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The efficient markets hypothesis
Much of modern investment theory and practice is predicated on the Efficient Markets Hypothesis (EMH), the assumption that markets fully and instantaneously integrate all available information into market prices. Underlying this comprehensive idea is the assumption that the market participants are perfectly rational, and always act in self-interest, making optimal decisions. These assumptions have been challenged. It is difficult to tip over the Neo classical convention that has yielded such insights as portfolio optimization, the “Capital Asset Pricing Model”, the “Arbitrage Pricing Theory”, the “Cox Ingersoll-Ross theory” of the term structure of interest rates, and the “Black-S[choles/Merton option pricing model”, all of which are predicated on the EMH (Efficient Market Hypothesis) in one way or another. At few points the EMH criticizes the existing literature of behavioral finance, which shows the difference of opinion on psychology & economics. The field of psychology has its roots in empirical observation, controlled experimentation, and clinical applications. According to psychology, behavior is the main entity of study, and only after controlled experimental dimensions do psychologists attempt to make inferences about the origins of such behavior. On the contrary, economists typically derive behavior axiomatically from simple principles such as expected utility maximization, making it easier for us to predict economic behavior that are routinely refuted empirically
The biggest threats to Modern Portfolio theory is the theory of Behavioral Finance. It is an analysis of why investors make irrational decisions with respect to their money, normal distribution of expected returns generally appears to be invalid and also that the investors support upside risks rather than downside risks. The theory of Behavioral finance is opposite to the traditional theory of Finance which deals with human emotions, sentiments, conditions, biases on collective as well as individual basis. Behavior finance theory is helpful in explaining the past practices of investors and also to determine the future of investors.
Behavioral finance is a concept of finance which deals with finances incorporating findings from psychology & sociology. It is reviewed that behavioral finance is generally based on individual behavior or on the implication for financial market outcomes. There are many models explaining behavioral finance that explains investor's behavior or market irregularities where the rational models fail to provide adequate information. We do not expect such a research to provide a method to make lots of money from the inefficient financial market very fast.
Behavioral finance has basically emerged from the theories of psychology, sociology and anthropology the implications of these theories appear to be significant for the efficient market hypothesis, that is based on the positive notion that people behave rationally, maximize their utility and are able to prices observation, a number of anomalies (irregularities) have appeared, which in turn suggest that in the efficient market the principle of rational behavior is not always correct. So, the idea of analyzing other model of human behavior has came up.
Further (Gervais, 2001) explained the concept where he says that People like to relate to the stock market as a person having different moods, it can be bad-tempered or high-spirited, it can overreact one day and make amends the next. As we know that human behavior is unpredictable and it behaves differently in different situations. Lately many researchers have suggested the idea that psychological analysis of investors may be very helpful in understanding the financial markets better. To do so it is important to understand the behavioral finance presenting the concept that Investors are not as rational as traditional theory has assumed, and biases in their decision-making can have a cumulative effect on asset prices. To many researchers behavioral finance is a revolution, transforming how people see the markets and what influences prices. "The paradigm is shifting. People are continuing to walk across the border from the traditional to the behavioral camp”. (Gervais, 2001, P.2). On the contrary some people believe that may be its too early call it a revolution. Eugene Fama( Gervais, 2001) argued that Behavioral finance has not really shown impacts on the world prices, and the models contradict each other on different point of times. He gave little credit to behaviorist explanations of trends and "anomalies"(any occurrence or object that is strange, unusual, or unique) arguing that data-mining techniques make it possible to locate patterns.
Other researchers have also criticized the idea that the behavioral finance models tend to replace the traditional models of market functions. The weaknesses in this area, explained by him (Gervais, 2001) are that generally the market behavior displayed is attributed to overreaction and sometimes to under reaction. Where People take the behavior that seems to be easy for the particular study regardless of the fact that whether these biases are the result of underlying economic forces or not. Secondly, Lack of trained and expert people. The field does not have enough trained professionals both academic psychology and traditional finance and so the models that are being put up together are improvised.
David Hirshleifer (Gervais, 2001) focuses on the individual behavior influencing asset prices, suggesting that behavioral finance is in its developmental stage and not yet a mature one, there's a lot of disagreement but productive one. Hirshleifer agrees that applying behavioral-finance concepts to corporate finance can pay off. If managers are imperfectly rational, he says, perhaps they are not evaluating investments correctly. They may make bad choices in their capital-structure decisions. Few people realistically think behavioral finance will displace efficient-markets theory. On the other hand, the idea that investors and managers are not uniformly rational makes insightful sense to many people.
Traditional Finance & Empirical Evidence:
“Traditional theory assumes that agents are rational & the law of one price holds” that is a perfect scenario. Where the law of “One price” states that securities with the same pay off have same price, but in real world this law is violated when people purchase securities in one market for immediate resale in another, in search of higher profits because of price differentials known as “Arbitrageurs”. And the agents rationality explains the behavior of investor “Professional & Individual” which is generally inconsistent with the rationality or the future predictions. If a market achieves a perfect scenario where agents are rational & law of one price holds then the market is efficient.
With the availability of amount of information, the form of market changes. It is unlikely that market prices contain all private information. The presence of “noise traders” (traders, trading randomly & not based on information).
Researches show that stock returns are typically unpredictable based on past returns where as future returns are predictable to some extent. Few examples from the past literature explains the problem of irrationality which occurs because of naïve diversification, behavior influenced by framing, the tendency of investors of committing systematic errors while evaluating public information.(Glaser et al, 2003)
Recent studies suggest that peoples` attitude towards the riskiness of a stock in future & the individual interpretation may explain the higher level trading volume, which itself is a vast topic for insight. A problem of perception exist in the investors that Stocks have a higher risk adjusted returns than bonds. Another issue with the investors is that these investors either care about the whole stock portfolio or just about the value of each single security in their portfolio and thus ignore the correlations.
The concept of ownership society has been promoted in the recent years where people can take better care of their own lives and be better citizen too if they are both owner of financial assets and homeowners. As a researcher suggested that in order to improve the lives of less advantaged in our society is to teach them how to be capitalist, In order to put the ownership society in its right perspective, behavioral finance is needed to be understood. The ownership society seems very attractive when people appear to make profits from their investments. Behavioral finance also is very helpful in understanding justifying government involvement in the investing decisions of individuals. The failure of millions of people to save properly for their future is also a core problem of behavioral finance. (Shiller, 2006)
According to (Glaser et al, 2003) there are two approaches towards Behavioral Finance, where both tend to have same goals. The goals tend to explain observed prices, Market trading Volume & Last but not the least is the individual behavior better than traditional finance models.
- Belief - Based Model: Psychology (Individual Behavior) Incorporates into Model Market prices & Transaction Volume. It includes findings such as Overconfidence, Biased Self- Attrition, and Conservatism & Representativeness.
- Preference Based Model: Rational Friction or from psychology Find explanations, Market detects irregularities & individual behavior. It incorporates Prospect Theory, House money effect & other forms of mental accounting.
Behavioral Finance and Rational debate:
The article by (Heaton and Rosenberg,2004) highlights the debate between the rational and behavioral model over testability and predictive success. And we find that neither of them actually offers either of these measures of success. The rational approach uses a particular type of rationalization methodology; which goes on to form the basis of behavior finance predictions. A closer look into the rational finance model goes on to show that it employs ex post rationalizations of observed price behaviours. This allows them greater flexibility when offering explanations for economic anomalies. On the other hand the behavior paradigm criticizes rationalizations as having no concrete role in predicting prices accurately, that utility functions, information sets and transaction costs cannot be ‘rationalized'. Ironically they also reject the rational finance's explanatory power which plays an essential role in the limits of arbitrage, which actually makes behavioral finance possible.
Milton Friedman's theory lays the basis of positive economics. His methodology focuses on how to make a particular prediction; it is irrelevant whether a particular assumption is rational or irrational. According to this methodology, the rational finance model relies on a limited “assumption space' since all assumptions that are supposedly not rational have been eliminated. This is one of the major reasons behind the little success in rational finance predictions. Despite the minimal results, adherents of this model have criticized the behavioral model as lacking quantifiable predictions that are based on mathematical models. Rational finance has targeted a more important aspect in the structure of the economy, i.e. investor uncertainty, which further cause financial anomalies. In explaining these assertions, the behavioural emphasises the importance of taking limits in arbitrage.
Friedman's methodological approach falls into the category ‘instrumentalism', which basically states that theories are tools for predictions and used to draw inferences. Whether an assumption is realistic or rational is of no value to an instrumentalist. By narrowing what may or may not be possible, one will inevitably eliminate certain strategies or behaviors which might in fact go on to maximize utility or profits based on their uniqueness. An assumption could be irrational even in the long run, but it is continuously revised and refined to make it into something useful.
In opposition to this, many individuals have gone on to say that behaviouralists are not bound by any constraints thus making their explanations systematically irrational. Rubinstein (2001) described how when everyone fails to explain a particular anomaly, suddenly a behavioral aspect to it will come up, because that can be based on completely abstract irrational assumptions. To support rationality, Rubinstein came up with two arguments. Firstly he went on to say that an irrational strategy that is profitable, will only attract copy cat firms or traders into the market. This is supported when a closer look is given towards limits to arbitrage. Secondly through the process of evolution, irrational decisions will eventually be eliminated in the long run. The major achievements characterized of the rational finance paradigm consist of the following: the principle of no arbitrage; market efficiency, the net present value decision rule, derivatives valuation techniques; Markowitz's (1952) mean-variance framework; event studies; multifactor models such as the APT, ICAPM, and the Consumption- CAPM. Despite the number of top achievements that supporters of the rational model claim, the paradigm fails to answer some of the most basic financial economic questions such as ‘What is the cost of capital for this firm?' or ‘What is it's optimal capital structure?'; simply because of their self imposed constraints.
So far this makes it seem like rational finance and behavioral finance are mutually exclusive. Contrary to this, they are actually interdependent, and overlap in several areas. Take for instance the concept of mispricing when there is no arbitrage. Behavior finance on the other hand suggests that this may not be the case; irrational assumptions in the market will still lead to mispricing. Further even though certain arbitrageurs may be able to identify irrationality induced mispricing, because of the imperfect market information, they are unable to convince investors of its existence. Over here, the rational model is accepting the existence of anomalies which are affected both through the factors of risk and chance; therefore coinciding with the perspective of behavioral finance. Two instances are clear examples of how rationalization is an important limit of arbitrage: i) the build-up and blow-up of the internet bubble; and ii) the superiority of value equity strategies.
If we focus on the latter, we are able to see behavioral finance literature that highlights the superiority of such strategies in the ability of analysts to extrapolate results for investors. This is possible when rationalization is taken as a limit to arbitrage. Similarly these strategies may also limit arbitrage against mispricing, through the great risk associated with stocks. In explaining most anomalies it is essential that analysts first conclude whether pricing is rational or not. To prove their hypothesis that irrationality-induced mispricing exists, behaviouralists may find it easier if they accepted the role of rationalization in limits of arbitrage. Slow information diffusion and short-sales constraints are other factors that explain mispricing. However these factors alone cannot form the basis of a strong and concrete explanation that will clarify pricing across firms and also across time.
Those supporting the rational paradigm attack behavioral finance adherents in that their predictions for the financial market have been made on irrational assumptions; that are not supported by concrete mathematical or scientific models. In their view the lack of concrete discipline in the methodology adopted in behavior finance leads to the lack of testing in their forecasts. On the other hand the rational model is criticized for its lack of success in financial predictions. The behaviouralists claim that this limitation exists because the supporters of rational finance dismiss aspects of the economic market simply because it may not fall into explainable rational behavior. Both perspectives claim to align themselves with respect to the goals of ‘testability' and ‘predictions', while at the same time continue to offer evidence against the other model. In reality however, rather than being exclusively mutual both paradigms assist one another in making their predictions.
A cognitive bias is a person's tendency to make errors, based on cognitive factors. Forms of cognitive bias include errors in statistical judgment, social attribution, and memory that are common to all human beings. (Crowell, 1994, p. 1) “Cognitive bias is the tendency of intelligent, well-informed people to consistently do the wrong thing”. The reason behind this cognitive bias is that the Human brain is made for interpersonal relationships' and not for processing statistics.
The paper discusses facility of forecasts. Generally it is said that the world is divided into two groups. One who forecasts positively and one negatively. These forecasts exaggerate the reliability of their forecasts and trace it to the “illusion of validity” which exists even when the illusionary character is recognized. (Fisher and Statman, 2000) discussed five cognitive bias, underlying the illusion of validity that are Overconfidence, Confirmation, Representativeness, Anchoring, and Hindsight
(Shiller, 2002) discusses, that irrational behavior may disappear with more learning and a much more structured situation. As the past research proves it that may of cognitive biases in human judgment value uncertainty will change, they may be convinced if given proper instructions, on the part-experience of irrational behavior. There are three main themes in behavioral finance and economics
Heuristics: People often make decisions based on approximate rules of thumb, not strictly rational analysis. See also cognitive biases and bounded rationality.
- Prospect theory
- Loss aversion
- Status quo bias
- Gambler's fallacy
- Self-serving bias
- Money illusion
Framing: The way a problem or decision is presented to the decision maker will affect their action.
- Cognitive framing
- Mental accounting
Market inefficiencies: There are explanations for observed market outcomes that are contrary to rational expectations and market efficiency. These include mis-pricings, non-rational decision making, and return anomalies. Richard Thaler, in particular, has described specific market anomalies from a behavioral perspective.
Anomalies (economic behavior)
- Disposition effect Endowment effect
- Inequity aversion Intertemporal consumption
- Present-biased preferences Momentum investing
- Greed and fear Herd behavior
Anomalies (market prices and returns)
- Equity premium puzzle Efficiency wage hypothesis
- Limits to arbitrage Dividend puzzle
Models in behavioral economics are typically addressed to a particular observed market anomaly and adjust standard neo-classical models by describing decision makers as using heuristics and being affected by framing effects. In general, economics sits within the neoclassical framework, though the standard assumption of rational behavior is often challenged.
Loix et. Al in their paper “Orientation towards Finances” explains the individual financial management behavior, people dealing with their financial means. They have analyzed the Non-specific Financial behavior as already we see extensive research on the specific finance behavior such as saving, Taxation, Gambling, amassing debt. But they had given a lot of importance to stock market, investors and households. The analysis of general public`s behavior was done, where an ordinary man is not sure and simply act according to the guesses over their money related issues. It was also found that people interested in economic and financial matters are much more active in collecting specific information than general public, stating that financial behavior of household is an important relevant topic that needs to be discussed in much more details. Household financial management is similar to the financial management. The construct of orientation towards finances was developed where the individual ORTO FIN focuses on competencies (interest and skills). Having stronger money attitude is an indication of stronger orientation towards finances and much more effective competencies. Therefore we expect some relevance and similarity between corporate and household management behavior as both require organizing, forecasting, planning and control.
(Loix et. al, 2005) analyzed general public's behavior in basically dividing them into two groups, Financial Information & Personal financial planning. Also explaining some practical and theoretical gaps in the area of psychology of money usage, they concluded that ORTOFIN (Orientation towards finance) indicates the involvement of individuals in managing their finances. Proving out the point that active interest in financial information and an urge to plan expenses are two main factors. A stronger ORTFIN indicates: Greater use of debit accounts, Higher savings account, Wide variety of investments, Greater awareness of one's financial Intimate knowledge of the details of Ones savings/deposit accounts obsessed by money, Higher achievement and power in monetary terms, Further age is also inversely proportional.
Shiller in 2006, in his article talked about the the co-evolution of neo-classical and behavior finance. In 1937 when A. Samuelsson one of the great economists wrote about people maximizing the present value of utility subject to a present vale - budget constraint. Another judgment he realized was time being consistent human behavior where if at any time t
0 < t < b
Where people reconsidered the problem of maximization from that date forward, they would not change their decision where as in real life it is totally opposite for example people sometimes try to control themselves by binding their future decision as from history we find out that that some of man make irrevocable trust in the taking out of life insurance as a compulsory savings measure. (shiller, 2006, p.) Considering personal saving rate, saving and down for no reason has emerged as a weakness of human self control. People seem to be vulnerable to complacency from time to time about providing for their own future.
The distinction between neoclassical and behavioral finance have therefore been exaggerated. Both of them are not completely different from each other. Behavioral finance is more elastic willing to learn from other sciences and less concerned about the elegance of models whereby explaining human behavior
Investing and cognitive bias:
Money Managers & Money management is a very popular phenomenon. The performance in the stock market is measured at the daily basis and not to wait for a highly subjective annual review of one's performance by one's superior. Market grades you on a daily basis. The smarter one is, the more confident one becomes of one's ability to succeed, clients support them by trusting them that eventually helps their careers. But the truth is that few money managers put in sufficient amount of time and effort to figure out what works and develop a set of investment principles to guide their investment decisions (Browne, 2000). Further Browne discussed the importance of asset allocation and risk aversion, in order to understand why we do what we do regardless of whether it is rational or not. General public opts for money Managers to deal with their finances and these managers are categorized in three ways: Value Managers, Growth Managers and Market Neutral Managers. The vast majority of money managers are categorized as either value managers or growth managers although a third category, market neutral managers, is gaining popularity these days and may soon rival the so-called strategies of value and growth. Some investment management firms even are being cautious by offering all styles of investments. What too few money managers do is analyze the fundamental financial characteristics of portfolios that produce long-term market beating results, and develop a set of investment principles that are based on those findings. Difference of opinion on the definition of Value is the problem.The reasons for this are two-fold, one being the practical reality of managing large sums of money, and the other related to behavior. As the assets under management of an advisor grow, the universe of potential stocks shrinks
Analyzing that why individual and professional investors do not change their behavior even when they face empirical evidence, that suggests that their decisions are less than optimal. An answer to this question is said to be that being a contrarian may simply be too risky for the average individual or professional. If a person is wrong on the collective basis, where everyone else also had made a mistake, the consequences professionally and for one's own self-esteem are far less than if a person is wrong alone. The herd instinct allows for the comfort of safety in numbers. The other reason is that individuals try to behave the same way and do not tend to change courses of action if they are happy. If the results are not too painful individuals can be happy with sub-optimal results. Moreover, individuals who tend to be unhappy make changes often and eventually end up being just as unhappy in their new circumstances.
According to the traditional view of Investment management, fundamental forces drive markets, however many other investment firms considers to be active and working out based on their experienced Judgment. It is also believed that Judgmental overrides of Value & Fundamental forces of markets can be lethal as well as a cause of Financial Disappointment. From the history it has been found that people Override at the wrong times and in most cases would be better off sticking to their investment disciplines (Crowell, 1994) and the reason to this behavior is the Cognitive bias. According to many researchers, stocks of small companies with low price/book ratios provide excess returns. Therefore, given a choice among small cheap stocks & large high priced stocks, prominent investors (financial analysts, senior company executives and company directors) will certainly prefer the small cheap ones. But the fact is opposite to this situation where these prominent investors would opt for large high priced ones and so suffer from cognitive bias and further regret. According to a survey in 1992/1993, a research was carried out that included senior executives & directors where they were suppose to rate companies in their industries on eight factors: Quality of management, Quality of products & services, Innovativeness, Long term investment value, Financial soundness, Ability to attract, develop and keep talented people, Responsibility to the community and environment, Wise use of corporate assets.
The assumptions that we made were that that “Long term investment value should be negatively correlated with size since small stocks provide superior returns. Long term Investment value should have a negative correlation with Price/book since low Price/Book stocks provide superior returns”.(Crowell, 1994).
Whereas the results of the survey were contrary that stated that Long Term Investment had a positive correlation with the size and also that the Long term investment value had a positive correlation with the Price/Book stocks. According to Shefrin and statman, prominent investors overestimate the probability that a good company is a good stock, relying on the representative heuristics, concluding that superior companies make superior stocks. Aversion to Regret: aversion to regret is different from aversion to risk, Regret is acute when the individual must take responsibility for the final outcome. Aversion to regret leads to a preference for stocks of good companies. The choice of the stocks of bad companies involves more personal responsibility and higher probability of regret. Therefore, we find there are two major Cognitive errors:
“We have a double cognitive error: a Good company make good stocks (representativeness), and involves less responsibility(Less aversion to regret” (Crowell, 1994,p.3)
The Anti Cognitive bias actions would be admitting to your owned stocks, admitting earlier investment mistakes. Further Taking the responsibility for the actions to improve their performance in the future. The reasons for all the available disciplines, tools, and quantitative techniques is to deal with the Cognitive bias error, where the quantitative investment techniques enables the investment managers to overcome cognitive bias, follow sound investment, and eventually be successful contrarian investor(one who rejects the majority opinion, as in economic matters).
Behavioral finance also is very helpful in understanding justifying government involvement in the investing decisions of individuals. The failure of millions of people to save properly for their future is also a core problem of behavioral finance. With the help of two very important examples Shiller explains how Government involvement can influence financial investments of individuals.
In April 2005 “Tony Blair” stated a program when all new born babies were given a birthday present of 250 to 500. The present were to choose among a number of investment alternatives to invest until child comes of age. This is an effect done in order to make the parents feel connected with investments and modern economy.
Another example: as it is said that people should be heavily active in stock market when they are young and so generally should reduce the activity with age. According to the conventional rule people should have
100 - Age = % age of investment
In 2005 president bush also portfolio announced one such plan for personal account “life - cycle fund” which would be among the option that works will be offered to invest their personal account. It was A centerpiece of the president's proposal bur a major point to be noticed was the default option.
An important aspect of behavioral finance is the human attention is capricious focuses heavily tat same times on financial calculations and are subject to distraction and dissipation of default option is central. All this brings us a question that what should an intertemporal optimizer do to manage his portfolio over the lifetime. According to Samuelson someone who wished to maximize the expected value of his intertemporal utility function by managing the allocation of the portfolio between a high yielding asset and less yielding asset would not actually change the allocation through time. Neoclassic finance appears highly relevant to such a discussion in that it offers the appropriate theoretical framework for considering what people ought to do with the portfolio if not what they actually do. Behavioral is beginning to play an important role in public policy such as in social
Global culture Culture & Social Contagion:
The selective attention exhibited by a human mind is the concept of culture. Every nation, tribe or asocial group has a social cognition reinforced by conversation ritual and symbols, rituals and supposition of a particular nation has a subtle but far reliability affect on human behavior. Some researchers found that the unique customs of people actually arise as a logical consequence of a belief system of a nation group of people. Cultural factor were found to have great influence on rational or irrational behavior. We find many factors that are same across countries , e.g fashion, music, movies, youthful rebellious, other than these we find more factors in producing internationally- similar human behaviors then just rational reactions. Therefore it is a difficult job to decide in what avenues global culture exerts its influence. (Shiller, 2002)
(Sandroni, 2004) wrote an article on the efficiency of markets and the Bayesian rule where he presents a long standing assumption, where two possible situations have been clearly examined. Relaxing the assumptions that agents form beliefs according to the laws of probability & Assume a simple heuristic and also that agents process information according to the Bayes Rule, but are lack of sufficient information in order to generate the true data process. He found out reasons for these anomalies, where there were two vital factors, first Possibility that agents do not process information according to the Bayes Rule and so eventually suffer from cognitive bias in forming beliefs and second Possibility that agents process the information according to the Bayes Rule but do not have sufficient amount of information about the structure of the economy to hold correct beliefs.
According to the Behavioral finance literature agents beliefs are assumed to be much closer to the experimental market than theoretical laws. But it has many people's criticism attached to it as well:
- This approach allows for any belief and essentially explains any behavior.
- Agents should use existing data to form any rational expectations.
- The most crucial one states that each agent does not impact prices equally.
As the traditional efficient market hypothesis states: that “agents who do not predict as accurately as others will be unable to accumulate sufficient wealth and will be driven out of market”.
However, it has not been proven yet that agents who process information according to Bayes Rule accumulate more wealth at the expense of those who do process the information according to the laws of probability. Past Researches provides us with two more important factors of market selection that are Correct/Incorrect beliefs. as it is said “That agents with correct beliefs drive the agents with incorrect belief out of the market”. In order to better understand the situation we must compare the two scenarios where One agents process information according to the Bayes rule (Bayesian Paradigm) and Second, agents who use behavioral rules to update beliefs(Non-Bayesian Behavioral Models).
Sandroni further classifies the fundamental structure of the assets into two groups, Learnable: When the available data reveals the true probability of the dividends with near certainty (History becomes the perfect guide) &Unlearnable: When the available data cannot reveal the true probability of the dividends, here the history can never be a perfect Guide. When the fundamental structure of the asset is Learnable, the Bayesian agents will learn and survive, where as Some Non Bayesian may learn and some may fail to do so. Agents who are slow in their learning process, or do not learn are eventually driven out of the market, whereas Some Non Bayesian agents who learn as quickly as Bayesian agents would learn and survive. According to sandroni it is near to impossible to drive a Bayesian agent away of the market because Bayesian agents will always find a way to stay in the market and influence prices. The facts explain the situation where Agents with belief based on inconsistent estimators are driven out of the market(agents failing to understand the fundamental structure of the asset vanish and so asset prices are eventually determined by agents rational expectations. Overconfident & One parameter Non economical Agents survive( where agents forecasts arbitrarily close to the forecasts of the Bayesian agents & survive, and non parsimonious agents starts with an incorrect model of the fundamental structure of asset, but the massive amount of information overrules the initial disadvantage & permits their survival). One Dimension Non Parsimonious Agents are driven out of the Market ( These will eventually learn the true parameters but they will vanish from the economy.
When the fundamental structure of asset is Unlearnable, Bayesian agents would survive whereas Non Bayesian would be driven out of the market. Therefore, in both markets assets are priced under the Bayesian paradigm, and so financial anomalies driven by cognitive biases can only persevere if Behavioral agents keep entering the economy, bring sufficient wealth from. Sandroni further investigates that who will actually survive when the Bayesian and Non Bayesian agents learn to forecast correctly, and presents evidence that Bayesian agent will drive Non Bayesian agents out of the Market. Expressions like cognitive bias, over & under reaction, overconfidence were used to distinguish Non Bayesian estimators from the Bayesian benchmark. And agents in this study traded for speculative reasons, holding different beliefs, Traded for risk sharing reasons, having different preferences over risk. Agents without wealth do not influence prices. All Bayesian agents are driven out of the market by Non Bayesian agents: Following that agents whose beliefs are based on estimators of good predictability, are driven out of the market when they do not forecast arbitrarily close to the Bayesian paradigm, this difference produces a persistent tendency of driving Non Bayesian agents out of the Market.
Self is never neutral: Why economic Agents Behave Irrationally
In 2005 Gao and Schmidt discussed the same concept of agents rationality. According to him it was a very common mistake of agents being always rational, because economic agents do not always choose what they want and in order to maintain self-value they try to rationalize it. Since ages neo- classical economist is often criticized for placing rationalism ahead of realism which eventually represents man as unrealistic. According to it man is an unbiased Bayesian forecaster always serious minded and never subject to psychological effects. As the concept of rationality is said to be an Olympian model. It is said that if financial markets consisted of only rational agent there would have been no trading. Another very important approach discussed was agents maintaining their self-value, creating a link between rationality and behavior. Also the relationship between disposition effect of trades their self-value has been discussed.
Theory of Self- value:
Real economic agents are not expected utility maximizes rationality is considered to be the focal point of economics in today's' convention but alternatively the international rationality is a much more dominant approach. Real Economic agents are not utility maximizes. They choose sub optionally but are not satisfied. We find the X- efficiency theory to explain the phenomenon of that's all I needed.” The causes of x inefficiency are motivation related ,intrinsic laziness often causes individuals to be inefficient but appropriate amount of pressure will reduce this kind of X- inefficiency and boost productivity. According to simon humans' rationality includes limitation on information acquiring, processing computational cap ability, organization and utilization of memory.
The Problem indecision utility and the concept of self-value.
- Self is never neutral
- Self is illusory
- Self is relative
Self is never neutral:
The concept of decision utility explains that self is never neutral. As discussed earlier economic agents often choose things, they do not require and so they rationalize it to save their self-value. The long heard phenomenon of sour grapes can best explain the concept. Individuals are boom with different physical and social incumbents and therefore behave differently. So the basis starts here where no care can stay neutral. When the economic agents are forced to accept thing in order to maintain or save face. “Although utility giving them psychological satisfaction and subjective comfort. It is very important to understand the difference between rationality and rationalism. Rationalization is not “acting rationally” rather seeking justification for an action or behavior. people rationalize to keep them self- value, that is either consciously or unconsciously.
Self is Relative:
Man is a social animal and so it is said there can be no self without the presence of others. According to Neoclassical economist utility is “ the subjective enjoyment or usefulness of person in consuming an article” or service” and does not support envy. Whereas in real life every human evaluates his/her utility not in absolute terms rather in relative terms”. It is also said that utility depends not only on consumption with in a population. (Sasndroni, 2004) proposes that the utility of an individual is basically their own relative position in their peer group as the struggle to be socially distinct is vital part of all humans. People get psychological satisfaction when they realize themselves to be better than the rest and are uncomfortable when they know that the care is vice- versa
Self is illusory
As it is known individuals are unable to understand themselves completely, reason being that a man does not view himself with his own eyes so self is said to be illusory. Agent self value illusion is the essence of matter. If people believe they personally have some value, they will be inclined to overconfidence. Hence it is the driving factor for most people to see themselves as better than average and for others see them.” Status quo bias also explains people self-value. individual are modest, conservative and require things that are relatively the same as that of others, because they are relative to knowledge that desirability of something until they are sure that they will get it. So highly rate what they already have which brings us in a better position to understand the kind of irrational behavior.
Disposition effect & self value:
He further analyzed the Disposition effect and the self value on which he explains why stock market traders tend to sell winners early and hold on to the looser for long” disposition effect”. Agents want to realize gains as soon as possible in order to keep self - value and so sell winner early whereas if the sell losers early they would realize loss , eventually portraying a wrong decision. It found that higher need to maintain self- value is found if the trade has a smaller trading account less annual salary, low education level and older investors. With worse disposition and vice- versa. Also the changes in the stocks performers could have higher impacts on people with trading account and low income than wealthier people.
Bias describes a tendency towards a particular idea or result, when the tendency interferes with the ability to be impartial, unprejudiced. In other words, bias can be termed as 'one-sided' perspective. It is used to describe an attitude, judgment, or behavior that is influenced by a prejudice. Bias can be unconscious or conscious in awareness. Cognitive bias is based on factors related to the brain. A cognitive bias is the difference in judgment that occurs in particular situations. Cognitive biases are instances of evolved mental behavior. There are many types of cognitive biases that include confirmation bias, Herding, Hindsight, Anchoring, Representativeness, Overreaction, Overconfidence etc. The existence of some of these cognitive biases has been verified empirically in the field of psychology. The causes of these cognitive bias are generally said to be the Attribute substitution where it is difficult for a person to judge by unconsciously substituting an easier judgment, second Attribution theory, Cognitive dissonance (Impression management & Self-perception theory), Thirdly, Heuristics, including: Adaptive bias, Misinterpretations or misuse of statistics.
- Availability heuristic - estimating what is more likely by what is more available in memory, which is biased toward vivid, unusual, or emotionally charged examples
- Representativeness heuristic - judging probabilities on the basis of resemblance
- Affect heuristic - basing a decision on an emotional reaction rather than a calculation of risks and benefits
Starting with Overconfidence, we find the evidence that according to (Glaser et al, 2003) Overconfidence can manifest itself in the following form: People believe that their abilities are above average(better than average effect), Thinking that they can control random tasks, being optimistic about the future (Illusion of control & unrealistic optimism.(Kahneman & Riepe, 1998, p. 54) Glaser et al, 2003 stated that:
“The combination of overconfidence and optimism is a potent brew, causes people to overestimate their knowledge, underestimate Risks and exaggerate their ability to control events”
People generally tend to believe that their knowledge is the best, and they are very confident about their own judgments(Shiller, 2002). People seem to learn from the errors made in past but still the over confidence bias appears to be a common act. Another study by Barber and Odean ,2001, (Glaser et al, 2003) explains the phenomenon of overconfidence and their proxy for overconfidence is Gender which proves that higher degree of overconfidence is found among men than women. Overconfidence leads to high trading volume by analyzing trades of individual investors who have online broker account. Over confident investors affect market outcomes, It is modeled as the over estimation of the precision of information or the underestimation of the variance of information signals. Some models assume that the degree of overconfidence changes over time that it increases as a function of past investment success due to biased self attribution. The tendency towards overconfidence has been found in both laboratory and materialistic settings and also among laypeople and experts. Researchers have found discrepancies between individuals subjective and relevant probability. Well by history it is proven that experts provide well calibrated judgments e.g weather forecast and horse race bettors. Factors that contribute to overconfidence are high degree of perceived expertise, more information, cultural difference & Gender.
There are two types of overconfidence
- Overconfidence in one's own knowledge
- Overconfidence in one's own ability
Overconfidence is one's own knowledge can be proven experimentally by giving test subjects general knowledge questions or subsequently acting them how confident they are in their answers. A systematic distortion can also be identified for judging confidence in one's own abilities (asking about driving skills).Though it is not always possible to differentiate between overconfidence in one's own knowledge or overconfidence in one's own abilities. (Torngren et Montgomery, 2004) describes an analysis done by two groups of people. Stock market professionals and lay people where it was found that professionals based the predictions on specific information of stock ignoring the unreliability of information, whereas laypeople used simple heuristics based on previous price movements. It also discusses the expert professionals actually know now about stocks and their future and to the extent to which they think they know. Experts are experienced and use the information efficiently. Generally it is assumed that expert knowledge helps investors make better judgments and more accurate predictions resulting in greater return on investment. Laypeople often take help of experts in order to deal with complex and uncertain environments whereas on the contrary this assumption has been ruled out by Groove n Meehl in 1996 that states: “As a simple linear model provides a more accurate prediction than experts” (Torngren et Montgomery, 2004, p. 148) Also that the basic amount of trading can provide lay people with enough knowledge to match up to the level of experts Now the question arises when they know so much, how can they perform badly? A research suggests that experts could do a better job by using historical means instead of specific evaluation.
One of the more significant and irrefutable findings of psychologist is that people are overconfident in their judgements and tend to overestimate the reliability of their information (Browne, 2000). People make changes in their lives and their portfolios because they are confident they are making a change for the better. The same tendency towards over-confidence exhibits itself in portfolio turnover rates, which are largely a result of attempting to “time the market.” Behaviorists have a term, “calibrated confidence,” which means knowing what you can do and what you cannot do. It requires being comfortable with the knowledge of how limited our abilities really are. It has also been found that over-confident investors trade more and make less. The greater the trading volume, the poorer the returns. Further (Browne, 2000) found A lack of confidence in one's abilities usually results in a lack of activity and low activity levels have been proven to produce better returns
(Torngren et Montgomery, 2004) concluded that according to results both groups expected the professionals to outperform the lay people by large margins but actually experts made equal number of errors as laypeople. Both groups were found overconfident but again the professionals overestimated their abilities by large margin. One professional's performance was 50% worse than expected rate. Also there was no distinct condition between certainty of having picked the right stock and actual success of both groups. Professionals mainly depended upon knowledge while the laypeople relied on the previous months dta as well as their judgment thus it is proven that the benefit of experience knowledge by experts is overreacted but in reality experts have no advantage over the laypeople. In short both groups displayed overconfidence and it was more evident among the professionals. Also that the information based predictions of experts did not outperform the simple heuristics of laypeople.
It is said that overconfidence is an outcome of perception of increased control Humans have a strong need to feel in control of their own situation, it is so strong that any deficiency in the perception of control can have physiological consequences. People like to imagine themselves in total control even if they are not because it makes them happier known as “illusion of control”. Illusion of control is the financial markets are observed when a person believes he/ she can significantly influence market events (strong perception). A very weak perception of control exists when a market participant believes he/she can explain why something happened after the fact. The perception of control here corresponds exactly to the overconfidence phenomena.(Olaf & Rudiger, 2005). Therefore, confirming the point that Perception of control significantly influences the level of overconfidence. “Stronger the perception of control, higher the level of confidence”. The study suggests the analysts should consciously confers the overconfidence phenomenon & take steps towards improving the quality of their forecasts. Head to become confident without being overconfident. The results of the study confirms the assumptions that overconfidence is more pronounced for earnings forecast then price forecasts. Also when their price forecasts are compared with those their colleagues, “Analysts argued that prices sometimes happen by chance are irrational investors”, whereas successful price forecasts have something to do with “luck”.
Future prices are dictated by general market movement “The stronger perception of control, the more overconfidence should be observed.” (Olaf & Rudiger, 2005, P. 122). “Bolder forecaster might be overconfident & Regression analyses are a good a remedy for overconfidence (Fisher and Statman, 2006).
Rumors and the Financial Marketplace
Rumors have a strong impact on contemporary business and economic environments. Life cycle and effect of rumors on the market varies from being transitory and kind to long-lasting and devastating. Technological advancements, particularly electronic media, have significantly increased the potency of rumors as it targets masses and information gets transmitted quickly. But the major drawback of this development is that it becomes quite difficult for the recipient to establish reliability of the information. Over the years it has been observed that rumors are increasingly targeting financial market (Kimmel, 2004). Electronic media has complicated the task of decelerating spread of marketplace rumors. Even a small mistake by a computer beginner can have a detrimental impact on a company's financial status. Not only is it difficult to establish authenticity of the rumor but also the speed with which it spreads in the market. At times, the companies have to face major losses because of spread of false rumors. (Further Kimmel, 2004) discussed the issue of how and why these rumours spread. There were number of etiological explanations found regarding spread of rumors. Behavioral scientists and social scientists attribute rumor origination and spread to social and individualistic needs. Social Psychologists Gordon Allport and Leo Postman (Kimmel, 2004) were of the view that rumors serve an important function, especially during the time of crisis. According to them, rumors alleviate anxieties of people by providing some sort of explanation when faced with uncertain distressing conditions. Factors that play a central role in rumor's diffusion include credibility of the person who delivers the information; reliability of the source providing information and repetition.
Financial rumors are believed to spread as the result of people's curious nature and strong desire to establish rumors' truthfulness. By trying to establish rumors' credibility, people attempt to anticipate changes that are likely to occur in the financial market. As opposed to non-financial marketplaces rumors, rumors' target gets as much attention as does its content.
Financial rumors are categorized into three basic forms -- Company based Financial Rumors (rumors about companies' financial behavior), People-Oriented Financial Rumors (rumors revolving around people whose activities influence financial status of the firms) and Event-Oriented Rumors (rumors about events occurring in economic and political environments). In the contexts where new information is valued, financial rumors get utmost importance. More specifically, rumors manage to gain more attention in the bear markets contrary to the markets that maintain a stable standing. Amount of attention a rumor gains also depends on the place where it is printed in a newspaper. The content of rumors also impact emotions of the people by making them either optimistic or pessimistic. Financial markets and firms need to take a number of steps if they want to protect themselves from the devastating effects of rumors. Financial marketplace need to direct their attention towards enhancing their public relations so that they can develop an environment of trust among people. Financial business environments should not only be mindful to the emergence of rumors but also prepared to counter their detrimental effects. Firms should hire people that should be assigned the task of assessing the presence of rumors and also monitor firm's acts that are likely to generate rumors. Company should implement crisis management plan in case it senses presence of a rumor likely to negatively impact company's standing in the financial market. By following the aforementioned strategies, financial marketplace can insulate itself from number of variables that are likely to affect its sound stability.
What is herd behavior? Herd behavior describes how individuals in a group can act together without planned direction. The term pertains to the behavior of humans conduct during activities such as stock market bubbles and crashes, street demonstrations, sporting events, religious gatherings, episodes of mob violence and even everyday decision making, judgment and opinion forming.
(Lutje, 2004) in his article explains the phenomenon of Herding, and finds out that this type of bias is very common among the Financial market experts known as “Institutional investors” These are organizations which pool large sums of money and invest those sums in companies. They include banks, insurance companies, retirement or pension funds, hedge funds and mutual funds. Their role in the economy is to act as highly specialized investors on behalf of others. Furthermore, because institutional investors have the freedom to buy and sell shares, they can play a large part in which companies stay solvent, and which go under. Influencing the conduct of listed companies, and providing them with capital are all part of the job of investment management. They face Low transaction costs & a balanced portfolio. From the empirical results we find that they mostly fail to achieve the market developments, no matter what kind of fund they manage” which is eye-opening as we all expect the institutional investors to be sophisticated , experienced and well- informed. Kimmel gives the possible explanation for the weaker performance which is that asset managers could show inadequate working effort as they receive insufficient incentives and tend to follow the herd behavior that is related to less amount of effort than others. The institutional investor act as an agent of the client where it brings about a conflict of interest that is: “when clients demand attractive risk adjusted performance and the investor being effort averse are more concerned about the adequate compensation for their working effort(Explicit Incentive), and adequate development of their professional career (Implicit Incentive).” (Lutje, 2004, p. 2) Whereas they should be more concerned with their reputation instead of being effort averse. To measure the performance of asset managers their investment performance is commonly analyzed comparative to their peer group. Which, again causes the strategic behavior of herding where they try to be either equally good as their peers or Try to be better than the peers. Furthermore it is found that Herding Managers are successful in finding and sharing the blame and hide in the herd when their decisions appear to be unprofitable”. It is said that the reputational career concerns may induce Herding, as young managers are much more concerned about their future and have a higher probability of being fired on their bad performance than seniors. Empirical results prove that the tendency to herd decreases with the age, as when the managers become old they are more experienced, established and tend to make bolder forecasts to manipulate the assessments of their ability. The survey results provides evidence fort the reputational her behavior, exerting less effort, More Risk Averse, prefer short term investment and usage of non-fundamental information but are willing to take higher risk in short term tournaments scenarios tending not to fall out of the herd.
Survey was carried out in 2003 and findings were based on reputational herding, Herding managers' working effort, preferred source of information and investment horizon, Herding managers' risk taking behavior, Herd behavior in the tournament Scenarios. The results somewhat supported the hypothesis that were created and it was found that institutional herding is part of the practical world. It is perceived to a large extent by a great majority of asset managers. The results clearly state: Herding managers believe in benefits of herd behavior for their career. In order to be either as good as peers or better than peers they show less working effort than non-herding asset managers. Herding managers' investment behavior drives prices away from fundamental equilibriums, because they significantly use more non-fundamental information and focus on shorter investment horizons. Furthermore, they are generally more risk averse and loss averse and their investment decision is more biased by a disposition effect. Interestingly, the survey provides strong evidence that herding managers are generally more risk averse, but in the tournament they are willing to take more risk. We ascribe this finding to their fear of falling out of the herd. The survey done by Lutje, 2004 concludes that herding is induced by career concerns, as asset managers working effort is not monitored by the client and just by his supervisors; he has some opportunity to reduce his working hours. From the survey results it was found that the Herding asset managers base their investment decisions comparatively more on technical analysis, investment decision of other market players and statements of other opinion leaders, giving significantly less importance to fundamental information and discussions with their colleagues. The survey confirms that the herding managers focus on the short term investments' than non-herding managers. According to the self - assessment herding managers consider themselves as More Risk Averse. But we must take into the account the bias that self assessment can deviate from the actual risk taking behavior. Whereas to analyze this risk taking behavior we further divided into two main factors: a) Loss aversion (Being more sensitive to losses than gains, while loss aversion only considers the investment behavior regarding losses, the disposition effect will take care of profits) Results confirm the hypothesis that Herding Managers are More loss averse. b) Disposition effect ( To ride the losers for long and to sell winners too soon).The results demonstrate a stronger disposition factor among herding managers. Concluding the hypothesis that managers do not keep their strategies to the end of the period, managers are biased towards taking less risk in case of Outperformance. In (Shiller, 1995) “Rhetoric & Economic Behavior Conversation, information and Herd behavior” discussed the herding as a bias where People sharing same geographical background, cultural and sociological ideas generally behave similarly. The tendency for people in groups to think and behave similarly explains exhibited as they represents their thoughts or in some cases it is psychological motivation. Herd behavior is an outcome of not hard and fast rules or facts rather subtle matters (depending upon the variety of thoughts, time, intelligence of individuals), there are limitations in discovery all such relevant information. Two approaches are analyzed. Informational cascade, In which people acquire information by observing actions of others in their group of people, which precede them in actions. The bad equilibrium arises from a hard externality” of imitating others and thereby concealing one `s own information. This may also be called as a social pressure where people rational take into account others information based interpretation. An example might clearly start the concept e.g a group of people are asked a question to which the answer seems to be an obvious one and the probability of making an error is low. But if first three or four subjects answer a wrong statement thus there is a greater possibility of other subject answering wrong.
Which explains the psychology of human “to me it seems, I'm right, but my reason tells me I'm wrong , because I doubt that so many people could be wrong I alone right (Asch, 1952 . p: 464) Shiller, 1995. Explaining the irrational effort to interpret the conflicting evidence.
Further the Shiller explains the phenomenon of Herd Behavior with the help of drugs, alcohol, cigarette, religion. Secondly, Conversation Analysis: To condensate is to communicate in order to facilitate communication, make it efficient and frequent there has evolved a complex structures of brain structures supporting emotional important facts, common assumption an important facts. A social group must promote a collective memory of important facts, common assumption and conventions.
Human behavior involves a tendency of free flow of ideas and thoughts exchange known as conversation, to exchange a wide variety of information: with the evolution of time, modern civilizations have come up with other structured environment for exchange of information e.g seminar, meeting, conferences etc but are still dominates by ordinary face to face personal conversation. One of the reason of media appearing to be comparatively less effective in transmitting information them ordinary interpersonal conversation are the emotional response. These are discussed the rules of a polite conversation, which calls for the respect for common consensus on the topic of discussion. Abruptly changing the topic is out of mannerism rather linking it to the previous one would an appropriate way. Every member should be given a chance to communicate.(Shiller, 1995). Information & the volatility of mass behavior while the concept of information cascade has been discussed. Different groups have different conversation patterns as well as circumstances promoting informational cascades. The reason of differences in mass behavior among different groups, the difference in transmission of information. The difference of transmitting information among group must be due to differences in initial condition and opinions of that group. Conversation patterns may also vary across groups in terms of habits of reviewing the source of information. Differences across groups in such dimensions.
The framing effect describes that presenting the same option in different formats can change people's decisions. Individuals have a tendency to select unpredictable choices, depending on the framing of the question. Framing impacts people, because individuals perception varies on the concept of losses and gains The value function, founded in prospect theory, illustrates an important underlying factor to the framing effect that a loss is more disturbing than the gain is gratifying. Thus, people tend to avoid risk when a positive frame is presented but seek risks if a negative frame is utilized. Another important factor contributing to framing is certainty and pseudo certainty effects(people's tendency to make risk-averse choices if the expected outcome is positive, but make risk-seeking choices to avoid negative outcomes) in which a sure gain is favored to a probabilistic gain.
Some Market data providers assume a positive relationship between information quantity and investment success by promising that a person will make more, because he will know more. Evidence suggests investors generally benefit from the provision of information. Empirical studies, however, indicate that more information does not necessarily lead to more knowledge. In the psychological literature, this is referred to as the “illusion of knowledge”, and is confirmed empirically for many decision domains.(Kirchler et al, 2005) Information plays an important role not only in individual investment decisions, but also in market environments. Market efficiency requires that aggregate market prices will not be affected by either objectively irrelevant information, or by selectively distributed information. Thus, while individual investors may be prone to biases like the illusion of knowledge even then aggregate market prices are considered unbiased.
(Kirchler et al, 2005) In their research focused on the communication and the quality of information in the context of a competitive asset market. Investigating the impact of objectively irrelevant information on trading behavior, by drawing upon a novel type of framing. The results showed that objectively irrelevant information does influence trading behavior. “Moreover, positively and negatively framed information leads to a particular trading pattern, but leaves trading prices and trading volume unaffected”. (Kirchler et al, 2005, p.91)
The findings also supported the disposition effect where Participants who experienced a gain sold their assets more rapidly than those who experienced a loss. This effect is further mediated by framing: Positively framed market participants generally sell their assets later than negatively framed participants. Expected utility theory assumes vivid invariance, which implies that different representations of the same choice problem should yield the same preference. However, several empirical studies indicate that this saying is frequently violated in individual decision making. In 2000, Weber, Keppe, and Meyer-Delius (Kirchler et al, 2005) investigated the impact of “endowment framing” on market prices in an experimental asset market. Participants were given either 1) cash plus a certain amount of positively valued risky assets (long position, positive framing), or 2) a larger amount of cash and certain state-contingent liabilities (short position, negative framing). In terms of final wealth, the endowments were identical. In line with the predictions of prospect theory, Weber, Keppe, and Meyer-Delius  found that overpricing1 was observed more often for negatively framed market participants than for positively framed participants. Framing effect is generally a reliable phenomenon.
Eventually it was found that objectively irrelevant information influences trading behavior: Positively framed buyers purchase assets from negatively rather than positively framed sellers, and negatively framed sellers sell their assets to positively rather than negatively framed buyers. The matching of unequally informed subjects, however, does not lead to different trading prices. We also find that a probability variation of the framed information impacts trading volume. We believe this is attributable primarily to the unbalanced sequence of trading periods across markets. Based on the predictions of prospect theory, we expect that a purchase price lower than the previous market price implies a gain situation that leads to more rapid selling. In turn, a purchase price higher than the previous trading price implies a loss situation that leads to less rapid selling. Positively framed participants seemed to be more optimistic about the likely performance and profit of their assets. They were thus also more patient, both in gain and in loss situations.
Objectively irrelevant information does influence individual trading behavior. Moreover, positively and negatively framed information leads to a particular trading pattern: Positively framed buyers purchase assets from negatively framed sellers, and negatively framed sellers sell their assets to positively framed buyers. The observed matching of unequally informed subjects, however, does not lead to different trading prices. There is weak support for the assumption that a probability variation of the framed information impacts trading volume. However, we believe this effect is attributable to the unbalanced sequence of trading periods in the two asset markets, not to the available information. The disposition effect was confirmed. Participants sold their assets more readily in gain situations than in loss situations. The effect was further mediated by framing: Positively framed market participants generally sold their assets later than negatively framed participants (Kirchler et al, 2005) The framing of dividend information influenced individual expectations, and therefore market behavior as well. Since objectively irrelevant information influenced market behavior, our findings violate expected utility theory and the invariance axiom. Standard finance theory assumes that markets filter out irrelevant information, allowing individuals to arrive at unbiased decisions. In particular, it assumes that even if irrelevant information helps nothing, it does not harm anything either. But our findings cast doubt on this statement. Additional irrelevant information does not leave the decision problem unchanged. It can systematically influence trading behavior even in competitive market environments.
Over & Under Reactions:
Under reaction It is a situation where individuals fails to react completely and immediately to new information: under reaction is often dated to people relying on anchoring values, even if not clearly defined, Over reaction is excessive reaction to information, it may stem from representativeness ,arising from important information and strengthen after a series of similar information. (Kaestner, 2006) This article presents explanation for stock price anomalies that doest not take into account the fully rational behavior. The two groups of pervasive in efficiencies have the challenges of efficient markets
Short term under reaction'
Long term overreaction
The study aims to reconcile short term under reaction with long term overreaction in the quarterly earnings announcement frame word. Earlier researchers were focusing on the most famous stock market anomalies PEAD(Post Earnings Announcement Drift) where as the writer scales unexpected surprises positive or negative surprises. In such context the bias of representativeness is keen to overreaction. Kaestner takes the eidence of investor's misreaction regarding earning information and found that many researchers have been working on this phenomena of over reaction of investors to past stock market performance where as the overreaction phenomena lay over horizon has been confirmed several times on the stock market. Subsequent abnormal performance turns out to be higher for prior losers that is stock expediency the present past performance. Unlike over reactions analysis, prior winners outperform prior losers over the following 6 months period.
Many theories have been advanced to explain the slow adjustments of stock prices to recently and publicly available earnings information. A great role has been played by the individual's investor's illiquidity issues, low analyst coverage, or analyst under reaction to extreme bad news causing market under reaction. More recently the disposition effect is a potential explanation for the PEAD, investors having experienced gains or facing positive news are more inclined to take their gains then delaying the information dissemination.
There are relatively fewer empirical studies reporting simultaneously over and under reaction recently in order to understand that whether mispricing may be reacted to cognitive bases may thyroidal models have integrated both the phenomena together. It also has been found in a model by daniel ,hirshleifer and subra manyan in 1988 (Kaestner, 2006) where over reaction is due to over confidence where as self attribution causes under reaction. Also by integration two cognitive heuristics, anchoring and represent manners came under and over reaction on the contrary using market related information causes over reaction.
Investors under reaction to earning announcements, Kaestner also confirms the existence of slow price adjustments to unexpected earnings. Again Kaestner results were consistent with the overreaction representativeness hypothesis. Where, it seems that investors rely too heavily on the information carried out by the past earnings surprises. After an important positive surprise, investors are deceived, on average by the recent earning figure and for the prior losers, having an unexpected negative surprise would again portray a wrong picture. “And so it was found that for a highly unexpected positive surprise brings on negativity where as negative surprises bring on positively abnormal returns at the time of the subsequent earning.”
Therefore, the results suggested that extreme earnings surprises are followed at the time of earnings announcements by a market reaction to the opposite sign to the initial surprise. If thus over reactions is due to representative bias then investors would not extrapolate a given earnings surprise into future /and end up disappointed when the subsequent actual earnings figures are announced, but also miscreant heavily to a series of similar surprises. So investors over react to past highly unexpected earnings and only correct the extreme belief at the date of subsequent earnings for a long series of similar consecutive earnings surprises. The results indicate that representativeness' causes investors to over react more heavily to a series of similar information. If these beliefs are not confined by actual earnings figures the markets experiences a strong reversal. It also has been confirmed that under reaction exists with post earnings announcement and leading to overreact to high unexpected past earnings surprises. Investors simultaneously exhibit short term under reaction to earning announcements and long term over reaction to past highly unexpected earning.
According to Fisher and Statman the illusion of validity persists because people fall to the confirmation bias “Focusing on the information that is consistent with the beliefs, neglecting inconsistent information”(Fisher and Statman, 2006, p.
) The confirmation bias is common. As it is said that people are terribly good at feeling themselves. they are sure about the answer and does not want to confuse with the other dock. The only remedy for the bias is examining all date confirming as well as disconfirming
Anchoring is the common human tendency to rely too heavily or “anchor” on one trait or piece of information when making decisions. Usually once the anchor is set, there is a bias towards that value. (Shiller, 2002) There may be sometime a rational phenomenon for respondents. Anchoring has an information- response component in may circumstances, anchoring behavior persists even when information is absent. People may object that the concept of anchoring on part prices helps determine present prices in the stock market might be inconsistent with the low serial correction of stock price might be inconsistent with low serial correction of stock price changes” smart money”. It is assumed that many economic phenomena of “sticky price” in macroeconomics. The more ambiguous the value of commodity the more important a suggestion is likely to be and the more important anchoring is likely to be for price determination. Anchoring is also present at the back end of “money illusion” introduced by Fisher (1928) that refers to human tendency to make inadequate allowance in economics decision rate of inflation and confuse real and nominal qualities.
(Fisher & Statman, 2006) The anchoring bias rated by Ford foundation is also one major cognitive bias which was born out the crash of 1929. It was concluded that the past thinking by many endowment managers has been overly influenced by feen of a major crash. Although future is unpredictable, we can not think a long term policy founded on such few can survive dispassionate analysis of the probability of a crash and the cost of guarding against one long. The anchoring bias involves the tendency to anchor estimate to silent humbers even if there numbers have little or no relevance to the estimate.
Hindshight bias leads people to exaggerate the quality of their foresight. It also is a serious problem for all historians, including stock market historians. Fischoff found that in general, people overestimate the quality of the initial knowledge and forget initial errors.
“once an event is part of history, there is a tendency to see the sequence that led to it as inevitable”
In hindsight, blunders with happy resells are described as brilliant tactical moves, and sad results of choices that were well grounded in available information are said to be avoidable blunders. Remedies for cognitive biases: Regression analyses protects from over confidence, Regression analyses protects from confirmation bias, By confirming all data, confirming as well as there statistical tools are very useful, extracting systematic patterns from part. They work best with data that can be quantified and traced over long periods of time.
Long periods of time Where as there statistical tools have pitfalls of their own, pitfalls that require careful applications and judictions interpretations. However organizational tools can supplement statistical tools in alleviating cognitive bias
Regret and Cognitive Dissonance
Regret and Cognitive Dissonance is human phenomena of repenting on doing something wrong or taking wrong decision. In order to avoid the pain of regret, one may alter ones behavior in a way by doing irrational acts. “Regret is the pain we feel when we find that its too late, that other choices would have led to better outcomes” (Fisher & Statman, 2006, p. 7). There are many ways of representing how people behave who feel pain of regret, but a general concept is having a kink in the value function at the reference point. According to a research investors delay selling of stocks that have gone down in value whereas the accelerate the selling of stocks that have gone up, in order to (Shefrin and Startmen, 1985) overcome the regret.(Shiller, 2002). Whereas cognitive dissonance is the mental conflict between different alternatives present with evidence that their belief or assumption or wrong so it's a regret over mistake belief. The regret and the cognitive dissonance theory assert that there is a tendency for people to take actions to reduce cognitive dissonance that would not normally be fully rational. People my avoid the information or develop contorted arguments to maintain beliefs or assumption. There is empirical support that people often make the errors represented by the theory of cognitive dissonance. When investors loose funds they are unwilling to comfort the evidence that they make a investment by selling their investment.
The disjunction effect
It is tendency for people to want to wait to make decisions until information is revealed, even if its not important. Regardless of the fact that their decision would change based on the information. It is a contradiction to the “Sure thing principle of rational behavior, with the help of experiment the researcher plots the behavior of individuals that if the outcome of one thing is known as its good, then subjects have nothing to lose in taking another option too, and if the outcome is bad they want to try to recap their losses, but if the outcome is not known they have no clear reason to accept the second one. It also might explain changes there is sometimes low volatility and low volumes of trade just before an important announcement is made. Shefir & Tuersly in 1992(Shiller, 2002) gave the example of presidential elections including stock market volatility, when the outcome of election is known.
Gambling Behavior & Speculation
Human behavior of playing game that bring on unnecessary risks has been found to prevail in all the cultures of the world and indicates a basic human trail. The tendency for people to gamble has provided a puzzle for the theory of human behavior under uncertainty come across two type of behavior generally.
- Risk avoiding
- Risk loving
Gambler does not appear to be systematically risk- seekers in any general sense instead either its part of entertainment or habitual. Other than that gambling is often found with certain specialty in any game or just the phenomenon of being lucky with entrainment things. Gambler may have very rational expectations at some level for the likely outcome of their gamble where as economists only talk about quantitative expectation as the only characterization result.
Magical Thinking and Quasi - magical Thinking:
It can be regarded as a specific behavior pointed out by B.F Skinner, 1948 (Shiller, 2002) Arbitrary behaviors are termed as magical thinking as there are variety of economics behavior such specified behaviors might appear as the result of few chains of action and events. An example presented might explain the phenomenon much more clearly. Where people were divided into two group “critical and experimental” and were asked to hold their hands in icy cold water for a time span, in experimental group subjects were told that only people with strong hearts could hold their levels longer in the water, and so people in the experiment s' outcome can be explained as a desire for self- deception where people do behave as if they thinks they can change predetermined conditions. Quasi-magical thinking appears to operate more strongly when outcome of future events rather, than history. Therefore stated that Quasi- magical phenomenon is unable to explain the basis of strictly rational behavior.
Like all other phenomenon, mental components refer o a human tendency to place particular event into mutual components based on superficial look at small decision separately. It is agree that investors place their investment into separate mental attributes, instead of having a clear wide idea, invidual look at small decision separately. It is agree that investors place their investments into separate mental components. Shefrin& Thaler in 1998 (Shiller, 2002) categorized peoples' sources of income into three categories. Current wage, Asset income and Future income. Spending differently out these this phenomena might also explain the concept of January Effect anomaly, which is not related to the taxes as the model was tested in different countries, and the tax year of each country is different. It depends on peoples' mindset if they consider the year end as a time of reckoning and new year as new start. They may be inclined to behave differently at the terms of the year end this may explain the January effect”.
Trends & Sequences in Financial Performmance: A test of Behavioral Theories
The recent researches on the inefficient markets hypothesis have been based on investors biased Information processing, which is just a variation of representative heuristics.. Representative heuristics is central to the phenomenon of Mispricing. For any industry the past performance of the industry is the major indicator of the future of that Industry, similarly, in Behavioral Finance, the pattern of past performance is an important driver or Representative heuristics. it has been argued “that trends & sequences, in financial performance operationalize representativeness”. (Chan et al, 2002, p. )
Investigating the past trends & sequences of financial performance and the future returns. The study fails to prove that investors systematically over extrapolate a consistent sequence of financial performance at long horizons; to some extent it is proved that investors under react to a one year trend in accounting performance. Also that the past trends & the pattern of growth do not lead to predictable returns following subsequent performance confirming or contradicting the past trend. Therefore, the evidence fails to suggest that patterns or trends in past financial growth rates leads investors form biased expectorations about the future performance. Presenting a challenge to the representative based theories. For the behavioral theories of mispricing it is said that Arbitrage is restricted and thus it cannot eliminate the mispricing completely.
Chan et al discusses the Representative bias and its role in the formation of investors expectations. It is perhaps the most prominent bias on human information processing.”It is the tendency of people to classify things into discrete groups based on similar characteristics. It is said that individuals focus on similarities, so they diverge from rational reasoning. Subjects fail to consider base rates, Subjects fail to incorporate sample size and Subjects ability to realize that extreme observations are unlikely to be repeated
In many recent models of BF, representative bias is an under lyer which assumes that some investors are irrational. Representative bias is an outcome of either investors assumption of wrong model or because they are not Bayesians. Investors predict on the basis of strings sequences or patterns of financial performance.
Moreover the paper explains the concept of operationalising the representative bias. Barberis et al(Chan et al, 2002) predicted that securities with string of good performance, when measured, receive extremely high valuations and then valuations, on average , return to be the mean. Moreover Salience and availability of information have a vital role in representative bias and formation of expectations. Representative bias can lead investors to use known facts as the starting point from which to draw inferences or conclusions about something unknown and cause overreaction, which later on would prove to be incorrect conclusion or are proven false. Prediction entails three basic steps
- Researchers define a model of biased investors expectation about dividends.(where the length of the model does not specify the past performance to generate an optimistic or pessimistic expectations.
- Specifying the model of how dividends truly evolve.
- Deriving the patterns of error in expectations, that can predict patterns of stock returns.
Therefore Representativeness could predict either a Drift or reversal in medium terms, whereas the behavioral theories appear to be of extreme financial performance over a five year horizon leading to over-optimism or pessimism and eventually reversing the prices
Also the representative bias influences the optimism and pessimism of the investors consistency in the performance of intervals (one year - 5 years), examining the consistency of performance over one-five year horizons further leading to overreaction and its reversal. Confirming and disconfirming also effects the price performance. Investors suffering from Representative bias initially overreact but again reconcile with the observations that confirm their bias or correct for the past overreaction when faced with disconfirming observations.
In a typical behavioral finance model, investors mentally misplace firms into various groups based on their own perceptions, past performance, and are surprised or disappointed in predictable ways. This surprise is reflected in returns. The evidences were consistent to the findings of previous researches of multi month momentum in returns after accounting performance. the momentum is substantially reduced when the earnings surprise effect has been controlled, No evidence of multiyear reversal was found related to past performance. A .little evidence has been found that consistent growth rates improves return predictability, past accounting performance is not related to future returns, and therefore is unlikely to bias investors consensus expectations.
Brav, Alon, Heaton, B.J and Rosenberg, Alexander (2004), “The Rational-Behavioral Debate in Financial Economics”, Journal of Economic Methodology, Vol. 11, No. 4, (page 393-409).
Browne, Christopher H (2000), “Value Investing & Behavioral Finance” Columbia Business School.
Chan, Wesley. S, Frankel, M.Richard and Kotahri. P.S (2002). “Testing Behavioral Finance Theories Using Trends & Sequences in Financial Performance”, Working Paper MIT Sloan School of Management.
Crowell. Richard A (1994), “Cognitive Bias and Quantitative Investment Management”, Pan Agora Asset Management Inc.
Kirchler. Eric, Maciejovsky. Boris & Weber. Martin (2005), “Framing Effects, Selective Information and Market Behavior: An experimental Analysis”, The journal of Behavioral Finance, Vol. 6, NO. 2, (page90-100).
Fisher, Kenneth L. and Statman, Medir (2000), “ Cognitive Bias in Market Forecasts”, The Journal of Portfolio Management.
Gao, Lei and Schmidt, Ulrich (2005), “Self is Never Neutral: Why Economic Agents Behave Irrationally”, The Journal of Behavioral Finance, Vol.6, No - 1, (Page 27-page 37).
Gervais, Silmon (2001) “Is Behavioral Finance a Growth Industry” Knowledge at Wharton.
Glaser, Markus, Noth, Markus & Weber, Martin(2003), “Behavioral Finance”, SonderForSchungsBereich 504, Universitat Mannheim (No 03-14).
Kaestner, Michel (2006), “Investors` Misreaction to Unexpected Earnings: Evidence of Simultaneous Overreaction and Underreaction”, Montpellier University
Kimmel, J. Allan (2004), “Rumours & the Financial Market Place” (Editorial Commentary), The Journal of Behavioral Finance, VOL 5, No. 3, (Page 134-141).
Loeper, B. David (1999), “The Asset Allocation Myth”, Wealth care Capital Management, White Paper.
Loix. Ellen, Pepermans. Roland , Mentens. Cindy, Goedee, Marten and Jegers, Marc (2005), “Orientation towards Finances: “Development of a Measurement Scale”, The Journal of Behavioral Finance, Vol. 6, No. 4, (page 192-201).
Lutje, Torben (2004), “To Be Good or To Be Better: Asset Managers` Attitudes Towards Herding”, Discussion Paper No. 297.
Olaf Stotz and Rudiger von Nitzsch (2005), “The Perception of Control and the Level of Overconfidence: Evidence from Analyst Earnings Estimates and Price Targets”, The Journal of Behavioral Finance, Vol. 6, No. 5, (page 121-128).
Sandroni Alvaro (2004), “Efficient Markets & Byes Rule”, Economic Theory 26, (page 741-764).
Schmidt, Ulrich & Horst, Zank (2002), “What is Loss Aversion?”, The Unviersity of Manchester, United Kingdom & Universtat Hannover.
Shiller. J. Robert (1995), “Rhetoric and Economic Behavior, Conversation, Information and Herd Behavior” Cowles Foundation Paper 909 (Page181-page185).
Shiller, J. Robert (2001), “ Human Behavior and the Efficiency of the Financial System” Cowles Foundation Paper No. 1025
Shiller, J. Robert (2002) , “ From Efficient Market Theory to Behavioral Finance, Cowles Foundation For Research in Economics, Discussion Paper No 1385.
Shiller, Robert J (2006), “Tools for Financial Innovation: Neo classical versus Behavioral Finance”, The Financial Review 41 (page 1-8) Yale University.
Torngren, Gustaf & Montgomery, Henry (2004), “Worse than Chance? Performance and Confidence among Professionals and Laypeople in the Stock Market”, The Journal of Behavioral Finance Vol. 5, No. 3, (Page 148 - 153)