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The modern investment theory and its application on the efficient markets hypothesis

1. Introduction

The Modern investment theory and its application is predicated on the Efficient Markets Hypothesis (EMH), assumption that markets fully and instantaneously integrate all available information into market prices. Underlying this comprehensive idea is the assumption that 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, "Capital Asset Pricing Model", "Arbitrage Pricing Theory" and "Cox Ingersoll-Ross theory" of the term structure of interest rates, all of which are predicated on the EMH[2] rather than downside risks[3]. The theory of behavioral finance is opposite to the traditional theory of Finance and deals with human emotions, sentiments, conditions, biases on collective as well as individual basis. Behavior finance theory is helpful in explaining past practices of investors and determining the false performance of the investors. Behavioral finance is a concept of finance which deals with finances incorporating findings from psychology and sociology. It is reviewed that behavioral finance is generally based on individual behavior and financial market outcomes. There are many models explaining behavioral finance that explains investor's behavior or market irregularities where rational models fail to provide adequate information. Investors do not expect such research to provide a method to make lots of money from inefficient financial markets quickly. According to Shiller (2001) Behavioral finance has basically emerged from the theories of psychology, sociology and anthropology where implications of these theories appear to be significant for efficient market hypothesis, that is based on the positive notion that people behave rationally, maximize their utility. It is found that in efficient market the principle of rational behavior is not always correct. Thus, the idea of analyzing other model of human behavior has come up. Gervais (2001) further explains the concept where he says that people like to relate to the stock market as a person having different moods, this person can be bad-tempered or high-spirited and can overreact one day or make amends the next. This person indicates human behavior which is unpredictable and behaves differently in different situations. Lately many researchers have suggested the idea that psychological analysis of investors may be very helpful in understanding financial markets better. To do so it is important to understand behavioral finance presenting the concept of traditional theory overestimating rationality of investors, their biases in decisions casting a cumulative impact on asset prices. To many researchers the study of behavior in finance appeared to be a revolution. As it transforms people's mentality and perception about markets and factors that influence the markets. "The paradigm is shifting. People are continuing to walk across the border from the traditional to the behavioral camp". Gervais (2001, pp.2). On the contrary some people believe that may be its too early to call it a revolution. Gervais (2001) states that Fama in (1970) argued that behavioral finance has not really shown an impact on world prices, and that model contradict each other on different point of times. Giving very less account to behaviorist explanations of trends and the irregularities "anomaly" ( is any occurrence or object that is strange, unusual, or unique) also argued that in order to locate patterns the data mining techniques are much helpful. Other researchers have also criticized the idea that behavioral finance models tend to replace the traditional models of market functions. Some weaknesses in this area, explained by Gervais (2001)are that generally overreaction and under reaction are major causes of market behavior. In these cases People take the behavior that seems to be easy for a particular study regardless of the fact that whether these biases are either primary factor of economic forces or not. Secondly, lack of trained and expert people. The field does not have enough trained professionals both in psychology or finance fields and therefore as a result the models presented by researchers are improvised.

Gervais (2001) also focused on individual behavior impacting asset prices and explained that this field of behavioral finance is currently in its developmental stage, in its way of development it is facing a lot of disagreement which itself is a productive one. He points out that if we apply the conceptual models of behavioral finance to the corporate finance, it can majorly pay off. If money managers are incorrectly rational, means they are probably not evaluating their investment strategies correctly. They might take wrong decisions in their capital structure decisions. It has been found that quite a few people foresee behavioral finance displacing the age old Efficient Markets theory. On the contrary underlying assumption that investors and managers are completely rational makes insightful sense to many people.

2. Traditional Finance and Empirical Evidence

Fung, (2006) claimed that Post Keynesian theory has criticized mainstream economic theory for using statistical methods to model the world in which histori­cal market data cannot provide, In recent years, two different lines of research experimental economics and behavioral finance have pro­duced results that are at odds with the predictions of mainstream finan­cial theory. This paper argues that it is beneficial to the development of good financial theory for Post Keynesian economists to engage in an exchange of ideas with the practitioners of these two lines of research. The difference of opinion originated when experimental economics and behavioral finance understood the difference between agents rationality in theory and in real world. Both had a same point of view regarding Post Keynesian economists where both of them refused to assume Post Keynesian economists assumption of economic actors being always rational by maximizing expected utility. Instead of assuming rational economic ac­tors who always act consistently, they often tap into insights provided by psychology to try to explain economic behavior. The use of psychol­ogy can be traced back to Keynes, and, in fact, some of the papers in experimental economics and behavioral finance take a remark of Keynes on the psychology of economic actors as an inspiration for designing empirical tests of economic behavior. Indeed, some of these papers rec­ognize that we live in an uncertain world, and they examine the heuris­tics, or rules of thumb, that economic actors develop to guide their behavior in face of uncertainty. When Keynes made his remark in 1936 (the original publication date of the General Theory), there was not yet an efficient market hypothesis. But in 1970 Fama published his pioneering paper on efficient markets. In it, he defined an efficient market as a market in which prices always 'fully reflect' available information. Traditional theory assumes that agents are rational and the law of one price holds" that is a perfect scenario. Where the law of "One price[5]". And agent's rationality explains the behavior of investor "Professional and Individual" which is generally inconsistent with rationality or future predictions. If a market achieves a perfect scenario where agents are rational and law of one price holds then the market is efficient. With the availability of large amount of information, form of market changes. It is unlikely that market prices contain all private information. The presence of "noise traders" (traders, trading randomly and 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. According to Glaser et al. (2003) Few examples from the past literature explains the problem of irrationality which occurs because of naive diversification, behavior influenced by framing, the tendency of investors of committing systematic errors while evaluating public information. Lately it has been found that investors` attitude towards the riskiness of a stock in future and 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 actions that stocks have a higher risk adjusted returns than bonds. Another issue with the investors is that these investors either care about a stock portfolio or just about the value of each single security in their portfolio and thus ignore correlations. The concept of ownership society[6] 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 Shiller (2006) suggested that in order to improve lives of less advantaged people in our society is to teach them how to be capitalist, In order to put ownership society in its right perspective, behavioral finance is needed to be understood. The concept of ownership society seems very attractive when people appear to make profits from their investments. Behavioral finance is also very helpful in understanding and justifying government involvement in investing decisions of individuals. The failure of millions of people to save properly for their future is also a core focus of behavioral finance.

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 and 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 and Transaction Volume. It includes findings such as Overconfidence, Biased Self- Attrition, and Conservatism and Representativeness.

Preference Based Model: Rational Friction or from psychology Find explanations, Market detects irregularities and individual behavior. It incorporates Prospect Theory[7], House money effect and 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 it was found 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 behaviors. 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.

Heaton & Rosenberg (2004) presented Milton Friedman's theory that laid the basis of positive economics. His methodology focused 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 economy, i.e. Investor uncertainty, which further cause financial anomalies. In explaining these assertions, the behavioral approach emphasizes importance of taking limits in arbitrage. Further his methodological approach falls into the category `instrumentalism[8]', 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 said that behaviouralists are not bound by any constraints thus making their explanations systematically irrational. Heaton & Rosenberg (2004) further explains the concept of Rubinstein that 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, he 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, and 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 which 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 markets 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. Ray (2006) examines a new genre of behavioral markets "prediction markets" and their remarkable ability to aggregate inside and expert information from around the world in order to accurately predict all types of economic and financial variables. To date it is said that the prediction markets are the most accurately efficient markets as they prove to show all three forms of market efficiency (weak, semi-strong, and strong), in contrast to regulated markets. Prediction markets are also said to be "decision markets". It initially evolved in 1988 with the first online betting market the Iowa Electronic Market. These online markets have proven their predictions accurately since the time they came into being. To be precise these prediction markets are behavioral markets with powerful statistical components that are able to predict the most likely values of future financial variables, variances around such values, and their correlations with other future financial variables. Ray (2006) says that being unregulated, prediction markets are highly effective at flushing out and thereafter aggregating relevant information including inside and expert information regarding a particular event, globally extracting such information from savvy bettors who are eager to profit from their inside and expert information. These sorts of prediction markets have become so popular that now a day's major companies use such behavioral markets to accurately forecast sales, earnings, product success, and many other financial and economic variables. The foremost tool for these markets is the wisdom of crowd. In order to accurately predict financial and economical variables he presented few conditions as a prerequisite, which included mainly having a variety of opinions, with no herd behavior, should be able to use their knowledge according to the information available with them and last but not the least is the fact that prediction markets expectations are not self fulfilling prophecies. Prediction markets are a new genre of behavioral markets that continually reveal the thinking of confident insiders by suggesting them to profit from their inside and expert information. The subjective evidence with a few statistical evidences corroborates the impressive ability of these markets to predict financial events of all types. The phenomenon exists from ages and effectively proves its performance especially in world's financial markets. The demonstrated accuracy of predictions in these markets can be of significant utility to traders, financial analysts, behavioral analysts, and many others intending to forecast and analyze financial data.

A person's tendency to make errors is known as cognitive bias. These errors are based on the cognitive factors that include statistical judgments, social attribution and memory being common to all the humans in the world. "Cognitive bias is the tendency of intelligent, well-informed people to consistently do the wrong thing". Crowell (1994, pp. 1). The reason behind this cognitive bias is that the Human brain is made for interpersonal relationships' and not for processing statistics. He discussed the frailty of forecasts. Generally it is said that the world is divided into two groups: People forecasting positively and people forecasting 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. History proves it that many of cognitive biases in human judgment value uncertainly will change; they may be convinced if given proper instructions, on the part-experience of irrational behavior. The three most common themes of behavioral finance are as follows: Heuristics, Framing and Market Inefficiencies. People when decide on the basis of the rules of thumb regardless of rationalizing suffer from Heuristics. Some forms of Heuristics are: Prospect theory, Loss Aversion, Status quo Bias, Gamblers Fallacy[9], Self-serving bias and lastly Money illusion. Framing is basically a problem of decision making where the decision is based on the point where there is difference in how the case is presented to the decision maker. Cognitive framing, Mental accounting and Anchoring are the common forms of Framing

3. Market Inefficiencies

As observed, that market outcomes are totally opposite to rational expectations and efficient market hypothesis where mispricing, irrational decision making and return anomalies are examples of it. Fung (2006) introduced three forms of market efficiency earlier presented by Fama in 1970. In the weak form, the information set con­tains only historical prices. In the semi strong form, information set contains all publicly available information. In the strong form, the infor­mation contains not only all publicly available information but also insider information not available to the public. This definition of efficient mar­kets is too general to be testable empirically. To make the model testable, he proposed a process of price formation known as the expected re­turn or fair game efficient markets model. In this model, when investors form expectations of security prices, they fully utilize all the information that is fully reflected in those prices. It is called a "fair game" model, because using only the information that is fully reflected in security prices, no trading system can have expected profits or returns in excess of equi­librium expected profits or returns. These terms have been described as specific market anomaly from a behavioral point of view.

Anomaly (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)

Efficiency wage hypothesis Limits to arbitrage Dividend puzzle Equity premium puzzle

Behavioral Economic Models are restricted to a certain observed market anomaly and it adjusts the neo classical models by explaining the phenomenon of Heuristics and framing to the decision makers. It is usually said that economics get along with in the neo classical framework, with just one restriction of the assumption of rationality. Loix et. Al (2005) 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 and amassing debt, and gave 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 and 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, (2006) in his article talked about the co-evolution of neo-classical and behavior finance that in 1937 when A. Samuelsson one of the great economists wrote about people maximizing the present value of utility subject to a present value. Another judgment he realized was time being consistent human behavior "where if at any time t,

"0 < t < b" (Shiller, 2006, pp.3,). Where people reconsidered the problem of maximization from that date forward and they would not change their decision where as in real life it is totally opposite. 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.

4. Investing and Cognitive Bias

Money Managers and Money management is a very popular phenomenon. The performance in a stock market is measured at daily basis and waiting 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, 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 he 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 other related to behavior. As the assets under management of an advisor grow, universe of potential stocks shrinks. Analyzing why individual and professional investors do not change their behavior even when they face empirical evidence, 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 collective basis, where everyone else also had made a mistake, the consequences professionally and for one's own self-esteem are far less damaging than if a person is wrong alone. The herd instinct allows for comfort of safety in numbers. The other reason is that individuals try to behave 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 traditional view of investment management, fundamental forces drive markets, however many other investment firms are consider being active and basing their working on their experienced Judgment. It is also believed that Judgmental overrides value and fundamental forces of markets can be lethal as well as a cause of financial disappointment. Historically it has been found that people override at wrong times and in most cases would be better off sticking to their investment disciplines and the reason to this behavior is the cognitive bias. According to Crowell (1994) and many other researchers, stocks of small companies with low price/book ratios provide excess returns. Therefore, given a choice among small cheap stocks and large high priced stocks, prominent investors (financial analysts, senior company executives and company directors) will certainly prefer 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.

The assumptions made by Crowell (1994, pp.2) were 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. Whereas the results Crowell`s survey were contrary stating that Long Term Investment had a positive correlation with size and with Price/Book stocks. Crowell further stated that 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. Discussing the concept of regrets, aversion to regret is different from aversion to risk; Regret is acute when an 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, two major Cognitive errors appear: "We have a double cognitive error: good company always makes good stock (representativeness), and involves less responsibility(Less aversion to regret)". (Crowell, 1994,pp.3) The Anti Cognitive bias actions would be admitting to your owned stocks, admitting earlier investment mistakes. Further, taking the responsibility for actions to improve their performance in future. The reasons for all the available disciplines, tools, and quantitative techniques is to deal with Cognitive bias error, where quantitative investment techniques enables investment managers to overcome cognitive bias, follow sound investment, and eventually be successful contrarian investor(one who rejects a majority opinion, as in economic matters). Behavioral finance also is very helpful in understanding justifying government involvement in investing decisions of individuals. The failure of millions of people to save properly for their future is also a core focus of behavioral finance. With the help of two very important examples Shiller in (2006) 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(GBP). The Parents were to choose among a number of investment alternatives to invest until child comes of age. This is in effect done in order to make the parents feel connected with investments and modern economy. Another example: as it is suggested that every single person 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.(Shiller, 2006, p.6, para. 1)

In 2005 president Bush also announced one such plan for personal account "life - cycle fund" which would be among an 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 that human attention is capricious, focuses heavily some times on financial calculations and is subject to distraction and dissipation of default option is central. All this brings us a question that what should an intertemporal optimizer[10] do to manage his portfolio over the lifetime. According to Shiller (2006) Samuelson stated that someone who wished to maximize the expected value of his intertemporal utility function by managing 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 appropriate theoretical framework for considering what people ought to do with the portfolio. Behavioral finance is beginning to play an important role in public policy such as in social security reforms.

5. Agents Rationality

Selective attention exhibited by a human mind is a concept of culture. Every nation, tribe or social group has a social cognition reinforced by conversation ritual and symbols, rituals and supposition of a particular nation has a subtle but strong reliability effect on human behavior. To researchers the unique customs of people basically appears as a logical outcome of a belief system of a nation group of people. The Cultural factors were one of the major influences on rational or irrational behavior. Many factors that are same across countries , e.g fashion, music, movies, youthful rebellious, other than these we find more factors internationally similar human behaviors then just rational reactions. Therefore as Shiller (2002) says that it is a difficult job in order to decide the avenues of global culture and the influences it exerts.

Sandroni (2004) wrote an article on efficiency of markets and the Bayesian rule where he presents a long standing assumption, where two possible situations have been clearly examined. Relaxing the assumption that agents form beliefs according to the laws of probability and assume a simple heuristic and also that agent's process information according to the Bayes Rule, but are lack of sufficient information in order to generate a 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 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 structure of the economy to hold correct beliefs.

According to 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 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 laws of probability. Past research 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" Sandroni (2005, pp. 744). In order to better understand the situation we must compare 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).

According to Kenourgios et. Pavlidis (2004) the classical analysis of financial analysts viewed them as rational market experts who immediately and without bias incorporated information into their earnings forecasts and made trade recommendations. This assumption presumed that analyst' forecasted earnings immediately, are unbiased and incorporates all new information. However, most of the research on financial analysts' behavior documents a systematic misinterpretation to earnings information. Some studies conclude that analysts systematically overreact to new information, while more recent studies provide evidence of systematic under reaction.

Sandroni (2004) further classifies the fundamental structure of assets into two groups, Learnable: When available data reveals the true probability of dividends with near certainty (history becomes the perfect guide) and Unlearnable: When available data cannot reveal the true probability of the dividends. Here the history can never be a perfect guide. When fundamental structure of an 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 survive. According to Sandroni (2004) it is near to impossible to drive a Bayesian agent away from the market because Bayesian agents will always find a way to stay in the market and influence prices. The facts explain a situation where Agents with belief based on inconsistent estimators are driven out of market agents failing to understand the fundamental structure of asset vanish and so asset prices are eventually determined by agents rational expectations. overconfident and one parameter non economical Agents survive where agents forecasts arbitrarily close to the forecasts of the Bayesian agents and 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 and permits their survival. One Dimension Non Parsimonious Agents are driven out of Market (These will eventually learn the true parameters but they will vanish from the economy).

When fundamental structure of an 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 and 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 and under reaction, overconfidence were used to distinguish Non Bayesian estimators from the Bayesian benchmarks. 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 market by Non Bayesian agents: Following that agents whose beliefs are based on estimators of good predictability, are driven out of 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 Market.

5.1 Self is not Neutral and Agents Behave Irrationally

Gao and Schmidt (2005) discussed the same concept of agents rationality. According to him, it was a very common mistake of agents being always rational, as agents often make choices that they do not actually long for and want 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 which man is an unbiased Bayesian forecaster always serious minded and never subject to psychological effects. 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. 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 basic starts here where no one 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 their self- value that is either consciously or unconsciously.

5.2 Theory of Self-Value

Real economic agents are not expected utility maximizes and 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 maximize. 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. Humans' rationality includes limitation on information acquiring, processing computational cap ability, organization and utilization of memory. The Problem of indecision utility and the concept of self-value.

5.3 Self is Relative

Man is a social animal and so 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 but rather in relative terms. Sandroni, (2004) proposes that 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 case is vice- versa Self is illusory. As it is known individuals are unable to understand them 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 to 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, they highly rate what they already have which brings us in a better position to understand the kind of irrational behavior.

5.4 Disposition Effect and Self Value

Gao and Schmidt (2005) 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 they sell losers early they would realize loss, eventually portraying a wrong decision. It found a 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 changes in stock performers could have higher impact on people with low trading account and low income than wealthier people.

6. Biases

Bias describes a tendency towards a particular idea or result, when this tendency interferes with the ability to be unbiased and evenhanded. In other words, bias can be termed as 'one-sided' perspective. It describes an approach, decision, or behavior that is influenced by a prejudice. Bias can be insensible or mindful in awareness. A cognitive bias is the difference in judgment that occurs in particular situations. Cognitive biases are examples of aroused mental behavior. There are many types of cognitive biases that include confirmation bias, herding, hindsight, anchoring, representativeness, overreaction, overconfidence etc. It has been proved empirically that these cognitive biases exist and occur 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 himself without bias, second cognitive dissonance (Impression management and Self-perception theory), Thirdly Heuristics including: Adaptive bias, Misinterpretations or misuse of statistics. Availability Heuristics are the memories readily available based on clear, unusual or emotionally charged evidences. Representative Heuristic is moderating the probabilities on the basis of similarity. Affect Heuristics is when a person base his decision on an emotional reaction rather than accurate calculation of risks and benefits

6.1 Overconfidence

Starting with Overconfidence, Glaser et al (2003) found evidence that overconfidence can manifest itself in the following form: People overestimate their abilities and think themselves to be above average (better than average effect). Assuming that they can control random tasks, by being optimistic about the future (Illusion of control and unrealistic optimism). Kahneman and Riepe in 1998 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". Glaser et al. (2003, pp. 12). Shiller (2002) states that people generally tend to believe that their knowledge is the best, and they are very confident about their own judgments. 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 Glaser et al (2003) explains the phenomenon of overconfidence by Barber and Odean 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 precision of information or the underestimation of variance of information signals. Some models assume that degree of overconfidence changes over time and 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. Historically 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 and gender. There are two types of overconfidence: Overconfidence in one's own knowledge, Overconfidence in one's own ability. Overconfidence in one's own knowledge can be proven experimentally by giving test subjects general knowledge questions or subsequently asking 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 and 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 predictions on specific information of stock ignoring unreliability of information, whereas common people used simple and general heuristics based on past price movements. It also discusses expert professionals actually know how about stocks and their future and to an 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 who states: "As a simple linear model provides a more accurate prediction than experts" Torngren et Montgomery (2004, pp. 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 psychologists is that people are overconfident in their judgments 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. Greater the trading volume, poorer the returns will be. 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 previous month's data as well as their judgment thus it is proven that benefit of experience knowledge by experts is overreacted but in reality experts have no advantage over laypeople. In short both groups displayed overconfidence and it was more evident among the professionals. Also that the information based on 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 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 that 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 overconfidence phenomena. Olaf and Rudiger (2005). Therefore, confirming the point that Perception of control significantly influences level of overconfidence. Stronger the perception of control, higher the level of confidence will be. The study suggests that analysts should consciously confer to the overconfidence phenomenon and take steps towards improving the quality of their forecasts, have to be confident without being overconfident. The results of study confirmed the assumptions that overconfidence is more pronounced for earnings forecast then price forecasts. Also when their price forecasts are compared with 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 "Stronger the perception of control, more overconfidence should be observed." Olaf and Rudiger, (2005, P. 122). Fisher and Statman (2000) points out that bolder forecaster might be overconfident and Regression analyses are a good a remedy for overconfidence.

According to the traditional psychologists, overconfidence is a phenomenon in which subjects are asked to answer factual questions in a variety of subject domains, and secondly predict the out­come of an upcoming event. Besides making deci­sions, subjects estimate the probability (or give odds) that their answers are correct. Psychologists compare actual rate at which subjects are correct with their predictions of being correct (their confidence). It is found that subjects are generally overconfident, i.e., they overestimate their accuracy in answering ques­tions. Many psychologists suggest that overconfidence re­lates to a person's ability to process information. Allen and Evans (2006) found that initially Griffin and Tversky claimed that overconfidence originated in people's biased evaluation of evidence. Evidence is said to have two dimensions: strength and weight. Strength refers to the farthest point of the evidence (e.g., someone forecasts an event as highly unlikely to occur), while weight refers to the predictive soundness of the evi­dence (e.g., the accuracy of the forecasting model or the credibility of the recommender). Further suggested that overconfident people tend to fo­cus on strength of evidence and then adjust it in­adequately for its weight. When strength is high but weight is low, people tend to be overconfident. When strength is low but weight is high, they tend to be under confident.

Allen and Evans (2006) suggested that less com­petent individuals have trouble judging their compe­tence, leading them to overestimate their ability. Self-attribution bias is an explanation of overconfidence a trait that appears when people point their successful outcomes to their own abilities and their failures to external factors. The more successful one has been, the more self-attributing and overconfident one becomes. Overconfidence is consistently associated with limitations or biases in information processing. Several researchers have investigated analytically the extent to which overconfident traders might persist in financial markets and their impact on market out­comes. Traditional financial models imply that rational traders should drive overconfident traders out of the market. But these analytical studies show that overcon­fident traders can indeed survive in markets, and may even dominate them and also that overconfident traders hold more risky assets in their portfolios that would be pre­dicted to maximize utility, earning them the higher re­turns associated with higher-risk assets. According to another researcher overconfidence is a trader's belief that his infor­mation is more accurate than it actually is. And that overconfident traders trade more frequently than ratio­. An overconfident trader will update his beliefs with bias, overweighting his signal interpretation successes and underweighting his failures. They demonstrate that fre­quent, quick, and clear market feedback can reduce overconfidence because it allows traders to learn to judge their abilities more quickly. It is also said that overconfident traders bid more aggressively than rational traders be­cause they overestimate the expected payoff and un­derestimate variance of their trading strategies. Traders' aggressive bidding makes them better able to exploit any risky profit opportunities and any mispricing caused by liquidity and noise traders. It also earns them higher profits—but at the expense of lower expected utility.

6.2 Rumors

Rumors have a strong impact on contemporary business and economic environments. Life cycle 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, companies have to face major losses because of spread of false rumors. (Further Kimmel, 2004) discussed the issue of how and why these rumors 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 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 person who delivers the information; reliability of the source providing information and repetition. Financial rumors are believed to spread as a 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 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 bear markets as oppose 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 impacts the emotion of 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 to assess the presence of rumors and also monitor firm's acts that are likely to generate rumors. A 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 aforementioned strategies, financial marketplace can insulate itself from a number of variables that are likely to affect its sound stability.

6.3 Herding

Herd Behavior explains the tendency of people acting together in a group without planned directions. The term refers to human behavior during activities of stock market crashes and Bubbles, Religious gathering, Festivals, sporting events, street demonstrations and also in the day to day decision making process and forming an opinion. According to Scahrfstein and stein (1990) Herd behavior may arise from a variety of contexts, as a result of manager's efforts to enhance their reputation in the market. Other than reputational factors there are many other factors affecting the behavior of money managers, e.g correlated prediction errors lead to sharing blame effect that drives managers to herd. Investors may be reluctant to act according to their own information and beliefs, fearing that their contrarian behavior will damage their reputations as sensible decision makers. As Keynes suggested, that professional managers will "follow the herd" if they are concerned about how others will assess their ability to make sound judgments. Scharfstein and stein, (1990) developed a clear understanding of some of the forces that can lead to herd behavior. It is said that under certain circumstances, mangers simply mimic the investment decisions of other managers ignoring substantive private information. Although this behavior is inefficient from a social standpoint, it could be rational from manager's perspective, concerned about their reputation in labor market. Thus sharing the blame effect arises because smart managers tend to receive correlated signals (since they are all observing a piece of the same truth), while dumb ones do not (observing simply correlated noise. Consequently, if one manager mimics the behavior of others, this suggests to labor market that he has received a signal that is correlated with theirs and is more likely to be smart. In contrast, a manger who takes a contrarian position is perceived as more likely to be dumb, ceteris Paribas. Thus even if a manager's private information tells him that an investment has a negative expected value, he may pursue before other do. Conversely, he may refuse investments that he perceives as having positive expected value if others before him have also done so. Managers who care about their reputation will always herd whereas other concerned about profits would look for tradeoffs.

Scharfstein and stein further explains that herd behavior by money managers could provide partial explanation for excessive stock market volatility. By mimicking others behavior (buying when others are buying and selling when others are selling) rather than responding to their private information, members of herd will tend to amplify exogenous stock prices shocks. Since there is presumably more uncertainty about the abilities of younger managers, thus the committee should be made of young and old executives, and there young ones should be asked to voice their opinions before old ones. Herding is more likely to be a problem when managers outside opportunities are relatively unattractive, and when compensation depends on absolute rather than relative ability assessments. 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 companies collect huge sums of money and reinvest in other companies like Banks, Insurance companies, pension funds, retirement funds and mutual funds. Their task is to act as specialized investors on other peoples behalf. Moreover, these institutional investors have the resources to buy and sell shares, so they can play a vital role in which companies stay in the chips, influencing conduct of other listed companies and last but not the least is to provide them with capital, are the job description of Investment management firms. They technically face low transaction costs and a balanced portfolio. From the empirical results we find that these investors mostly fail to achieve market developments, no matter what kind of fund they manage which is eye-opening, as generally it is expected the institutional investors are sophisticated, experienced and well- informed. Kimmel (2004) gives the possible explanation for 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 acts as an agent for the client which 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, pp. 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 would again cause strategic behavior of herding, where they try to be either equally good as their peers or try to be better than peers. Furthermore it is found that herding managers are successful in finding and sharing blame and hide in the herd when their decisions appear to be unprofitable." It is said that 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 age, as when managers become old they are more experienced, established and tend to make bolder forecasts to manipulate the assessments of their ability. Evidences are found for the reputational herd 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.

Lutje carried a survey in 2003 with total of 263 respondents and based his findings on reputational herding, working efforts, sources of information and investment horizon (their risk taking behavior and the Herd behavior in tournament Scenarios). The results somewhat supported the hypothesis that were created 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 disposition effect. Interestingly, the survey provides strong evidence that herding managers are generally more risk averse, whereas in the later they seem to agree to take higher risk. We ascribe this finding as their fear of falling out from the herd. Therefore the survey concludes that herding is induced by career concerns, as asset managers working effort is not monitored by client but just by his supervisors; he has some opportunity to reduce his working hours. Also that 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 herding managers focus on short term investments' than non-herding managers. According to self - assessment herding managers consider themselves as more risk averse. But we must take into the account bias that self assessment can deviate from actual risk taking behavior. Whereas to analyze this risk taking behavior we further divide risk into two main factors: a) Loss aversion (Being more sensitive to losses than gains, while loss aversion only considers investment behavior regarding losses, disposition effect will take care of profits) Results confirm the hypothesis that Herding Managers are more loss averse. B) Disposition effect (to ride 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 period, managers are biased towards taking less risk in case of outperformance. Shiller (1995) "Rhetoric and Economic Behavior Conversation, information and Herd behavior" discussed herding as a bias where People sharing same geographical background, cultural and sociological ideas generally behave similarly. The tendency X for people in groups to think and behave similarly is psychological motivation. Herd behavior is an outcome of no hard and fast rules or facts rather subtle matters (depending upon variety of thoughts, time, and intelligence of individuals). 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 social pressures where people rational take into account others information based on interpretation. An example might clearly state the concept e.g a group of people are asked a question to which answer seems to be an obvious one and 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. Shiller (1995, pp. 182) explains psychology of human as Asch in 1952 states: "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 and I alone right". Thereby, explaining irrational efforts of investors to interpret conflicting evidence. Further Shiller explains the phenomenon of Herd Behavior with the help of drugs, alcohol, cigarette and 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 important facts, common assumption and 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 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 dominated by ordinary face to face personal conversation. One of the reasons of media appearing to be comparatively less effective in transmitting correct information is because it's a medium of ordinary interpersonal conversation and people respond emotionally. Shiller (1995) Different groups have different conversation patterns as well as circumstances promoting informational cascades. The reason for differences in mass behavior among different groups is due to difference in transmission of information. The difference of transmitting information among group must be due to differences in initial conditions and opinions of that group. Conversation patterns may also vary across groups in terms of habits of reviewing source of information.

The framing effect is presenting the same option in a different style can change people's decisions. Individuals have a tendency to select unpredictable choices, depending on the framing of the question. Framing impacts people, because individual's perception varies on the concept of losses and gains. Loss aversion is an underlying variable to the framing effect that is the Value function that is initially found in the Prospect theory stating that a loss is more disturbing than the gain is gratifying. Therefore, people avoid risk in a positive framed situation but seeks risk in a negative framed situation. Certainty and pseudo certainty effects (in which a sure gain is favored to a probabilistic gain are also not worth ignoring as they contribute to the phenomenon of Framing. Where people make risk averse choices if the expected result is positive but make risk seeking choice if the expected result is negative.

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. Investigated 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 have an impact on the trading behaviors. "Moreover, positively and negatively framed information leads to a particular trading pattern, but leaves trading prices and trading volume unaffected". Kirchler et al. (2005, pp. 91). The findings also supported the disposition effect where the people sold their assets more rapidly who experienced a gain than those who experienced a loss. This effect is further mediated by framing: Positively framed market participants take time in selling their assets 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 assumption is frequently violated in individual decision making. In 2000, Weber, Keppe, and Meyer-Delius (Kirchler et al, 2005) investigated the effect of "endowment framing on the 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, they found that overpricing 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 patterns. Besides both framed information (positive and negative) leads to a specific trading pattern, where 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 took time in selling their assets 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, the 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.

6.5 Over and Under Reactions

Under reaction It is a situation where individuals fails to react completely and immediately to new information: under reaction is often related 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) presented 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.

Under Short term condition markets under react and in long term conditions the market generally has overreaction. The study aims to reconcile short term under reaction with long term overreaction in the quarterly earnings announcement frame work. 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. He further takes the evidence of investor's misreaction regarding earning information and finds 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. 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 many models have integrated both the phenomena together. It also has been found in a model by Hirshleifer and Manyam in 1988 (Kaestner, 2006) where over reaction is due to over confidence where as self attribution causes under reaction. Also by integration of 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 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 misreact 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 leading to overreaction 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.

Kenourgios et. Pavlidis (2004) specifically studied two forms of overreaction: (1) generalized overreaction, where changes in forecasted earnings are overly extreme; and (2) overreaction to prior changes in earnings. Their evidence supported the generalized overreaction and rejects overreaction/under reaction to prior performance and did not support either the overreaction due to small firm size or the prior expectation about the overreaction for high P/E ratio companies and the higher overreaction regarding the forecasting horizon. Further they explained the 'winner-loser' effect and interpreted as investors' irrational behavior suggesting that they overreact, that excessive optimism or pessimism causes prices to be driven too high or too low from their fundamental values, and that overreaction is corrected in a subsequent period. In forming expectations, investors give too much weight to the past performance of firms and too little to the fact that performance tends to mean-revert. They also suggested the fact an investor can earn abnormal profit by buying past losers and selling past winners short (a contrarian investment strategy using past prices as the information set) has important implications for the validity of efficient market hypothesis (EMH). Their results indicate that predicted earnings changes are greater than actual earnings changes, implying that market professionals overreact to changes in earnings figures. Moreover, the extent of overreaction in analysts' earnings forecasts increases with the length of the forecast horizon, because overreaction increases with uncertainty and the uncertainty is greater over longer horizons. Another researcher argues that losers tend to be smaller than winners and when size is controlled there is no significant difference in test period performance. The results indicate that when losers are smaller, they outperform the winners. When winners are smaller, they outperform the losers

Kenourgios et. Pavlidis, (2004) tested two forms of overreaction (generalized overreaction and overreaction to prior earnings) in relation to three aspects of analysts' information environment (forecast horizons, firm size and P/E ratio). The results based on both models did not support the overreaction due to small firm effect, the prior expectation about the overreaction for high price/earnings ratio companies and higher would be the overreaction regarding the forecasting perspective. There are two potential reasons given that may explain the results regarding the overreaction of analysts. First, there may be "institutional reasons" that trigger the reported overreaction. Analysts employed in brokerage firms probably report overoptimistic forecasts, in order to make their customers to increase the volume of trade, and as a result to increase brokerage firm's profitability. The second reason is related to private information. Some of the listed companies employ analysts who trade their stocks on their behalf. These analysts are considered to have private information.

De Bondt and Thaler (Fung, 2006) proposed a stock market overreaction hypothesis: Waves of optimism and pessimism make stock prices swing temporarily from their funda­mental values (the present value of the stream of future cash flows asso­ciated with the stocks). They also suggested two other hypotheses that result from their overreaction hypothesis: (1) Extreme movements in stock prices will be followed by subsequent price movements in the opposite direction. (2) The more acute the original price movement, greater will be the subsequent adjustment. Both hypotheses imply a violation of weak-form market efficiency". This is be­cause the overreaction hypothesis implies that returns in excess of equi­librium returns can be earned by investing in stocks that, at portfolio formation time, have performed more poorly than average. To test the overreaction hypothesis, De Bondt and Thaler (Fung, 2006) classified the common stocks in their database into winner (W) and loser (L) port­folios based on their performance in the previous three years. Perfor­mance is measured by residual returns, defined as the monthly return of the stock in question minus the monthly return of the market index (a measure of average return). If the residual return for a stock is positive, the stock has earned an above-average return, and if it is negative, the stock has earned a below-average return. According to Fama's defini­tion of market efficiency, no trading system or strategy can result in positive residual returns. On the other hand, the overreaction hypothesis suggests that a strategy of selecting stocks that are losers in the previous three years will earn above-average returns, because the extreme de­pression of their stock prices in the previous three years will be fol­lowed by extreme appreciation in the next three years. Thus, the stocks in the loser portfolio should have positive residual returns in the next three years, while the stocks in the winner portfolio should have nega­tive residual returns in the next three years.

6.6 Confirmation Bias

According to Fisher and Statman (2000) the illusion of validity persists because people fall for the confirmation bias "Focusing on the information that is consistent with the beliefs, neglecting inconsistent information". Fisher and Statman, (2006,pp .3) The confirmation bias is common. As it is said that people are terribly good at feeling themselves above average, they are sure about the answer and do not want to confuse with the other dock. The only remedy for the bias is examining all data confirming as well as disconfirming Anchoring. Anchoring is basically the humans propensity to rely too heavily on one trait "anchor" or information while deciding. Usually once the anchor is set, there is a bias towards that value. Shiller, (2002) observed that there may be sometime a rational phenomenon for respondents. Anchoring has an information response component in many circumstances; it exists even when certain information regarding some event is missing. People may object that the concept of anchoring on past prices determines the present and future prices in the stock market must be not in agreement with the low serial correlation of stock price changes. It is said that as the value of a commodity gets ambiguous the more important a suggestion is likely to be and higher the chances of anchoring occurs 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.

6.7 Hind Sight Bias

Hind sight bias leads people to exaggerate the quality of their foresight. It also is a serious problem for all historians, including stock market historians. 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 their 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, where as these statistical tools have pitfalls of their own, pitfalls that require careful applications and judicious interpretations. However organizational tools can supplement statistical tools in alleviating cognitive bias.

6.8 Regret and Cognitive Dissonance

Regret and cognitive dissonance is human phenomena of repenting on doing something wrong or taking wrong decision. In order to get over with the soreness of regret, a person may alter the 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 and Statman (2006, p. 7). There are many ways of showing and proving the behavior of individuals suffering from regret, but a general concept is having a bend in the value function at the reference point. According to a research by (Shefrin and Startmen, 1985) Shiller (2002) investor's delay selling of stocks that have gone down in value whereas they speed up selling of stocks that have shown a positive growth, in order to (overcome the regret). Whereas cognitive dissonance is the mental conflict between different alternatives available with proofs that their assumptions are wrong so it's regret over mistake belief. The regret and cognitive dissonance theory explains that there is a propensity for people to take remedy measures to reduce cognitive dissonance that would normally be completely rational. People may avoid the available information or develop twisted arguments to maintain self beliefs and assumptions. It has been proved in the past that people often make the errors that are represented by the cognitive dissonance theory. When investors loose funds they are unwilling to find the evidence that they make a investment by selling their investment.

6.9 The Disjunction Effect

It is the ability to want to wait in order to decide until the information is revealed even if its not important. Regardless of the fact that their decision would change, based on this information. Shiller, (2002) Opposed 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 somehow the result appears to be not as good as they wanted, they would try to recapitulate their losses, but if the outcome is unknown they do not have sound grounds to accept the latter option. It also might explain changes that sometimes with a low instability and low volumes of trade just before important information is revealed or an announcement made. Shefrin and Tversky in 1992 (Shiller, 2002) gave examples of presidential elections including stock market volatility, when the outcome of election is known.

6.10 Gambling Behavior and Guesswork

Shiller (2001) presented his ideas of humans gambling in the financial markets. He argued thatHuman behavior of playing games generally sharpens the qualities of risk taking among lay people. It prevails in all the cultures of the world and indicates a basic human trail. The ability of people to gamble brings up a dilemma for the theory of human behavior under certainty. There are mainly two types of behaviors. Risk avoiding and Risk loving. Gambler is not a systematic risk seeker 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. They may have very rational and logical prospect at some level for the possible outcome of their gamble. Whereas, economists only talk about quantitative expectation, as that is the only characterization result.

6.11 Magical Thinking and Quasi - Magical Thinking

It can be regarded as a specific behavior pointed out by Skinner in 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 have a perception as if they can change the predetermined conditions. Quasi Magical thinking appears to support and operate much more strongly and rigidly when the outcome of future event is discussed rather than the history. Therefore stated that Quasi- magical phenomenon is unable to provide evidence of strictly rational behavior

6.12 Mental Compartments

Like all other phenomenon, mental components refer to human's ability 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, individual look at small decision separately. It is agreed that investors place their investments into separate mental components. Shefrin and Thaler (Shiller, 2001) categorized peoples sources of incomes into these types, Current wage, Asset Income and future income. The way of spending variates from person to person is the 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 end of the year a time of estimation and new year as a new start. They may be inclined to behave differently at the terms of the year end this may explain the "January effect[11]".

6.13 Representative Bias

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 and sequences, in financial performance operationalize representativeness, Chan et al. (2002) Investigating the past trends and 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 and 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. (2002) 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 operationalizing 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 utilize known facts as the initial step from where then the inferences are drawn or conclusions about something unknown and causes 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.

7. Conclusion and Recommendations

Behavioral finance is a young enterprise and on its way to proving its usefulness. Steming as a part or psychology and influencing financial market behaviors, it explains human behaviors and the biases. Since it deals with humans emotion, sentiments, and their biases, it also helps to identify past practices of investors and also determines the future. . The classical models of finance generally talked about the specific finance behaviors such as taxation, savings, gambling, and amassing debt. In this paper the Non Specific financial behaviors have been analyzed. The classical assumption that agents are rational has been greatly challenged by the Behavioral finance framework. Behavioral Finance framework declares that agents are not always completely rational. It is said that if financial markets consisted of only rational agents then there would have been no trading. Therefore, agents are closer to the real life, experimental markets rather than the theoretical laws presented by the classical MPT (Modern Portfolio Theory). Agents behave irrationally, are not neutral and sometimes take decisions that are actually not desired by them. The reasons for these irrationalities are the cognitive biases that include Overconfidence, Over and Under reaction, Framing, Herding, Gambling, Hindsight and Representativeness. These biases influence the behavior of human on individual as well as collective basis. To be more precise, it is further suggested to come up with new financial models based on behavioral finance assumptions of decision making, and to prove that these new models win over the models presented by the standard theory of finance. Further, it is also important to find out weaknesses of the efficient market theory which paints a picture of an ideal world. The relevance of orientation towards finance and the consumer behavior is also a very interesting path for research to follow.

[1] An investment theory that states it is impossible to "beat the market" because stock market efficiency causes existing share prices to always incorporate and reflect all relevant information. According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices

[2] The extent to which the value of a security or other investment may increase beyond forecast levels. The opposite of downside risk

[3] An estimation of a security's potential to suffer a decline in price if the market conditions turn bad

[4] The theory that the price of a given security, commodity or asset will have the same price when exchange rates are taken into consideration. The law of one price is another way of stating the concept of purchasing power parity.

[5] Arbitrageurs are typically very experienced investors since arbitrage opportunities are difficult to find and require relativelyfast trading.Arbitrageurs also play an important role in the operation of capital markets, as their efforts in exploiting price inefficiencies keep prices more accurate than they otherwise would be

[6] An ownership society values responsibility, liberty, and property. Individuals are empowered by freeing them from dependence on government handouts and making them owners instead, in control of their own lives and destinies. In the ownership society, patients control their own health care, parents control their own children's education, and workers control their retirement savings.

[7] A theory that peoplevaluegains andlosses differently and, as such, will base decisions on perceived gains rather than perceived losses. Thus, if a person were given two equal choices, one expressed in terms of possible gains and the other in possible losses, people would choose the former

[8] In the philosophy of science, the view that concepts and theories are merely useful instruments whose worth is measured not by whether the concepts and theories are true or false (or correctly depict reality), but how effective they are in explaining and predicting phenomena.

[9] Whenan individualerroneouslybelieves that the onset ofa certain random event is less likely to happen following an event or a series of events. This line of thinking isincorrect because past events do not change the probability that certain events will occur in the future

[10] An economic termdescribing how an individual's current decisions affect what options become available in the future. Theoretically, bynot consumingtoday, consumption levelscould increasessignificantly in the future, and vice versa.

[11] A general increase in stock prices during the month of January. This rally is generally attributed to an increase in buying, which follows the drop in price that typically happens in December when investors, seeking to create tax losses to offset capital gains, prompt a sell-off.