The efficient market hypothesis and behavioral finance

The efficient market hypothesis is directly related to the behaviour of prices in asset markets. Initially the term ‘efficient market’ applied only to the stock market, but later it was generalised to other asset markets. The efficient market hypothesis is seen as the turning point of the modern finance (Fama, 1965) and in his classic paper, Fama (1970) defined efficient market as one in which “security always fully reflect the available information” [p.383]. Market efficiency is known as the speed and accuracy where the current market prices reflect the investor expectations. When the market is efficient, all the available information is fully and automatically reflected in the price, gaining profit by using this information is seen impossible. Efficient market hypothesis predicts that market price should incorporate all available information at any point in time.

According to Pesaran, Hashem M (2010) “The efficient market hypothesis (EMH) evolved in the 1960’s from the random walk theory of asset prices advanced by Samuelson (1965). Samuelson showed that in an informationally efficient market hypothesis, price changes must be unforecastable. Kendall (1953), Cowles (1960), Osborne (1959), Osborne (1962), and many others had already provided statistical evidence on the random nature of equity price changes. Samuel-son’s contribution was, however, instrumental in providing academic respectability for the hypothesis, despite the fact that the random walk model had been around for many years; having been originally discovered by Louis Bachelier, a French statistician, back in 1900.”

One important implication is that security prices will change only when there is arrival of new information that was not considered during the formation of current market prices. Yet the information will be evaluate and process this information efficiently and immediately incorporate into the security prices. The crucial questions here is the relevant information because it needs careful analysis and the conclusion about market efficiency could be there or extracted from the information set. A standard classification for different compositions or information set was outlined by Fama (1970) as weak form, semi-strong form and strong form.

On the other hand, new empirical studies of security prices have reversed some of the earlier findings related to EMH. The traditional finance school named these observation anomalies due to the unexplainable in the neoclassical framework. Due to the increasing numbers of puzzles, the new approach of behavioural finance emerged. This approach focus on the investor’s behaviour in making decision in investment. This approach assumes that agents may be unreasonable during interpreting new information and thus lead to making wrong judgement in investment.

This paper will discuss the definition and concept of efficient market hypothesis and behavior finance in general. I will be look into market issues for countries of Malaysia, USA, Africa and Jordan. I would then like to highlight the issues on this area for future research.

Efficient Market Hypothesis

Definition and Concept

The Efficient Market Hypothesis (EMH) is an investment theory that stated it is impossible to compete with the market when stock market efficiency causes existing share prices to always incorporate and reflect all relevant information. According to the EMH, stocks are always trade at their fair value on stock exchanges. Investors will face difficulties or even impossible in either purchase undervalued stocks or sell stocks for inflated prices. The possible way for investors to obtain higher returns is by purchasing riskier investment and they have to outperform the overall market through expert stock selection or market timing.

Forms of Efficient Market Hypothesis

There are three forms of Efficient Market Hypothesis where the key to all the three forms remain that is intense competition among investors to gain profit from any new information. There are three versions of EMH, namely the Weak From EMH, Semi Strong EMH and Strong EMH.

The weak form EMH is based on past history of prices where the past information is used to analyze for profit return. This method is called technical analysis. The value retrieved from technical analysis is strong and consistent. On the other hand in semi strong form, the current stock price has fully taken into consideration all publicly information that is available. However, the information in the semi strong form is available to all the investors; one is expected not to gain much profit with such information. But this form is stronger than the weak form. Whereas strong form of EMH is taking the current price fully incorporates all existing inside information, both public and private.

When the information set us limited to past price and return, the market is said to be weak-from efficient and there is correlation between current return on security and the return over a previous period. However the return is purely unpredictable from the past information. In semi strong Efficient Market Hypothesis, all publicly available information is reflected in the stock market. Investment Managers claim that mutual fund managers are skilled in analyzing publicly available information but empirical evidence do not support. Market Efficiency and security prices reflect all available information whereas new information is expected to be converted into price changes. Efficient Capital Market participants will react immediately and in an unbiased manner.

Important of Efficient Market Hypothesis

There are common misconceptions of Efficient Market Hypothesis (EMH). EMH claims that investors cannot outperform the market but there are analysts who have succeed in outperformed. So EMH is seen to be incorrect. EMH claims that one should not be expected to outperform the market predictably or consistently. EMH said that financial analysis is pointless and investors are wasting time if doing research in security price. But everyone knows that financial analyst is still needed in the market. Again EMH is found to be incorrect. EMH sees new information as always fully reflected in market places and yet prices fluctuated every day, every hour and minutes. EMH must be incorrect. EMH presumes that all investors are technically expert but in reality it is otherwise. EMH is incorrect again.

Criticism towards Efficient Market Hypothesis

There are several opinions against the EMH. First is the over reaction and under reaction of investors. EMH claims that the investor react quickly and in an unbiased manner to new information but it was contradicted to De Bont and Thaler. EMH claims that investors react very fast and in an unbiased manner when they received information but De Bond and Thaler said otherwise. They said that stock with long term past return tend to have a higher future returns and vice versa and empirical observation shows that stock prices respond to earning about a year after the announcement. Secondly, the value versus growth where value strategy is able to outperform the market consistently. Finally is the small firm effects where average return on small stocks were too large to be justified by the CAPM while the average returns on large stocks were too low.

There are also implications of Market Efficient for Investors where the EM, investors have little to gain from active management strategies; should follow passive investment strategy and no attempts to beat the market but to optimize returns through diversification and asset allocation.

Behavioral Finance

Definition and Concept

The behavioural finance is an area in finance that highlighted on the investors’ behaviour and how they make their decision in understanding the pricing of assets and also explain the decisions of investors as rational actors. The rational actors are seeking for their self-interest, given the sometimes inefficient nature of the market.

EMH revolves around the preferences and behaviour. Psychologist and also experiment economics found out that there is a departure from the normal paradigm of the investors in making their investments. Behaviour finance emerged since 1980 where it incorporates more behaviour science into finance decision making. Due to the excess volatility, dividend puzzle, equity premium and future returns in the capital market is seen as consistent in an efficient market but the truth is inconsistency do happen. According to behaviour finance good year performance may not lead to another good year but it could be otherwise.

Issues in Behavioral Finance

Behavioral finance has emerged due to the problems faced in the traditional theory in explaining why some financial phenomena happened. It is said that agents may be irrational in with their own reactions to new information and investment decisions. To undo mispricing created by the irrational investors may be difficult. Due to that, market is seen to inefficient. Psychological sees these in many views.

People make mistakes when they perceive information and form their belief. Extensive evidence shows that individuals are overconfident in their judgement (Odean (1998), Barber & ODean (2001)). When investors are overconfident, they tend to invest more and intensively. Due to greed, overconfident and also overreact to new information, investors would tend to make heavy losses. What make it difficult it when investors stick to their own conclusion interpreting the information. Once people have formed an opinion, they often stick to it and inadequately update their beliefs in the lieu of new information (Edwards (1968)). Human emotions and moods are also said to influence investors’ behavior. When investors are in the good mood they are willing to take higher risks compared to when they are in bad mood. In fact market returns are found to be higher on days of good weather than on days with heavy clouds and rain. Social influence and interaction with other investors are also coherent to the behavior. Investors tend to follow others in making their investment, they tend to follow each other like in a herd. Herding leads more on the situation when an investor focuses more on other investors’ participation rather than evaluating the information of the particular security.

Behavior finance changes the way how we look at capital markets. It is a new approach that has direct impact not only to investors but also others such as corporate finance, market regulators and policy makers. In behavior finance, the investors should not consistently expect to beat the market even at times when they succeed in getting abnormal returns from their investment. According to behavior finance, market is not always efficient. Good return may due to the available information. However, it is advised to actually spend some of the return and study the cause of mispricing that have cause the market to fluctuates. It is said that achieving higher returns is not only due to good analysis strategies but a better self control.

Primary contribution of behavior finance is its potential help in beating the market.

Summary of Researches

This section will discuss the research finding from Malaysia ( KP Lim., Liew KS., and Wong HT, 2003), Africa (C Mlambo and N Biekpe, 2007) United States America (Jae H. Kim 2009) and Jordan (Mahdi M. Hadi, 2006)

The first research which was done by Lim et. al, 2003 was the weak form EMH that generally holds in KLSE Malaysia and the existence of the linear and the non-linear dependencies. These dependencies appear at very random intervals for a short of time but then disappear again even before investors have the chance to exploit it.

As we know efficient market hypothesis is a fair game where the prices changes in the security is reflected by any new information which was not taken into consideration earlier during the forming of current market price. The paper by Lim et al, 2003 focused on the weak form EMH where the historical price is the only determinant of the security prices. The price movement in a weak form occur randomly and successive price changes are independent of one another, i.e. random walk theory. Past price analysis has no meaning since the patterns observed in the past occurred purely by chance.

The weak form Efficient Market Hypothesis has been studied since many years in KLSE. Malaysian stock market is inefficient in the weak form when weekly data were used but efficiency exist when monthly data were used. Test done by Von Nehmann’s suggested that information that is based on historical prices is fully reflected in current price within a week but may not be fully impounded in current price within a day which conclude that Second Board of KLSE is weak form efficient with respect to weekly data. But when weekly data were used the efficiency of the Malaysian stock market has improved from a weak form inefficient market in mid 1980s to weak form efficient by late 80s and early 90s. Empirical evidence from various statistical test found out that the low trading volumes in most stocks and the possible price manipulations by those investors who own majority of the stocks might help to explain the findings of the runs test.

The reason for departure from random walk is due to the presence of non-linear dependencies in the underlying data generating process which is now widely accepted as a salient feature of financial returns in general and stock returns series in particular. Non linearity has strong implication on the weak form EMH for it implies the potential of predictability in financial returns. Lim et. al (2003b.d) and Lim and Tan (2003) provided convincing evidence that non-linearity has a high effect in the underlying dynamics of the Malaysian stock market. Ko and Lee (1991:224) If the Random Walk Theory hypothesis holds, the weak form of efficient market but not vice versa. Thus evidence supporting the random walk model is the evidence of market efficiency. But violation of the random walk model need not be evidence of market inefficiency in the weak form. Kok and Lee (1994) and Kok and Goh (1995) argued that though daily price series are found to be serially correlated, the magnitude of their correlations is not large enough for any mechanical trading rules to be devised for profitable investment timing. In connection to the existence of linear/non-linear dependency structures to the concept of information arrival and market reactions to that information will prove to enlightening. It is said that if the market is efficient and the new information is useful then it shall be reflected quickly and unbiasedly into market prices. There is a rationalization the correlation between the weak-form EMH and behavioural finance in KLSE. The statistical properties of random walk, linear and non-linear dependencies are interpreted in the context of information arrival and how the market react to that information.

The second research was done by C Mlambo and N Biekpe, 2007 with regard the weak form in the African Stock Market. Johannesburg Stock Exchange is found to be weak form efficient but using weekly data it is not weak form efficient. Studies that have used data on individual stocks used either monthly or weekly data rather than daily data due to non availability of computerised databases. Another argument for using data measured over longer time intervals in the problem of thin trading. Increasing the time interval is argued to reduce the potential biases associated with thin-trading by increasing the probability of having at least one trade in the interval. (Dickinson and Muragu, 1994). This paper studies the weak form efficiency of ten African stock markets using the serial correlation and runs tests

African stock market emerged in the late 1980s and early 1990s and the latest in 2003. African stock exchanges are also the smallest in the world in terms of both number of listed stocks and market capitalisation. The majority of stock markets in Africa trade daily from Monday to Friday. The portfolio inflows to Africa have been disappointing due to unfavourable scenario is that acquisition of shares by foreigners is limited on some African stock markets. The Market Regulator was established on the back of poor regulatory and legislative frameworks. African stock markets are also known to be illiquid and characterised by thin trading (Mlambo and Biekpe, 2005) in comparison to stock markets in other regions. The delay market is perceived by African governments to be an indication of integration into the global economy. It is considered to be a sign of international legitimacy and a measure of a country’s modernisation and commitment to private sector-led development (Moss, 2004). The data used in this study are daily closing stock prices and volume traded for individual stocks. The markets in this study exhibit serious thin-trading for the periods under investigation.

Positive serial correlation is usually considered to be a predictability phenomenon of the short run, while negative serial correlation is mostly a long run predictability phenomenon. The positive serial correlation on African Stock markets might also be a result of institutions imitating spreading their trades over several days to lessen the impact of trades in large volumes on the market (Asal, 2000). The weak market form efficiency if the NSX can probably be explained by the market’s positive correlation with the JSE due to the significant number of stocks that are dual-listed on both markets. The efficiency of the NSX can thus be said to be spill over from, or a reflection of, the weak-form efficiency of the JSE.

The weak form efficiency of the NSX was attributed to its correlation with the JSE. Kenya and Zimbabwe were also concluded as generally weak form efficient, since a significant number of stocks conformed to the random walk. The stock prices on the Mauritius market tend to deviate from the random walk hypothesis. The same conclusion was made for Ghana.

The run test used here only tests for the existence of a linear relationship which makes it inadequate as a testing method on African stock markets where the return generating processes are assumed to be nonlinear. The use of linear models would thus lead to wrong inferences being drawn. Thus further research is required to test the random walk hypothesis.

The third research that I would like to discuss is the market hypothesis in the United States America. Kim et al., (2009), study return predictability of the daily and weekly Dow-Jones Industrial Average indices from 1900 to 2009. The degree of return predictability is estimated using two autocorrelation test (variance ratio and portmanteau) statistics, implementing moving sub-sample windows of different lengths. They found strong evidence that changing of market condition has lead to return predictability. In particular, during market crashes (1929 and 1987), it was observed that return in unpredictable and when it is predictable it is very much associate with high level of doubt. When there is economic crisis, the return from the stock is very predictable even with moderate degree of uncertainty. Whereas during economic bubbles, return predictability and its uncertainty have been smaller than normal times. Our results are in strong support of the adaptive markets hypothesis, which claim that changing market conditions drive the key market features such as the return predictability.

They examine the degree of return predictability of the U.S. stock market using the century-long Dow-Jones industrial index. As measures of return predictability, they used their findings and complements with the recent study by Neely et al. (2009) who report the evidence in favour of the adaptive markets hypothesis for the foreign exchange market in the context of profitability of technical trading rules. The statistics from the automatic variance ratio and automatic portmanteau tests. To detect possible non-linear dependence in stock return, the generalized spectral test has been implemented.

They obtain monthly time-varying measures of return predictability by applying these tests to moving sub-sample windows over monthly grids. A regression analysis is conducted to determine how these measures of return predictability are related to changing market conditions and economic fundamentals.

They also find evidence for cyclical evolution of return predictability, in which changing market conditions are important factors for the degree of return predictability. It is found that, during market crashes, no return predictability is evident but its uncertainty has been exceptionally high. However, during economic and political crises, a high degree of return predictability is observed, but only with moderate degree of uncertainty. During bubble times, the return predictability and its uncertainty are found to be lower than normal times. Contrary to the general findings of past empirical and survey studies, we have found evidence the U.S. market has become more efficient after 1980. This is convincing given that the U.S. market has implemented a various measures of market innovations in the 1960’s and 19070’s, and that US macroeconomic fundamentals have become much more stable since 1980. In addition, there have been fewer occurrences of economic and political crises after 1980 than before. Our finding is a manifestation of the adaptive markets hypothesis, which argues that dynamic market conditions govern the degree of stock market efficiency.

Finally this paper will discuss on efficient market hypothesis in Jordan capital market. This paper by M. Hadi (2006) noted that the objective of accounting numbers is to provide the financial data about the performance of certain enterprise in order to help the managers, investors, shareholders and government authorities in making their decisions. On the other hand, the purpose of accounting research is to estimate the value of accounting data to all investors and other users. Furthermore, the purpose of capital market research is to examine the association between accounting numbers and security return and to test whether or not accounting data carry any information content to security market, and if so it should be impounded in the security price, the results show the security market reacted with mixed signal on releasing profitability, liquidly, and solvency information.

This paper identified EMH and provided some detail on the types of EMH, as well as identifying the empirical research that tested weak, semi-strong and strong forms of market efficiency. Accounting market based research more often assumes that market is efficient in semi-strong form, and the reason for this is that financial reports are considered public information once they are released to the market. In this paper empirical evidence has been provided from Jordanian market, and it shows the security market reacted with mixed signal on releasing profitability, liquidly, and solvency information. The selection of the relevant pricing model is very critical in market-based research. Brown and Warner (1980) investigate how different methods performed when some abnormal performance was present. They conclude that ” There is no evidence that more complicated methodology conveys any benefit. “(Brown and Warner, 1980). Also, they argue that using more complicated models will make the researcher worse off. Furthermore, the use of the market model or even simple models such as mean adjusted return is better than more complicated models like control portfolio.

5.0 Conclusion

The relationship between finance and other social sciences that has become known as behavioural finance has led to a strong and deepen of our knowledge of financial market. In judging the impact of behavioural finance to date, there is still no exact one method that can make an investors gain high profit. For instance in situation where efficient markets theory may lead to drastically incorrect interpretations of events such as major stock market bubbles.

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Indeed, we have to divert our presumption that financial markets always work well and that price changes always reflect genuine information. Evidence from behavioral finance helps us to understand, for example, that the recent worldwide stock market boom, and then crash after 2000, had its origins in human foibles and arbitrary feedback relations and must have generated a real and substantial misallocation of resources. The challenge for economists is to make this reality a better part of their models.

It is found that in Malaysia, there is co existence of weak form EMH and behavioural finance. Unlike in Africa, there are mix of two findings where conforms to the random walk theory and also deviate from the theory. Whereas in United States, it is claim that return predictability and market efficiency and investors’ behaviour are considered as highly context dependent and dynamic by changing market conditions. Whereas in Jordanian market shows the security market reacted with mixed signal on releasing profitability, liquidly, and solvency information.

Further research is suggested in Malaysia to incorporate the issue of model adequacy where the characteristic was found in the returns series and can be used to construct a better economic model. Whereas in Africa it is suggested to test on the existence of linear relationship in the stock markets where the return generating processes are assumed to be linear. In Kuwait, a few research has been investigated in market efficiency in strong form, it is suggested that for future research test for insider information should be investigated.