Can the theory of Behavioral Finance depict the reality on stock markets and does it contribute to the progression in the Capital Market Theory?


Term Paper, 2015
28 Pages, Grade: 1,7

Excerpt

Table of Contents

List of Abbreviations

1 Introduction
1.1 Problem Description and Objectives
1.2 Scope of Work

2 Theoretical Background
2.1 Basic Assumptions of Neoclassical Capital Market Theory
2.2 Dissociation of Behavioral Finance as a Theory
2.2.1 AvailabilityHeuristic
2.2.2 Herding

3 Dot-com Bubble
3.1 Historical Background Information
3.2 Critical Analysis based on Neoclassical Capital Market Theory andBehavioral Finance

4 Conclusion
4.1 Target Achievements
4.2 Prospects

Bibliography

List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

1 Introduction

1.1 Problem Description and Objectives

The Portfolio Theory by Harry Markowitz, the Capital Asset Pricing Model by William Sharpe and the concept of the Homo Oeconomicus of Adam Smith – all of these models that are taught to business students and referred to by financial specialists all over the world are based on the assumption of the fundamental efficiency of markets. Market analysts build their substantial economic and financial predictions on the supposition that investors and corporations always behave and decide rationally. Consequently there would not be a chance that manias, panics or crashes ever occur. Nevertheless there were various speculation bubbles in the past such as the 1929 Stock-market-crash, the Dot-com bubble starting 1997 and the US-Subprime crisis as of 2007.[1]

So stock prices show fluctuations that cannot be only elucidated by economic factors. Moreover there are studies that come to the conclusion that there is only a low correlation between share prices and fundamental data.[2] Concomitant new research approaches deployed that either developed the existing models further or even created a complete paradigmatic change. Nowadays when it comes to explaining the occurrences on the stock markets the field of psychology and the behavioral science gain in relevance. However the following question arises: Can the theory of Behavioral Finance depict the reality on stock markets and its participants and does it make a contribution for the progression in the Capital Market Theory?

Yet there are some approaches that attempted to answer this question but there is no scientific consensus about it. Hence this term paper should accomplish a concise but fundamental contribution for the contemplation of this topic.

1.2 Scope of Work

At first the following chapter itemized the basic assumptions of the Neoclassical Capital Market Theory to the end that it can be dissociated with Behavioral Finance as a theory in chapter 2.2. To complete the theoretical background information of this term paper, the chapter will be concluded with the Availability Heuristic as well as the theory of herding.

The third chapter will deal with the Dot-com bubble including historical background information in the beginning. These key data serve the following chapter as an analysis base, which examines critically the special perceptions based on the Behavioral Finance Theory. On this basis the last chapter will explain conclusively the significance of Behavioral Finance for explanations of the stock market and economic movements around the world. An evaluation of the prospective importance of this theory as well as the meaning for markets in reality will build the conclusion of this term paper.

2 Theoretical Background

2.1 Basic Assumptions of Neoclassical Capital Market Theory

First mentioned by the economist and sociolist Thorstein Veblen in the late 19th century[3] and initially developed for a dissertation by Louis Bachelier in the year 1900, the term neoclassical economics was established in the 20th century.[4] It examines the correlation between capital acquirers and financiers in order to formulate statements about price structures and developments.[5] In1952 Harry Markowitz created the methodical foundations for the neoclassical age with his Modern Portfolio Theory that stated how a rational investor creates a perfect portfolio.[6] Since this model had some inconsistencies, further scientists found new approaches such as the Capital Asset Pricing Model by William Sharpe.[7]

All of the neoclassical theories deploy hypotheses that are based on the perfect competition that is illustrated by an axiomatic system[8] and they all have the same commonalities: The Homo Oeconomicus as a market participant who “makes perfectly rational decisions, applies unlimited procession power to any available information, and holds preferences well-described by standard expected utility theory”[9], builds the basic assumption of the neoclassical approach.[10] Furthermore the expectations of the investors are homogeneous and there is information efficiency which means that market participants all have the same access – timewise and pricewise – to information.[11] Another important proposition is that individual mistakes are balanced out on the market level.[12]

2.2 Dissociation of Behavioral Finance as a Theory

The theory of Behavioral Finance is quite new but an emergent field that combines behavioral and cognitive psychological theory with traditional finance and economics in order to find explanations for people’s individual or group-decisions on markets. So whenever there is a variance of behavior that is not led by a perfectly rational decision within the efficient market hypothesis, this theory can make a contribution towards gathering background information.[13] Richard Thaler, one of the best known theorists of the Behavioral Finance, defined the main proposition of the theory in 1993 as follows: “Behavioral finance is simply open-minded finance.… Sometimes in order to find a solution to an [financial] empirical puzzle it is necessary to entertain the possibility that some of the agents in the economy behave less than fully rational some of the time.“[14]

Altogether there are two leverage points that this theory is built on: First there are many results from laboratory experiments in the field of cognitive psychology, which approve situative irrational investor behavior[15] and second there are manifold empirical studies about the capital market that prove that commercial paper prices differ from neoclassical theories and that they do not integrate all information available.[16]

However it took some decades for this field to become a part of the mainstream finance as it is today. After the peak of the neoclassical approaches, as described in chapter 2.1, the behavioral economics started to gain impact within the economic science. While this field focused on psychological as well as scientific aspects, the Behavioral Finance, that was a progression of it in the 1980s, concentrated on emotional and cognitive factors.[17] The following decades various psychologists and other scientists began to investigate human decision making and experiences in economics. So Amos Tversky and Daniel Kahneman studied the heuristics and biases that influence decision making under uncertainty and they established the prospect theory which even made them win the Nobel Prize in 2002.[18] These were the first tracts dealing with the topic and they led ultimately to the fact that the American Finance Association held a session about Behavioral Finance in its annual meeting in 1985.[19] This was followed the same year by a paper about investors’ sensitivity to news published by DeBondt and Thaler, which raised even more doubts about the basic assumptions of neoclassical finance like the Efficient Market Hypothesis or the Capital Asset Pricing Model.[20] In the 21st century there is a large amount of publications available and research done about the field of behavioral finance, which has also arrived and is recognized in business schools all over the world.

2.2.1 Availability Heuristic

The term Availability Heuristic was introduced by the psychologists Tversky and Kahneman in 1973 in their paper “Availability: A heuristic for judging frequency and probability”.[21] Referring to these two theorists Baker and Nofsinger define availability as something that “causes probabilities to be assigned, based on how easily similar examples can be brought to mind”.[22] This implies that a person first compares the structure of an experience or an event to already existing moments it still has in mind. The better an event or situation can be remembered, the more likely or the more possible a person will judge it to happen again. Similarities, connotative distances or associative distance might be weighed during that process so that the feasibility that the same event structure will occur again, can be estimated. Furthermore there are factors that strengthen one’s memories which impacts that these experiences will be more available than others. This effect can for example be achieved by repetitiveness, due to happenings that are very likely or when an occurrence is very emotional or salient. The theory implies that the use of the Availability Heuristic, affected by these factors, will certainly lead to biases, which describes a preference of a particular way of thinking or acting in a certain situation.[23] This heuristic and biases have a cognitive source and therefore they can be improved by better resources.[24]

Although it should be considered that Tverskys’ and Kahnemanns’ studies are based on experiments that always had objectively correct answers which did not reflect real decisions in investors lives. Especially incidents such as speculation bubbles, like the Dot-com bubble that will be presented in chapter 3, are very unique and influenced by various factors so that it is impossible that the exact occurrence, including both identical input and output, will recur.[25] Nevertheless investors might assess one financial crisis by another and behave in a certain way that is not rational.

Actually there are some major factors that influence the decision making process of potential and entrenched market participants because the availability is limited. First of all there are some occurrences that cannot be compared to any other event. This leads to the fact that history is not pertinent for the assessment of the feasibility. People would then rather create a scenario in mind that links the past with the present. The more difficult this process is, the more unlikely an event will be judged. Furthermore most of the incidents are influenced by interrelated variables which are hard to understand for persons. As a consequence humans are imagining scenarios that do not have many variables since only the obvious factors are considered. This is very problematic when persons are situated in conflict situations because their own emotions and concepts are more accessible than others.[26] Also the market participant tends to interpret its behavior as a reflection of the surroundings whereas behaviors of other people are simply based on character attributes.[27] The next challenge is that once the person has a scenario in mind it might narrow future attitudes and cogitations. “Thus, the generation of a specific scenario may inhibit the emergence of other scenarios, particularly those that lead to different outcomes.”[28] The last factor that can distort availability is the coincidental confrontation caused by extraordinary occurrences or anxiety. This is valid for very worthwhile outputs such as high returns as well as unsolicited outcomes like a stock market crash or speculation bubble bursts.[29]

2.2.2 Herding

“When the market has an idea, I will join it. Some movements are that strong, that one will follow it although one knows better.”[30]
H. Reimer

This citation shows that social interactions and social conformity have effects on investor’s decisions and behavior. Especially herding is a term that has a high significance in behavioral finance today since it prevails as one of the main reasons for economic bubbles in history. It demonstrates an emotional origin of behavior.[31]

In 1895 the pioneer of the mass psychology Gustave Le Bon mentioned as one of the first scientists the “era of crowds”.[32] Established in the beginning of the 90s, the basis of this theory was described as an “informational effect of observing what other (possibly smarter) people do before you act […]”[33] that might go that far that investors imitate behavior or decisions that contradicts the own logic, information and expectation.[34] Nevertheless scientific literature mentions inconsistent definitions of herd behavior, therefore this papers’ analysis is based on the precedent explanation.

As previously described behavior that occurs in mass can have a tremendous impact on economic bubbles. Daxhammer and Facsar summarize Le Bon’s main assertions as follows: Masses develop a collective soul. This means that people are very attached to each other and consequently follow procedures of others. Second the interest of individual persons place back after the public interest. In fact people get emotionally infected by others. Also feelings are very simple which means that people react mainly impulsive and they are easily irritable. At last Le Bon states that opinion-forming transpires on a basis of some rumors and conjectures since opinions and rumors get blown up.[35] As chapter 3 will demonstrate and analyze, theses phenomenon of groups of individuals are often observed in economic crisis when investors suddenly react in panic and fear of further losses. The more market participants act in the same way, the more media will report it and the more other investors will do the same, which leads to a domino effect as well as a downward spiral. Welch tried to find evidence in his studies that investor behavior is based on recommendations. So he clustered analysts’ recommendations to buy, sell or hold a stock in a client’s portfolio and ascertained that the total allocation of recommendations shows no herding on average. To be more specific he classified the moment the specialists revise their references towards the omnipresent mass persuasion as herding behavior.[36]

Herding of either private or institutional investors as well as media representatives that recommend certain behavior can have different motivations as Graham states. As a first reason he mentions informational cascades that describe a behavior when investors follow the leading opinion of the mass. It is usually the case when the notion of the commonalty is very strong so that the single market participant has no chance to change its opinion. The next motive mentioned is herding due to reputational interest which stands for everything that occurs due to the fear of damaging their own distinction. Therefore people also forget about their own sources of information. Furthermore Graham depicts herding based on sources of information. This means that people tend to consume the media that they think everyone else is reading respectively watching etcetera. Herding due to historical market movements is the last factor mentioned in Grahams’ paper. This is a description for behavior that analyses historical movements combined with the assumption that other investors do the same in order to be able to predict future movements.[37]

3 Dot-com Bubble

3.1 Historical Background Information

There are many speculation bubbles documented in the last decades on the economic markets and they all have one thing in common: An enormous impact on the businesses of this world. The definition of a speculation bubble in general builds the foundation for the following example: “A bubble is created when market participants drive the security prices way above their fair price. During this phase people disregard the fundamental valuation and get attracted to such overpriced securities which strengthen the mispricing even more.”[38]

The last stock market bubble of the old century, also known as the “Dot-com bubble” or the “Internet bubble”[39], aroused from the increasing commercialization of the Internet starting in 1995. Companies that had a business in the Internet, telecommunication or information technologies industries were summarized as the so-called “New Economy”, whereas companies without that kind of focus in their business strategy were part of the “Old Economy”. The Dot-com bubble was characterized by countless start-up companies without promising business models that still had a high market valuation compared to well-tried companies with a sustainable profitability.[40]

Overall this speculation bubble can be divided into five stages. The first period started in the mid-nineties when the Internet was a customized mass communication medium for the general public. Market participants such as investors, banks and companies believed in the overwhelming earning power of the new distribution channel and became euphorically that a new era was created around them.[41]

The second stage was much influenced by the increasing medial reporting and social contagion about rising share prices. Another important catalyzer for the development of the bubble was the historical low interest rates[42], which led to a soaring investment activity of companies as well as venture capitalists.[43] More and more start-up companies that focused on the Internet expedite their initial public offerings and presented the prospect of colossal increases in turnover and positive future profits.[44]

In the third period the German bourse established the special trading segment “NEMAX” for new economy companies in 1997. Until March 2000 the new segment grew tremendously up to a total of 240 companies with a market capitalization of more than 216 billion euros and reached its all-time high with 8.546 points.[45] At the peak of the euphoria investors were absolutely delighted of equity issues with the result that the issued shares were oversubscribed multiple times.

The critical stage began in the spring of 2000 when investors’ suspiciousness of the recent evaluation of the companies led to the outburst of the speculative Dot-com bubble. The quarterly results of the former Internet start-ups revealed that the ambitious growth targets could never have been accomplished. Moreover many companies were at risk of illiquidity as a result of the increase of interest rates. Consequently investors lost their interest in further initial public offerings and the so far continuously increasing stock market began to fall.[46]

The last period of the bubble was characterized by deeply falling stock prices due to manipulated business numbers of several companies and the ongoing panic on the financial markets. By the end of 2002 the stock index NEMAX lost over 95 percent compared to its former all-time high record and the German bourse announced to close the market segment for companies of the new economy.[47] Today the TecDAX-Index represents the 30 largest and most liquid companies from the technology sector of the prime segment below the DAX and is regarded as the legal successor of the NEMAX.[48]

The same development can be determined in the United States where the NASDAQ lost nearly 80 percent of its value during the same time period until 2002. Furthermore over $7 trillion in market capitalization were destroyed back then.[49] The trust in the technology industry was deeply abused for many years and most of the start-up companies aroused in the euphoria of the New Economy were later driven out of the market. In these times, the central bank of the United States (FED) reacted to the collapse as they reduce the interest rates again to stimulate the economy. In this context the reaction of the FED set the origin for another speculative bubble – the housing crisis in the United States, which is considered as the trigger for the following global economic and financial crisis starting in 2007.[50]

3.2 Critical Analysis based on Neoclassical Capital Market Theory and Behavioral Finance

Taking the theoretical background described in the second chapter as a basis, this following chapter shortly analyses whether the basic assumptions of the Neoclassical Capital Market Theory can offer an explanatory approach of the illustrated Dot-com bubble or not. Afterwards it will concentrate on the paper`s key question to what extent the theory of Behavorial Finance depicts the speculative stock market bubble during the steep rise of New Economy companies.

As described in chapter 2.1 there are five commonalities characterizing all of the neoclassical theories based on various well-known economists. To begin with, the first statement that the Homo Oeconomicus as a market participant “makes perfectly rational decisions”[51] can be seen as disproved regarding the stock market development during the early stages of the Dot-com crises. For example at the peak of the progression of German technology shares in March 2000, the market capitalization of EM.TV – a former media and Internet marketer – was as high as the old industrial company Thyssen-Krupp. Both enterprise values amounted up to 14 billion euros although EM.TV offered a deal worse financial result with an annual turnover of 320 million euros and no profits. In comparison Thyssen-Krupp presented a turnover of over 32 billion euros and on top of that a dividend payment to investors of 370 million euros. Without having a sustainable business strategy, which could have justified the market valuation, the example of EM.TV illustrates the excessive euphoria and an irrational behaviour of investors regarding New Economy companies.[52] The British author Alex Preston visualized this investment mood with the following words: “The young companies did not need to be profitable, they barely needed to exist. A flashy cascading PowerPoint presentation was enough to make the suits reach for the wallets.”[53] Conclusive this example represents many different overpriced shares of New Economy businesses and investors that did not consider to prove either alternatives or background information to make a rational decision. This leads to the next analysis foundation – the utility theory and the unlimited power of investors to gather information.

Also stated in chapter 2.1 the Homo Oeconomicus is characterized as an investor who “applies unlimited procession power to any available information and holds preferences well-described by standard expected utility theory”.[54] With regard to the rising New Economy many examples questioned the functionality of the Neoclassical Theory. In the very early stages of the rising Dot-com bubble, predominantly after manipulated business numbers of many technological companies were revealed to the public, it was clear that market participants had a hard time accessing all information they needed. For example when people and media outlets found out that Comroad, a company for navigation systems, replicated most of its turnovers, the executive board was sentenced to imprisonment because of bankruptcy fraud and insider dealing.[55] Relating to a comparable “strategy” as well as to the fact that the company Enron also had to deal with these kinds of problems, “Enronitis” was named the ugliest word of the year 2002 for German stockbrokers. Starting with the collapse of the American company Enron that had to admit heavy mistakes in its balance sheet, “Enronitis” spread out as an epidemic of many other enterprises such as Worldcom or Quest. These incidents led to a radical intensification of American financial reporting laws today known as the “Sorbanes-Axley-Act”.[56] These instances indicate that potential and current investors did not even had a chance to use all necessary information in order to judge the shares correctly. Furthermore even if market participants had tried to accumulate as many information as they needed, they would not have gathered everything since they lived in the 21st century. To be precise, in 2002 when the Dot-com bubble was already present, there were many media channels people could use to get knowledge and information such as TV, print, radio or the Internet. This deluge of news led to a media selection through consumers and consequently to a narrow range in order to weigh contrary information. So an assessment of the cost-effectiveness in the interest of the expected utility hypothesis was basically not possible. Keynes put this statement in concrete terms and said that it is impossible for people to be completely informed of all possible occurrences in order to develop the expected utility to a maximum.

[...]


[1] Cf. Daxhammer, R.J., Facsar, M. (2012),p. 12.

[2] Cf. eg. Roll, R. (1988), pp. 541-566; Shiller, R.J. (1981), pp. 421-436.

[3] Cf. Veblen Institute (2015), web.

[4] Cf. Daxhammer, R.J., Facsar, M. (2012), p. 17f..

[5] Cf. Rudolph, B. (1993), p. 2113.

[6] Cf. Markowitz, H. (1952), p. 77-91; Markowitz, H. (2008), p. all.

[7] Cf. Gräfer, H., Schiller, B., Rösner, S. (2006), p. 261.

[8] Cf. Steiner, M., Bruns, C. (2007), p. 21.

[9] Baker, H.K., Nofsinger, J.R (2010), p. 23.

[10] Cf. Daxhammer, R.J., Facsar, M. (2012), p. 17f.

[11] Cf. Bamberg, G., Coenenberg, A. (2004), p. 81ff.

[12] Cf. Garz, H., Günther, S., Moriabadi, D. (2006), p. 45 f.

[13] Cf. Baker, H.K., Nofsinger, J.R (2010), p. 3.

[14] Thaler, R.H. (1993), p. xvii.

[15] Cf. Anderson, J. (1996), p. 15.

[16] Cf. Chan, W., Frankel, R., Kothari, S. (2004), pp. 3-50.

[17] Cf. Daxhammer, R.J., Facsar, M. (2012),p. 20.

[18] Cf. Schriek, R. (2009), p. 26f.

[19] Cf. Shefrin, H. (2002), p. 295.

[20] Cf. DeBondt, W., Thaler, R. (1985), p. 793-805.

[21] Cf. Tversky, A., Kahnemann, D. (1973), pp. 163-178.

[22] Cf.Baker, H.K., Nofsinger, J.R (2010), p. 121.

[23] Cf.Tversky, A., Kahnemann, D. (1973), p. 163f.

[24] Cf. Daxhammer, R.J., Facsar, M. (2012),p. 194.

[25] Cf. Tversky, A., Kahnemann, D. (1973), p. 167.

[26] Cf.Tversky, A., Kahnemann, D. (1973), p. 177.

[27] Cf.Jones,E., Nisbett, R. (1971), p. 80.

[28] Tversky, A., Kahnemann, D. (1973), p. 177.

[29] Cf. Tversky, A., Kahnemann, D. (1973), p. 177.

[30] Reimer, H. (1997), p.135. Translation from original source: „Wenn der Markt eine Idee hat, mache ich mit. Manche Bewegungen sind so stark, dass man sich auch wider besseren Wissens dranhängt.“

[31] Cf. Daxhammer, R.J., Facsar, M. (2012),p. 194.

[32] Cf. Forbes, W. (2009), p. 233.

[33] Cf. Forbes, W. (2009), p. 228.

[34] Cf. Forbes, W. (2009), p. 228.

[35] Cf. Daxhammer, R.J., Facsar, M. (2012),p. 98.

[36] Cf. Welch, I. (2000), pp. 369-396.

[37] Cf. Graham, B. (1999), p. 239 ff.

[38] Prosad, J., Kapoor, S., Sengupta, J.(2015),p.6.

[39] Cf. Galbraith, Hale (2004), p.6

[40] Cf. Daxhammer,R., Facsar, M. (2012), p. 136.

[41] Cf. Guttmann, R. (2009), p. 54.

[42] The Fed Fund Rate was 1995 at 3 percent.

[43] Cf. Global Rates (2015), web.

[44] Cf. Daxhammer,R., Facsar, M. (2012), p. 136.

[45] Cf. Krafft, L. (2006), p. 168. The foundation was 1.000 points.

[46] Cf. Daxhammer, R., Facsar, M. (2012), p. 138.

[47] Cf. Krafft, L. (2006), p. 169.

[48] Cf. Deutsche Börse AG (2015), web.

[49] Cf. Gray, Frieder, Clark (2007), p.885

[50] Cf. Daxhammer, R., Facsar, M. (2012), p. 139.

[51] Cf. Baker, H.K, Bruns, C. (2007), p. 21.

[52] Cf. Daxhammer, R., Facsar, M. (2012), p. 137.

[53] Preston, A. (2011), p. 19.

[54] Baker, H.K, Bruns, C. (2007), p. 21.

[55] Cf. Daxhammer,R., Facsar, M. (2012), p. 139.

[56] Cf. Glebe, D. (2008), p.110.

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Title
Can the theory of Behavioral Finance depict the reality on stock markets and does it contribute to the progression in the Capital Market Theory?
College
University of Applied Sciences Essen
Grade
1,7
Authors
Year
2015
Pages
28
Catalog Number
V384956
ISBN (eBook)
9783668597334
ISBN (Book)
9783668597341
File size
477 KB
Language
English
Tags
behavioral, finance, capital, market, theory
Quote paper
Stephan Hoppe (Author)Carina Anna Schebitz (Author), 2015, Can the theory of Behavioral Finance depict the reality on stock markets and does it contribute to the progression in the Capital Market Theory?, Munich, GRIN Verlag, https://www.grin.com/document/384956

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