing Effect

Framing is the way how an information, situation or choice will be presented respectively framed, e.g. orally, in written, but also the sequence of the information and the environment where the information will be perceived.[24]

This anomaly influences the perception and hence the decision, i.e. leads to the result, that the same information will be differently perceived, evaluated and thus faulty allocated.[25]

This will be illustrated with reference to the Asian disease problem investigated by Tversky and Kahneman:

Scientists were preparing for the outbreak of an Asian disease, which was expected to hit the USA. Therefore they proposed two programs to reduce the number of affected victims. If the first program is accepted, 4,000 of the captioned 10,000 people will certainly be saved. If the second program is accepted, there is a 40 percent probability, that 10,000 will be saved and a 60 percent probability, that nobody will be saved. Most of the people surveyed selected the first program. Now these two options were presented in another way. If the first program is accepted, 6,000 of the captioned 10,000 people will certainly die. If the second program is accepted, there is a 40 percent probability, that nobody will die and a 60 percent probability, that 10,000 will die. Most of the people surveyed selected the second program.[26]

Whereby both presentations lead to the same result, most of the surveyed choose the first alternative in the first presentation, named winner’s perspective or survival frame and the second alternative in the second presentation, named loss perspective or mortality frame. The most overvalued secure values in the first presentation in a positive way, i.e. to safe life and in the second presentation in a negative way, i.e. to kill life. It also implies, that the most act risk avers in the first presentation and risk seeking in the second presentation. Risk Sensitiveness

Risk sensitiveness is human’s perception of dangers and evaluation of the risks or consequences involved, which are affected by human’s subjective understanding of the term risk. Human’s risk sensitiveness depends on quantitative (objective) and qualitative (subjective) factors, which lead to different perception and evaluation of risks and hence faulty decisions.[27]

Quantitative factors are the probability or the relative frequency of the risk occurrence and the amount or extend of damage. Risks, which are faced more often will be undervalued, e.g. car accidents whereas those, who are rarely faced, will be overvalued, e.g. accidents during go by train. The same phenomenon applies also to risks, which amount or extend of damage is high, e.g. flying. These risks will be overvalued whereas those with a minor damage, e.g. driving, will be undervalued.[28]

Qualitative factors are the characteristics of the risk source, the risk consequence and individuals. Characteristics of the risk source involve the geographical distance and the accountability and responsibility of the risk source. Risks, which are close to the risk source, e.g. handy radiation caused by a transmission mast, will be overvalued whereas those whose distance is bigger, will be undervalued. The same overvaluation occurs, if risks will be attributed to humans, e.g. Chernobyl whereas those who will be assigned to nature, e.g. natural disaster, will be undervalued.[29]

Characteristics of the risk consequence involve the below explained points:[30]

Congruity of risk and benefit allocation: Risks will be undervalued, if the benefits arise immediately, e.g. smoking whereas risks, whose benefits concern others, arise with time lag or are not traceable, will be overvalued, e.g. passive smoking.

Irreversibility of risk consequences: Risk consequences, which are reversible, e.g. property damages, will be undervalued whereas irreversible risk consequences, e.g. radiation contaminated people caused by a power plant explosion, will be overvalued.

Controllability of risks: Risks, which can be controlled, e.g. driving, will be undervalued as humans tend to overvalue their abilities especially of everyday usually practices. In contrast, uncontrollable risks, e.g. flying, epidemic plagues and nuclear waste, will be overvalued as humans have the feeling to be unable to control something whenever they rely on other humans or techniques.

Personal involvement: Risks will be overvalued, if someone directly or its environment is concerned with it. An investigation shows, that people, who become redundant or suffer a disease estimate the risk to become redundant and ill again higher than those who haven’t made experiences with unemployment or a disease.

Voluntariness of risk taking: Voluntary taken risks, e.g. smoking and driving, will be undervalued and much more accepted than risks, which will be involuntary taken, i.e. external imposed risks, like nuclear power plant and irradiation of food.

Risk awareness level: Risks, which will be daily faced and are well known, e.g. on the workplace, will be undervalued than those who are new und unknown.

Time delayed risk effects: Risks, whose effects occur with a time delay, like cancer by smokers, are subject to lower risk sensitiveness than those, whose consequences arise directly, e.g. death by car accident.

Individual-related characteristics involve human’s risk propensity. Risk seeking humans undervalue risks whereas risk averse humans overvalue them. Last individual-related traits are socio-demographic factors like the age. Young people indicate higher risk sensitiveness than old people.[31]

Aside of framing the risk sensitiveness will additionally be influenced by control illusion and optimism.[32]

This anomaly is linked to the next explained anomaly, named selective perception. Selective Perception

Selective perception is human’s tendency [33] to notice, filter and perceive only information, which corresponds to their own conceptions, hypotheses, actions and opinions. Contrary information will be eliminated, ignored or neglected. The reason for this behaviour is the cognitive dissonance. More in detail, humans seek for consistency and thus try to avoid the internal conflict, which arises, if they notice, that their conceptions, hypotheses, actions and opinions are inconsistent. Easily explained, it is a justification process,

which makes the misfit fit, in order to avoid the psychological pain. Hence selective perception serves as a protective shield for human’s psyche.[34]

This anomaly leads to an alleviated perception, due to which only information in context to the conceptions, hypotheses, actions and opinions are accepted while contradictory information are ignored. It also leads to confirmation bias, due to the unconsciously searching of information, which confirm the conceptions, hypotheses, actions and opinions. Moreover it results in selective bias, were contradictory information will be interpreted in a way, that they conform to the initial conceptions, hypotheses, actions and opinions. Also it leads to overhasty decisions, in order to avoid a justification pressure. Finally, it involves the adherence of prejudices too.[35]

This will be illustrated by the following example:

A smoker developed health problems, due to which his doctor advised him to stop smoking and handed out an information brochure for a rehabilitation to support his recovery. Upon reading the information, that smoking causes cancer the internal conflict arose, which he reduced by neglecting the information, that it causes cancer. Additionally he achieved internal harmony by searching for supporting information, which proved that he is right. In this case he stated, that his grandpa is a smoker aged 90 years and in good health. Another way is that he said, that smoking provides relaxation and that positive effects like that cannot promote health problems or cause cancer. Another method to which he applied to, was to tell, that cancer will only arise, when smoking too much.[36]

This example shows, that the smoker neglects, ignores and eliminates contradictory information, which in turn leads to biases in its risk perception.

2.2.2. Information Processing Anomalies

The information processing is the penultimate step of the decision making process. Affiliated irrational processes during the information perception are the reference point effect, mental accounting and loss aversion. Reference Point Effect

As already explained in 2.1.3., humans are geared to a subjective reference point respectively anchor. This reference point represents a part also in the information processing. In this sense the reference point is human’s subjective expectation. Consequences of an alternative, e.g. gains or losses will be not evaluated absolutely, but relatively to this reference point. More detailed, deviations close to the reference point will be evaluated higher than deviations, which are far apart from it.[37]

This result in the fact, that the same consequences, e.g. gains or losses will be differently evaluated, based on the distance to the individual set reference point, i.e. the difference between the actual situation and the expectation.[38]

This will be clarified by the following example:

Two women are visited a museum on a National Holiday. When woman A arrived at the museum she was told, that due to National Holiday the entrance fee is 6 Euro instead of the regular 10 Euro. Women B assumed, that due to the National Holiday the entrance would be for free. When she arrived at the museum she was told, that the entrance fee is 6 Euro. Whereas both cost situations are identical, women A sensed the price deduction as a gain of 4 Euro and women B as a loss of 6 Euro.[39]

This example shows, that the subjective reference point of both women – woman A 10 Euro and woman B 0 Euro – influences, if a consequence will be considered as a gain or a loss.

The reference point effect serves as basis to the following described anomalies, which are mental accounting and loss aversion. Mental Accounting

Mental accounting is a complex reducing mental process, which involves the categorization, codification and evaluation of alternatives respectively its consequences, as well as the way how they will be segregated or integrated. Easily explained, humans divide alternatives e.g. expenditures, incomes, months, and allocate them to different, not connected mental accounts, based on which they make their decisions. Each mental account involves a subjective reference point, as well as a cost and benefit side respectively loss and gain side. This mental process can be compared to the accounting of a company whereas companies create them according to the accounting rules. The way human’s create their mental accounts and segregate or integrate its sides is constituted by hedonic editing. Simplified said, it will be done in a way where they reach the most satisfaction, feel more convenient, maximize their benefits and is more attractive, i.e. avoids losses and cognitive dissonance.[40]

Mental accounting leads to different evaluations and thus suboptimal decisions, as consequences of an alternative will not be evaluated as a whole, but concentrated only on one account. Thereby dependences and interdependences to other mental accounts will be neglected.[41]


[1] Cp. Häcker, J. (2009), p. 83; Thaler, R.H. (1993), p. xvii.

[2] Cp. Häcker, J. (2009), p. 82; Nolte, D. (2009), p. 105; Piwinger, M. (2009), p. 24.

[3] Cp. Decker, M. (2009), p. 7.

[4] Cp. Fiala, J., Merten, H.-L. (2008), p. 34; Stanzel, M. (2007), p. 101.

[5] Cp. Fieseler, C., (2008); p. 117; Häcker, J. (2009), p. 87.

[6] Cp. Jedrowiak, J. (2008), p. 127; Kitzmann, A. (2009), p. 18; Rutkowski, L. (2008), p. 15; Ziegenbalg, B., Ziegenbalg, J., Ziegenbalg, O. (2007), p. 101.

[7] Cp. Noack, D. (2008), p. 18; Stanzel, M. (2007), p. 105.

[8] Cp. Greiner, M. (2008), p. 374; Gruß, C. (2008), p. 56.

[9] Cp. Unger, A., Unger, F., Raab, G. (2010), p. 129.

[10] Cp. Goldberg, J., Nitzsch, R. (2004), p. 51; Holtfort, T. (2009), p. 20; Riesenhuber, M. (2006), p. 144.

[11] Cp. Lisbach, B., Zacharopoulos, M. (2007), p. 36; Raab, G., Unger, F. (2005), p. 121; Schwarz, N.

(1997), p. 357; Titzkus, T. (2005), p. 87; Zuzak, M.T. (2008), p. 45.

[12] Cp. Schweiger, W. (2007), p. 144; Wunderle, S. (2006), p. 32.

[13] Cp. Raab, G., Unger, F. (2005), p. 122.

[14] Cp. Goldberg, J., Nitzsch, R. (2004), p. 72; Nitzsch, R., Stolz, O. (2006), p. 158-159; Reimann, M. (2005), p.81; Riesenhuber, M. (2006), p. 89. [15] Cp. Voigt, S. (2008), p. 28.

[16] Cp. Andrews, P.W., Haselton, M.G., Nettle, D. (2005), p. 727; Böhme, U. (2009), p. 5; Decker, M. (2009), p. 29-30; Imbacher, H., Jünemann, B. (2007), p. 46.

[17] Cp. Nitzsch, R. (2006), p. 28.

[18] Cp. Crupi, V., Hartmann, S. (2010), p. 91; Weber, J. (2008), p. 224.

[19] Cp. Schmeisser, W. (2010), p. 261; Zuzak, M.T.(2008), p. 46.

[20] Cp. Breuer, W., Gürtler, M., Schuhmacher, F. (2006), p. 259; Hirsch, B.(2007), p. 252.

[21] Cp. Decker, M. (2009), p. 31.

[22] Cp. Jeske, K.-J. (2008), p 75.

[23] Cp. Schmies, C. (2007), p. 170.

[24] Cp. Wahren, H.-K. (2009), p. 72.

[25] Cp. Schmies, C. (2007), p. 170.

[26] Cp. Grauwe, P., Grimaldi, M. (2006), p. 12; Kahneman, D., Tversky, A. (1981), p. 453-458, Steul, M. (2003), p. 70.

[27] Cp. Strohmeier, G. (2007), p. 32.

[28] Cp. Petermann, T., Revermann, C., Scherz, C. (2006), p. 140.

[29] Cp. Grunenberg, H, Heinrichs, H. (2009), p. 33; Günther, A., Haubl, R., Meyer, P., Stengel, M., Wüstner, K. (1998), p. 168; Wiedemann, P. (2010), p. 103.

[30] Cp. Anwander Phan-huy, S. (1998), p. 10; Bogun,, R. (2008), p. 129; Brandl, P.K. (2010), p. 88-89; Brühwiler, B. (1994), p. 70; König, W. (2010), p. 217; Mehl, F. (2001), p. 240; Schütz, H., Wiede- mann, P.M. (2005), p. 80.

[31] Cp. Müller-Reichart, M. (1994), p. 67-81; Wahren, H.-K. (2009), p. 99.

[32] Cp. Bergold, U., Mayer, B. (2005), p. 26; Schmidt, K. (2009), p. 541.

[33] Cp. Müller-Reichart, M. (1994), p. 89.

[34] Cp. Behrens, B. (2010), p. 78; Goldberg, J., Nitzsch, R. (2004), p. 210-211; Hermann, A. (2007), p. 166; Hofmann-Unger, K., Unger, C. (2007), p. 144; Michelis, D. (2009), p. 76; Schön, M. (2006), p. 42; Stanzel, M. (2007), p. 107.

[35] Cp. Egloff, B. (2002), p. 57; Jost, P-.J. (2008), p. 307; Junge, P. (2010), p. 118; Kottke, N. (2005), p. 66; Lehment, T., Krumbach-Mollenhauer, P. (2007), p. 82; Mieth, D. (2004), p. 91; Romppel, A. (2006), p. 239; Völker, R. (2008), p. 96.

[36] Cp. Hausmann, C. (2009), p. 91-92; Hornung, R., Lächler, J. (2006), p. 104-105; Schön, M. (2006), p. 18.

[37] Cp. Haas, A., Scheufele, B. (2008), p. 57; Wunderle, S. (2006), p. 43; Zayer, E. (2007), p. 67.

[38] Cp. Diller, H. (2008), p. 141; Greiner, M. (2008), p. 376.

[39] Cp. Lupert, P. (2010), p. 29.

[40] Cp. Kottke, N. (2005), p. 97; Nolte, D. (2009), p. 112.

[41] Cp. Schmeisser, W. (2001), p. 261; Werner, C. (2009), p. 26.


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Title: Capital Market Anomalies: Explained by human´s irrationality