See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/312233237 A Literature Review of the Efficient Market Hypothesis Article · September 2016 CITATIONS READS 2 685 1 author: Bachar Fakhry University of Lahore 11 PUBLICATIONS 26 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: PhD Thesis View project Analysing Market Participants' reaction to various events in the Global Financial Market View project All content following this page was uploaded by Bachar Fakhry on 12 January 2017. The user has requested enhancement of the downloaded file. Turkish Economic Review Volume 3 www.kspjournals.org September 2016 Issue 3 A Literature Review of the Efficient Market Hypothesis By Bachar FAKHRY †1 Abstract. The efficient market hypothesis and behavioural finance theory have been the cornerstone of modern asset pricing for the past 50 odd years. Although both theories are fundamental in explaining modern asset pricing, they are opposing views. The efficient market hypothesis dictates that the price of any asset depends on the information, while the behavioural finance theory dictates that the price depends on the reaction of the market participants to the information. Therein lays the key to the argument influencing modern asset pricing, does price immediately reflect the information or market participants‟ perception of the information. In this paper, we will critical evaluate the theory influencing the efficient market hypothesis. We will review the neoclassical economics underpinning the efficient market hypothesis and the recent empirical evidence. In concluding, we find that although the efficient market hypothesis has difficulties in testing and the empirical evidence is mixed. Yet it is useful as a benchmark for regulators and central bankers alike. However, market participants are homo sapiens and not homo economics; hence there is a requirement to understand their reaction. So in essence leading to a requirement to include the behavioural finance theory, if we are to understand asset pricing. Keywords. Efficient market hypothesis, Behavioural finance theory, Neoclassical economics JEL. B13, G02, G03, G12, G14. 1. Introduction T he dominant asset pricing theory since the early to mid-1960s have been the efficient market hypothesis, developed through the contributions of prominence articles such as Malkiel (1962), Fama (1965) and Malkiel & Fama (1970). As proposed by Malkiel (1962) and Fama (1965), the efficient market hypothesis argues that the price of any asset must immediately reflect fundamental information about the asset. However, to a certain degree the efficient market hypothesis relies on some untestable assumptions and models. Yet it is possible to test the key assumptions of random walk and efficiency individually thru the use of prominent tests like the variance ratio and bound tests proposed by Lo & MacKinlay (1989) and Shiller (1981) respectively. At the basic level, the efficient market hypothesis is the perfect competition, which is widely used in neoclassical economics. Perfect competition implies the assumption that market participants are rational, risk averse and profit maximising. This assumption of market participants‟ behaviour extends to the efficient market hypothesis, as proposed by Fama (1965) and Malkiel (1962). This highlights the needs to evaluate the assumptions influencing the behaviour of market participants under uncertainty before we can research the efficient market hypothesis. The paper will open with a brief overview of the fundamental economic paradigm underpinning the efficient market hypothesis, namely neoclassical 1 † University of Bedfordshire Business School, Park Square, Luton, LU1 3JU, UK. . +00441234400400 . mbachar.fakhry@me.com Turkish Economic Review economics. This will be followed by an in depth review of the efficient market hypothesis before concluding. 2. Neoclassical Economics Historically, neoclassical economics have been the dominant view in explaining the behaviour of financial markets under uncertainty. In essence, this view dictates that rational market participants should follow the key assumptions of profit maximization, Friedman (1953) and Alchian (1950), and risk aversion, Pratt & Zeckhauser (1987) and Kimball (1993), in their choice of investment. The key in understanding this argument is the negative correlation effect that the assumptions of profit maximization and risk aversion have on financial asset prices. This view has been criticised by many including proponents of the theory of behavioural finance such as Freeman et al. (2004) and Kourtidis et al. (2011). The key problem is the assumptions underpinning the view, are unrealistic, for example rational agents as explained by De Bondt et al. (2008) and stockholder theory as argued by Philips (1997). In this section, we critically review the neoclassical view concentrating on the arguments influencing the assumptions of profit maximization and risk aversion. However, since financial institutions with stockholders, dominate the sovereign debt market; it is necessary to discuss the stockholder theory. The stockholder theory dictates that businesses only exist to maximize the stockholders‟ wealth within the rule of the law; and as Alchian (1950) and Friedman (1953) hints this means the realization of profits; put simply as Alchian (1950, p. 213) states: “This is the criterion by which the economic system selects survivors: those who realize positive profits are the survivors; those who suffer losses disappear.” This is also argued by Friedman (1953, p. 22) “Whenever the determinant happens to lead to behavior consistent with rational and informed maximization of returns, the business will prosper and acquire resources with which to expand; whenever it does not, the business will tend to lose resources and can be kept in existence only by the addition of resources from outside.” However, as many proponents of the stakeholder theory (such as Freeman et al. 2004; Philips et al., 2003; Philips, 1997 and Hosseini & Brenner, 1992) would point out there is more to business ethics than just profits. The idea as defined by Jensen (2002) is that businesses have to take into account the interests of all stakeholders in the firm. By definition stakeholders includes all individuals and groups who can affect the welfare of the business and not just shareholders. However, Friedman (1970) argues that the only social responsibility for a business is to increase its profit. This seems to be suggesting that as dictated by the market selection hypothesis in order for the financial institutions to survive, there is a need to attract investment funds and thus generate huge profits as hinted by Dutta & Radner (1999). The problem is that the behaviour of many of these financial institutions during the assert price boom of the mid 2000s points towards pure profit maximization. As defined by De Scitovszky (1943), pure profit maximization is the constant shifting of profit targets to maximize the utility function of the shareholders. In contrast, the key argument of Alchian (1950) and Tintner (1941) is that businesses just have to make a positive profit to survive. The key point is, if they make losses they struggle to survive as hinted by many including Alchian (1950) and Friedman (1953). A point in case is the bankruptcy of Lehman Brothers and hence the government bailout of many financial institutions during the financial crisis. TER, 3(3), B. Fakhry, p.431-442. 432 Turkish Economic Review In a way this led to the accusations by many including government inquiries2 into the crises of financial institutions being too risk loving and greedy. However, the point defined by Kimball (1993), standard risk aversion follows a marginal increasing function, which means that bearing one risk makes the market participant less willing to bear another risk. Another argument highlighting this is that increasing risk leads to an upward shift in risk aversion as noted by Diamond & Stiglitz (1974). This seems to be the overwhelming behaviour during the recent financial and sovereign debt crises. A counter argument is that market participants‟ behaviour seems to be following proper risk aversion. As defined by Pratt & Zeckhauser (1987), proper risk aversion dictates that with respect to two independent risks, the rejection of one risk does not automatically deflect the market participants from taking the other independent risk. This is mainly due to market participants hedging their risks by the use of derivatives instruments such as options and futures. An example is the use of credit default swaps as hedges against the risk of a government defaulting on its debts. However, a key point made in Alchian (1950) definition above is that companies that make losses do not survive and this highlights an alternative argument that many market participants display loss aversion rather than risk aversion. As defined by Kahneman et al. (1991) and Thaler et al. (1997), loss aversion dictates that market participants tend to be increasingly sensitive to a loss than to a gain or put simply the feedback effect. This is obvious from the reaction of the financial institutions during the sovereign debt crises where a loss made the institutions averse to any further losses. This meant that the crises quickly spread from Greece to other sovereign debt markets. This leads us to the utility functions of the agents, since these agents caused the problems as often cited by government inquiries into the crises (see footnote 4). Given an option between a number of similarly risky investments, utility maximization theories dictate that the agent choses the one with the highest income. However, in a situation where the agents of financial institutions face investments of different risks, the key question is how can they choose the investment, which maximizes their utility? This problem occurs if interest rates are low and banks therefore take on larger risks for a higher return. This has resulted in the development of a sub-prime mortgage market, for example, where prices no longer reflect the risks, which ultimately led to the collapse of the market. The collapse occurred despite the existence of derivatives instruments such as CDS to insure against that risk. Surely, this would conflict with the utility maximization behaviour of buying risky securities such as subprime mortgage securities. Still, this behaviour can be justified as rational, when one takes into account an S-shaped utility curve. Friedman & Savage (1948) and Hartley & Farrell (2002) argue the possibility of non-concave or non-diminishing marginal utility function leads to different behaviour towards risk. This could explain the rational behaviour of the huge gamble taken by the agents during the recent housing and mortgage backed securities prices bubble. So in essence, the argument is that even efficient markets can lead to market instabilities. As the crisis has shown, however, many market participants did not actually know what they were buying as illustrated by (Beltran & Thomas, 2010; Brunnermeier, 2009; Gorton, 2008). Therefore, the validity of this argument is questionable in the least. However, as argued by Pennings & Smidts (2003) the evidence points towards an S-shaped utility function curve governed by the agent‟s attitude towards profit 2 Such as the House of Commons Treasury Committee Report Number 416 in the UK and Financial Crisis Inquiry Commission Report of January 2011 in the US. TER, 3(3), B. Fakhry, p.431-442. 433 Turkish Economic Review and loss, in other words, the shape of the utility function depends on the initial situation, which is not compatible with rational behaviour. As this makes the utility function unstable resulting in higher volatility of observed bond prices, as buying and selling of bonds depended on the changing utility function. So in essence, the argument is that even efficient markets can lead to market instabilities. The utility function of the agents in the financial sector dictates the supply and demand model is the reverse of the standard model as suggested by Cifuentes et al. (2005) and Shin (2008). And as hinted by Shin (2008), this means under profit maximization behaviour demand in high return assets increase putting upward pressures on the equilibrium price, while risk aversion behaviour not only reverses the demand for high return assets, due to the high risk associated with these assets, but also increases supply leading to a decrease in the equilibrium price. The sovereign debt crises elegantly illustrated this, in the high demand environment of the flight to liquidity or quality during the financial crises; governments were able to control the increase of demand by issuing more debt. During the sovereign debt crises demand for several sovereign debts decreased hugely but the point here is, the supply also increased putting huge downward pressures on the prices. The reasons are simple unlike the standard model of supply and demand which dictates when prices go down the issuer could reduce the supply to ease the pressures on the equilibrium price. The existence of a secondary market meant that as market participants became increasingly risk averse due to a high possibility of defaults, they sold the debts meaning the secondary market became overstocked and the prices plummeted. So no matter what the governments of the GIPS nations or the Eurozone tried to do, they could not reduce the supply and hence the yield. As hinted previously, an argument often used against the neoclassical economics is that market participants are not all rational as suggested by Hong & Stein (1999) and Kourtidis et al. (2011). In addition, unlike the assumption dictating that the impact on the prices from irrational market participants is shortlived, the evidence from Barberis & Thaler (2003) is that the impact is long-lived. The other issue concerning neoclassical economics is that the basis for many of the simplifying assumption of the models is that all market participants exhibit rational risk averse profit maximisation behaviour. As with the previous argument, the existence of heterogeneous market participants each with a different attitude to risks and earnings means that this assumption of homogeneous behaviour regarding risks and earnings does not hold. In this case, we need to use behavioural finance theories to identify the impact of heterogeneous market participants in different circumstances as illustrated by Hong & Stein (1999). 3. The Efficient Market Hypothesis Before we can start reviewing the efficient market hypothesis, there is a need to define information in the context of this research. Although as hinted by Malkiel & Fama (1970) and Malkiel (2003), the efficient market hypothesis dictates that prices should reflect all available information (which is why we use prices rather than spreads to check for market efficiency in this thesis). It is common practice to distinguish information in terms of fundamental and non-fundamental information (Bollerslev & Hodrick, 1992). In other words, information is the summation:  the fundamentals, such as yields or macroeconomic factors in the sovereign debt market, as hinted by Cochrane (1991) and Malkiel (2003),  non-fundamentals, such as information from news (i.e. they do not have any direct relationship to the asset but still have the power to influence the price such as the 9/11 terrorist attacks, Lehman Brothers bankruptcy in 2008 and Japanese Earthquake in 2011), as hinted by Caballero & Krishnamurthy (2008). TER, 3(3), B. Fakhry, p.431-442. 434 Turkish Economic Review Malkiel & Fama (1970) notes simply put the efficient market is a market where market participants are assumed to exhibit rational profit maximization behaviour and prices always fully reflect available information. In essence, as Malkiel (2003) states the view influencing the efficient market hypothesis is information spreads quickly and priced into asset valuation immediately. Hence, as Malkiel (2005) states this means that no arbitrage opportunities exist that allows for excess returns without excess risks. As Malkiel (2003) hints in an efficient market, competition will mean that opportunities for excessive risk adjusted returns will not persist. However, this does not mean that the efficient market hypothesis imply market prices will always be accurate and all market participants will always exhibit rational profit maximization behaviour. According to Malkiel & Fama (1970), the efficient market hypothesis dictates that any model of expected price should follow the notation of 𝐸 𝑝𝑗 ,𝑡+1 𝜙𝑡 = 1 + 𝐸 𝑟𝑗 ,𝑡+1 𝜙𝑡 𝑝𝑗𝑡 . The importance of this equation in the concept of this research is 𝜙𝑡 . According to Malkiel & Fama (1970), this suggests that the expected price based on all available information at present is the price at present plus the expected return based on all available information at present. As Malkiel & Fama (1970), states this notation of the expected price, means regardless of which model (e.g. APT or CAPM) used to derive the equilibrium price, expected return should fully reflect all information available at present, transaction costs and taxations being equal. Remember, as noted by Malkiel & Fama (1970), where expected excess value or return on the asset is equal to zero then by definition the excess value or return is a fair game with respect to the information available. In essence as quoted by Malkiel (1962), the expectation of the future price of the asset strongly influences the price of any long-lived asset. However, as put by Malkiel (1962), it is plausible that the recent past dictates the market participants‟ expectations. As suggested by both Fama (1965) and Malkiel (2003), the efficient market hypothesis is associated with the idea influencing the random walk model. A big issue with regard to the pricing of information, as seen in numerous events during the recent financial and sovereign debt crises, is nobody can predict the impact of information especially under uncertainty. Hence, as Fama (1965) states during periods of uncertainty the equilibrium price can never be determined exactly. Moreover, as hinted by Fama (1965) the instantaneous adjustment property of the efficient market hypothesis may cause successive independent price changes, which imply prices follow the random walk model. As defined by Malkiel (2003, p. 59) “The logic of the random walk idea is that if the flow of information is unimpeded and information is immediately reflected in stock prices, then tomorrow's price change will reflect only tomorrow's news and will be independent of the price changes today.” Although, as stated by Malkiel & Fama (1970), the random walk model does not state that past information has no value in assessing distribution of future returns. However, the random walk model does state that the sequencing of past returns has no value in assessing distribution of future returns. This last statement could infer the random walk model simply put is the direction in the short run of expected returns and hence prices is unpredictable given all available information; however, in the long run the trend in the market prices is partially predictable as stated by Malkiel (2005). Furthermore, as stated by Timmermann & Granger (2004), this makes the efficient market hypothesis notoriously difficult to forecast prices and returns. The key logic behind this is if prices and returns were forecastable, it would mean the existence of unlimited profit, which would make the economy unstable as noted by Timmermann & Granger (2004). TER, 3(3), B. Fakhry, p.431-442. 435 Turkish Economic Review As hinted by Ball (2009), many in the regulatory, financial markets and academic environments were critical of the efficient market hypothesis in the aftermath of the financial crisis. The reasoning behind their argument boils down to the key notation underpinning the efficient market hypothesis that market prices should reflect all available information. This led to the false sense of security by regulators and market participants that market prices were correct based on all information leading to an asset price bubble. Ball (2009) argues that while like all good theories the efficient market hypothesis does have major limitations; however, appear to exaggerate the criticisms in the aftermath of the global financial crises. Since the theory of the efficient market hypothesis was only published by Fama (1965), this argument is invalid since there have been many crises based on the asset price bubble before the advent of the efficient market hypothesis. Ball (2009) points to the fact that the efficient market hypothesis states current asset prices are correct based on all available information; this means that market participants should accept asset prices as correct. However, in the pre-crises asset price bubble many market participants thought that asset prices were “incorrect” and hence they could beat the market. This does seem to suggest that for some market efficiency based on all information the price is right/correct. However, this is misleading, since the efficient market hypothesis, as defined by Malkiel & Fama (1970), does not state that the price is right/correct; it only states the price should reflect all available information. A key argument often put against the efficient market hypothesis is that sometimes asset prices deviate from the fundamental value as hinted by many including Barberis & Thaler (2003) and De Bondt et al. (2008). In addition, as illustrated by Barberis & Thaler (2003) these deviations can be long-lived and substantial. Another issue raised by Hong & Stein (1999) is that market participants may not have access to all the information. And even if they do, as suggested by De Bondt (2000) and Daniel et al. (1998) they may have different sentiment about the information. A key assumption used in the efficient market hypothesis is the existence of well-informed wealthy rational arbitrageurs who push the asset price back to its fundamental value (Fama, 1965). As Hong & Stein (1999) illustrate the existence of these arbitrageurs does not counter the effect of other market participants and Abreu & Brunnermeier (2003) argue that these arbitrageurs sometime like to take advantage of the circumstances therefore pushing the price further from the fundamental value. Another key argument is that markets often go thru phrases where the efficient market hypothesis is not enough to explain the anomalies, e.g. bubbles (see Blanchard & Watson, 1982; Hong & Stein, 1999; De Bondt, 2000; Abreu & Brunnermeier, 2003). Hence, there is a need to research the psychology of market participants as suggested by De Bondt et al. (2008) and Kourtidis et al. (2011). This leads towards the use of the behavioural finance theory. The evidence seems to suggest there is a link between the pricing of information and sovereign debt markets and as Brandt & Kavajecz (2004) hints there are two main mechanisms for the daily changes in yields on sovereign debts: flow of public information and price discovery. However, as illustrated by the numerous empirical studies, the majority of the evidence is on the effect of macroeconomic information and the heterogeneous interpretation, known as price discovery, or public information. Christiansen (2000) argues that contrary to equity and corporate bond, in general there is no private information in sovereign debts returns. Thus, generally any movement in the returns on sovereign debts must come from public information, i.e. macroeconomic announcements and since the time varying return volatility of financial assets are autocorrelated and highly persistent, hence TER, 3(3), B. Fakhry, p.431-442. 436 Turkish Economic Review macroeconomic announcements could explain the high persistent observed in the volatility of sovereign debt markets. However, according to Greenwood & Vayanos (2010), macroeconomic variables sometimes cannot fully explain the variation in the yield curve and hence shifts in demand and/or supply of sovereign debts are other important drivers in understanding the movements in the yield curve. According to Fleming & Remolona (1999), the key implications stemming from how public information influences the US Treasury market is the extent to which it drives the price movement and market makers are not confronted by imperfect information when trading. As implied by the article unlike many other financial markets, the treasury market being dominated by non-market based trading hence it is restricted by maximum or minimum limits on bid-ask spreads or price changes, therefore spreads and prices can adjust endogenously on public information. They identify two stages in the market‟s adjustment for price formation and liquidity provision in the immediate aftermath of the announcement of public information: during the brief first stage, there is a sharp and instantaneous change in prices and a reduction in the trading volume. During the next stage persistence trading surges leads to high price volatility and moderately wide bid-ask spreads. Bollerslev et al. (2000) analysed the 5 min intraday US Treasury bond futures data over the period January 1994 to December 1997; researching long-memory volatility in macroeconomic announcements in the observed data. They found that US Treasuries futures exhibit long memory volatility in certain macroeconomic announcements. According to their research, the open and close of markets have higher volatilities than mid-day. The results indicate macroeconomic announcement is a key source of US Treasuries market volatility compared with prior results for FX and equity markets. In an empirical study by Balduzzi et al. (2001) on the effect of regular macroeconomics news on a number of US Treasuries, the study found the greater the unexpected macroeconomic news announcement is, the more significant the impact on the price of at least one of the US Treasuries. They found that generally the price is usually the first affected by the announcement hinting that public information mainly drives the initial price adjustment. The next stage is the widening of the bid-ask spread suggesting informed trading drives both volatility and volume. The final stage is the continuation of the volatility and volume beyond the normality of the bid-ask spread hinting at liquidity trading. According to the article, different macroeconomic factors have different effects on the various securities. However, several announcements have significant impact on a number of securities and the impact varies depending on the maturity. They conclude that surprises in the announcement have a substantial impact on the price volatility but the bid-ask spreads seem to recover quickly hinting at public information being rapidly absorbed into the price. In another empirical study by Brandt & Kavajecz (2004); show that price discovery is not necessarily concentrated around the time of the public information announcement. They imply at the existence of many factors influencing changes in the daily yield and therefore the structure of the yield curve but highlight two main complimentary factors: public information flow, such as periodically macroeconomic information releases, and heterogeneous interpretation of public information, i.e. price discovery, via trading in the Treasury market. Interestingly, the Andersson et al. (2006) study of the effect of macroeconomic news from various countries on price discovery in the German long-term government bonds market finds that in general macroeconomic news have a stronger longer-lasting impact on volatility. In addition, they found that TER, 3(3), B. Fakhry, p.431-442. 437 Turkish Economic Review macroeconomic news from the US have more influence than the Eurozone announcements or various countries within the Eurozone. An important aspect of market participants‟ behaviour as hinted by Caballero & Krishnamurthy (2008) is market participants face immeasurable systemic risks under certain market conditions, which lead to market participants exhibiting flight to quality or liquidity behaviour. Acknowledged as Knightian Uncertainty, it is believed to explain the behaviour of market participants in the aftermath of a wide range of events such as the Lehman Brothers Collapse in September 2008, Greek sovereign debt crisis and 9/11 terrorist attacks. The common factor is the lack of previous similar events to base information on. However, these events are based on news and hence as hinted by Malkiel (2003) news is by definition unpredictable resulting in price changes tending towards unpredictability and hence randomness. In general, there is a large body of empirical literatures on the efficiency of the financial market. A large percentage of these are based on the stock market, the recent evidence on the efficiency of the stock market is mixed. Some found the stock market to be inefficient; an example is Cajueiro et al. (2009) who found the liberalization of the Greek stock market made it significantly less efficient. However, the evidence from Cuthbertson & Hyde (2002) seem to suggest the acceptance of the EMH for the French stock market and slightly less so for the German. In comparison, the body of empirical literatures on the efficiency of the sovereign debt market is limited despite the first model of international efficient market being based on the French sovereign debt market as stated by Zunino et al. (2012). As Zunino et al. (2012) suggest the main reasons are the size of trading on the stock market and the type of trading for the sovereign debt market, mainly traded “over-the-counter”. Like the stock market, the recent empirical evidence on efficiency in the sovereign debt market is mixed. Zunino et al. (2012) using sovereign debt indices found that developed markets tend to be more efficient than emerging markets. Fakhry & Richter (2015) studying the impact of the recent financial and sovereign debt crises on the US and German sovereign debt markets found in general both markets were too volatile to be efficient. Although the US datasets do suggest the market is efficient, is efficient, yet the subsamples suggest a mixed results pointing to both crises having an impact on the efficiency of the US and German markets. Conversely, Fakhry et al. (2016) extending the method used in Fakhry & Richter (2015) to the GIPS markets, also find mixed evidence of efficiency during the crises. This leads to a possible explanation of the efficiency of the US datasets using the behavioural finance theory. Since market participants were overreacting/underreacting to information during different periods, one possible conclusion is that the overreaction/underreaction cancel each other out leading to a stable state in the datasets giving the impression of market efficiency. 4. Conclusion The efficient market hypothesis has been the mainstream of finance for nearly 50 years. However, as highlighted in the review, there are many issues with this theory and it does throw up a basic flawed idea. The concept is that the price always incorporates all the information at the time and hence the price reflects the given information. This idea is at the centre of the debate surrounding the efficient market hypothesis in the aftermath of the financial crisis. The other key issue is that it relies on key assumptions made in neoclassical economics, which do not always hold in the real world, i.e. the existence of rational market participants and perfectly competitive markets. In truth, both the efficient market hypothesis and TER, 3(3), B. Fakhry, p.431-442. 438 Turkish Economic Review neoclassical economics view are essentially just models of the financial market and are therefore best used as benchmarks and not observations of the real world. A key factor to note is that market participants are homo sapiens and not homo economics. Another issue as highlighted by Ball (2009), many were critical of the efficient market hypothesis in the aftermath of the financial crisis. The issue seems to be based around the price is correct argument, however this is dangerously misleading; since the efficient market hypothesis only states the price should reflect all available information at the time. There are two arguments regarding this issue; firstly, as highlighted by Ball (2009) in the pre-crisis period many market participants thought prices were incorrect and using sophisticated forecasting models, they could beat the market. Secondly, the efficient market hypothesis does not work when there is unequalled access to information resulting in incomplete or asymmetrical information. This goes back to the neoclassical economics assumption of perfect competition; in a perfectly competitive environment, information should be complete and accessible to all market participants. Of course, a key neoclassical economics assumption is that market participants are risk averse. However, as hinted by Buiter (2007) and Feldstein (2007), as early as 2005 many thought there was massive under-pricing of risks. Hence, market participants were not following this fundamental assumption of neoclassical economics and thus the efficient market hypothesis. This goes to the heart of the problem during any asset price bubble, as illustrated in the next section, it is often the case that market participants usually think they could beat the market and therefore consistently under-price risk in the attempt of making increasingly large profits. Therefore, distorting the market from the fundamental price leading to increased asymmetrical information. The key is determining whether the financial market accept the efficient market hypothesis, we presented strong historical empirical evidence suggesting financial markets are not efficient. The tests and methods used to test the efficiency of the markets in the empirical evidences are wide ranging, e.g. variance bound tests (Shiller, 1979), variance ratio tests (Lo & MacKinlay, 1988) and cointegration tests (Engle & Granger; 1987). Moreover, although the majority of the evidence seems to be based around the stock market, yet it does suggest that the global financial market is not random and asset prices are too volatile to be explained by the information. This is the key to our research, if markets are too volatile to be efficient then what is explaining the behaviour of volatility in the markets. Another key factor to our research as pointed out by Bollerslev & Hodrick (1992), the use of GARCH models can overcome clustering issues with the variance bound tests. A possible issue in the variance bound tests is that market participants seem to react differently to negative or positive information. In order to analyse whether markets are more efficient during phases of negative or positive shocks, there is a requirement to include the asymmetrical/leverage effect in the variance bound test. In concluding, the efficient market hypothesis and behavioural finance theory explain different parts of asset pricing. However, as things stand at present, both have strong weaknesses. This means in order to fully understand the pricing of assets there is still a requirement to use both fundamental theories. Coincidentally, the behavioural finance theory could be extended to explain the efficient market hypothesis by using the overreaction/underreaction steady state and the key is that this is testable. So in essence the behavioural finance theory is a more complete and therefore theoretically superior theory of asset pricing. TER, 3(3), B. Fakhry, p.431-442. 439 Turkish Economic Review References Abreu, D., & Brunnermeier, M.K. (2003). Bubbles and Crashes. 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This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by-nc/4.0). TER, 3(3), B. Fakhry, p.431-442. 442 View publication stats The Journal of Developing Areas Special Issue on Kuala Lumpur Conference Held in November 2015 Volume 50 No. 5 2016 NEW EVIDENCE FROM THE EFFICIENT MARKET HYPOTHESIS FOR THE NIGERIAN STOCK INDEX USING THE WAVELET UNIT ROOT TEST APPROACH Ikechukwu Kelikume* Pan-Atlantic University, Nigeria ABSTRACT The efficient market hypothesis (EMH) assumes the absence of asymmetric information in trading activities in a typical stock market. The EMH has been tested extensively in the developed market economy with mixed results, but very little contribution has been made on the subject matter in developing market economy because of the presence of asymmetric information, institutional constraints and poor data collection method. Validating the hypotheses for the African economy has remained of great interest to researchers and investors given the repeated emphasis on the African economy as the next frontier of economic growth. Issues surrounding the EMH in developing economy rest on the possibility of exploiting the stock market to make quick returns. The validity of this statement remains to be tested empirically for the developing market economy. This paper investigates the EMH for a major developing African economy-Nigeria being the most populous country in Africa and the second financial hob in Africa, next only to South Africa. The study seeks to test the efficiency of the Nigerian stock market, using a wavelet unit root test with different lags and other traditional random walk testing procedure. The use of the wavelet unit root test entails the decomposition of the variance of the time series stochastic process into the variance in its high and low-frequency series. The study made use of monthly average stock price index of the Nigeria Stock Market over the sample period 1985 to 2015 to carry out the test. The result obtained from the wavelet-based unit root tests showed clear and conclusive evidence that the Nigerian Stock Market follows the random walk behavior during the period of the study and that the Nigerian Stock Market is efficient. In other words, stock prices fully reflect all the available information existing in the market and investors, armed with the trading rules, cannot exploit the market to earn extraordinary returns. This has vital implications for speculators, investors and rentseekers hoping to capitalize on the unstructured nature of a typical developing market economy to make quick wins. Since the Nigerian Stock Market is efficient, investors should desist from futile attempts to forecast long-run share prices with the hope of making a quick, sustained win in the market. JEL Classifications: G10, C22, G14, G12, G17 Keywords: efficient market hypothesis, random walk hypothesis, wavelet unit root test Corresponding Author’s Email Address: ikelikume@lbs.edu.ng 186 INTRODUCTION The stock market in Nigeria has witnessed significant volatility since the 2007-2008 global financial crisis that had its root in the U.S Subprime mortgage crisis. The trend analysis in the Appendix (Figure 1) shows that the stock market has responded significantly to changes in the international oil price and exchange rate movement between 2010 and 2015. Between January 2010 and December 2013, the Stock market in Nigeria experienced significant growth as indicated by the market capitalization of listed equities which rose from N5.411 trillion in January 2010 to N13.226 trillion in December 2013 (CBN Statistical Bulletin). However, stock market capitalization of listed equities saw a sharp drop from N13.005 trillion in January 2014 to N11.477 trillion in December 2014. The sharp drop in market capitalization in 2014 can be traced to the declining international crude oil price and the series of devaluation that have taken place in Nigeria since the beginning of the third quarter of 2014 (see Chart in Appendix 1). The declining trend in market capitalization has produced many losers and very few gainers with many companies listed on the Nigerian Stock Exchange experiencing wide swing in their share prices. The current trend in the stock market points directly to the predictability of the movement of share prices and ability of players in the market to “beat the stock market.”1 The debate on the (EMH) which is still ongoing between financial market players and core finance academics is whether the stock market reflects all information made available to market participants at any given time thereby making it impossible for any one player in the market to beat the market through the attainment of greater profitability. The efficient market hypothesis (EMH) has played a central role in stock market research. A series of studies allows us to have a robust technical knowledge on key issues on EMH. For the most acceptable framework and econometric modeling technique (see, for example, Fama, 1970, 1991; Fama and French, 1988; Lo and MacKinlay, 1988), though a growing body of literature has been giving arguments in contradiction to the EMH theory (i.e. Schleifer, 2000, Barber and Odean, 2000; Lo, 2005). The theory is closely related to the idea of a “random walk,” which is characteristics of a price series where all successive price changes are random deviations from past prices. The idea behind the random walk is that if the information flow is unrestricted and information is instantaneously reflected in stock prices, then today’s price change will reflect only today’s news and will not be determined by the price changes yesterday. The major goal of the present paper is to advance knowledge on the particularities of the EMH in Nigeria by testing the efficiency of the stock markets. Most empirical studies on EMH have focused on the weak form2 (which is the lowest level of EMH) because if the evidence does not support the weak-form of market efficiency, examining the EMH at the stricter levels of semi-strong and strong form becomes The term “beat the market,” refers to the ability of investors to produce a better return than the market average which is usually benchmarked with S and P 500 or the Dow Jones industrial Average Index 2 The weak form of efficient market hypothesis describes a market in which historical price data are efficiently digested and, therefore, are useless for predicting subsequent stock price changes (see Hagin. 1979). 1 187 unnecessary. Therefore, we contribute to the literature by re-investigating the EMH, using daily Nigerian stock market data. Though various studies have addressed issues in this domain in the recent past, we extend the existing studies using a larger sample and newer methodology; we study daily data for the Nigerian stock market over the period 1885–2015. The large sample affords us the availability of a greater variety of information. This should reflect the dramatic transformations that have taken place in Nigeria’s securities sector in the past decade. Methodologically, this study investigates the efficient market hypothesis in Nigeria using the wavelet unit root tests, introduced by Fan and Gençay (2010). The remainder of the study is organized as follows. Section 2 summarizes the important literature on the efficient market hypothesis. Section 3 describes the methodology as well as the data on the Nigeria stock markets. Section 4 reports the empirical results. The conclusion is drawn in Section 5. LITERATURE REVIEW The study of the efficient market hypothesis has yielded a vast body of literature, being a subject of main debate of traditional finance from the 1970s. In his Efficient Capital Markets, Fama (1970), defined a stock market as efficient if the price of securities fully reflects all available and relevant information. In the words of Dima and Milo (2009, p. 402): “The efficient market hypothesis … states that asset prices are rationally connected to economic realities and always incorporate all the information available to the market. In this way, securities markets are seen as efficient in reflecting information about individual stocks or about the stock market as a whole.” In such a situation, the market participants cannot achieve unusual returns, different from what is obtainable if holding a randomly selected portfolio of individual stocks with comparable risks. The main attractiveness of the Efficient Market Hypothesis relies on the fact that it is built upon economic theory, specifically “random walk”. That is, the efficient market hypothesis is related to “the random walk”, where price series have subsequent price changes which are random departures from previous prices. Eugene Fama’s (1970) seminal article, “Efficient Capital Markets” gave birth to the efficient market hypothesis as the idea that “securities markets were extremely efficient in reflecting information about individual stocks and about the stock market as a whole” (Malkiel, 2003, p. 59). Today, as researchers have been discussing EMH for the past decades, the literature on the theme is now vast (see Fama, 1970; 1991; Fama and French, 1988, Lo and MacKinlay, 1988; Fawson, Glover, Fang and Chang, 1996; Kadapakkam, 1999; Karemera, Ojah and Cole, 1999; Schleifer, 2000, Barber and Odean, 2000; Lo, 2005, Alam, Tanweer and Groenewold, Sam and Wu, 2003; Wheeler, Bill, Tadeusz and Steve, 2002; Charles and Darne, 2009; Udoka, 2012; Gimba, 2012). In fact, this decade started with one overview of literature on the Efficient Market Hypothesis by Sewell (2011), which mainly focused on the history. Economic theory suggests that a stock market is efficient if stock prices fully reflect all available and relevant information at any time. For that reason, according to Charles and Darne (2009, pp. 117-126), “given only past price and return data, the current price is the best predictor of the future price, and the price change or return is expected to be zero. The essence of the weak-form efficient market hypothesis [EMH], which implies a random walk”. 188 More advanced econometric techniques have been applied to Efficient Market Hypothesis studies in the late 1990s and early 2000s compared to the studies between the 1970s and 1980s, contributing to improvements in the understanding of efficient markets. Some of the most advanced techniques have been applied to improve, among others, the estimates of the random walk. An exhaustive review of the literature shows that the most commonly tested form of EMH in the empirical literature is this random-walk implication. Some of the several statistical techniques commonly used to test weak form efficiency are runs test, unit root test, serial correlation tests, and spectral analysis. The runs test and unit root test are very common in studies from emerging stock markets. For example, Karemera et al. (1999), Wheeler et al. (2002), and Abraham et al. (2002) used the runs test; Groenwold et al. (2003), and Seddighi and Nian (2004) used the unit root test; Fawson et al. (1996), Moorkerjee and Yu (1999), and Abeysekera (2001) used both. Furthermore, Dickinson and Muragu (1994), Fawson et al. (1996), Moorkerjee and Yu (1999), Abeysekera (2001), and Groenwold et al. (2003) used a combination of correlation coefficient test and Q-test while Dockery and Vergari (1997), Karemera et al. (1999), Alam et al. (1999), Chang and Ting (2000), Cheung and Coutts (2001), Abraham et al. (2002), Smith et al (2002) and Lima and Tabak (2004) used variance ratio tests. In addition, Ayadi (1983) used non-parametric tests; Sharma and Kennedy (1977) and Fawson et al., (1996) used spectral analysis; Buguk and Brorsen (2003) used fractional integration test; Seddighi and Nian (2004) used ARCH test. The empirical literature shows that these empirical studies used different data. While studies such as Abeysekera (2001), Abraham et al. (2002), Lima and Tabak (2004) and Mikailu and Sanda (2007) used stock price indices, Dickinson and Muragu (1994), Olowe (1999) and Wheeler et al. (2002) used individual stock prices while Seddighi and Nian (2004) used both. Another issue is the frequency of time series. Mookerjee and Yu (1999), Cheung and Coutts (2001), Groenewold et al., (2003), Lima and Tabak (2004) and Seddighi and Nian (2004) used daily data; Samuels and Jacout (1981), Dickinson and Muragu (1994), Dockery and Vergari (1997), Abraham et al., (2002) and Bashir (2010) used weekly data, Sharma and Kennedy (1977), Barnes (1986), Fawson et al., (1996), Olowe (1999), Karemera et al., (1999), Alam et al., (1999) and Udoka (2012) used monthly; Chang and Ting (2000) used yearly. These differences in methodologies used to test the EMH in emerging markets have produced mixed and conflicting results. As a result, while some authors have evidence in support, others have evidence to oppose the EMH. For the Warsaw Stock Exchange, for instance, Wheeler et al. (2002) finds no evidence to support the weak form efficient hypothesis. For the stock markets in Chile, Mexico, Argentina and Brazil, Urrutia’s (1995) study provides mixed evidence on the weak form efficiency. Specifically, results of the variance ratio test reject the random walk hypothesis for all markets while findings from the run tests indicate that these markets are weak form efficient. Bombay and Dhaka Stock Exchanges, Sharma and Kennedy (1977) and Alam et al. (1999) show that the stock price changes support the random walk hypothesis. For stock markets in Sri Lanka, Kuwait, Saudi Arabia and Bahrain, Abeysekera (2001) and Abraham’s (2002) studies rejected the hypothesis of weak form efficiency. Information efficiency and operational efficiency (Baumol, 1965; Fama, 1970; Weston and Copeland, 1986) are the two major areas of stock market efficiency. 189 Research finds that a stock market may not be simultaneously operationally efficient and informationally efficient (Udoka, 2012). Studies such as Baumol (1965) and Fama (1970) have shown that a stock market is operationally efficient based on its transaction costs, availability of price information, price continuity and timeliness. Information efficiency of the stock market, on the other hand, suggests that the market adjusts quickly to new information in accordance with financial valuation theory (Udoka, 2012). In other words, the market can capture correctly the impact of any new information on the stock price, in such a way that it will be unnecessary for any investor to carry out independent valuation. This is the idea behind the Efficient Market Hypothesis. Moreover, today, one of the most remarkable features of international financial development is the increasing prominence of stock markets in emerging markets. Yet, these stock markets must be efficient in order to play their roles in the allocation and pricing of capital, and the pricing of risk. Malkiel (2003, p. 60) defines efficient financial markets as “markets which do not allow investors to earn above-average returns without accepting above-average risks”. Yet, the current context of institutional rigidities in the emerging markets raises efficiency concerns and necessitates an in-depth analysis of the EMH in emerging markets. According to Smith, Jefferis and Ryoo (2002, p. 475): “While the more-established emerging markets have been the topic of extensive analysis of market efficiency, the same cannot be said for African markets, largely because many of them are new and very small, and there has often been a problem obtaining data series of sufficient frequency and duration”. There have been many empirical studies on the weak form of EMH in emerging stock markets, especially Nigeria (Smith et al 2002; Gimba, 2010; Mikailu and Sanda, 2007), but no none has ever used the wavelet unit root test applied in the present study. As a matter of fact, only recently has Tiwari and Kyophilavong (2014) adopted the wavelet unit root test approach for the investigation of the random walk hypothesis for BRICS stock indices. Thus, the main difference between those studies and this one is the econometric method. It is obvious from surveying the literature on this topic that much has been learned about Efficient Market Hypothesis. For the Nigerian stock exchange, Olowe (1999), Bashir (2009), Mikailu and Sanda (2007) and Udoka (2012) found that evidence to support efficient in the weak form while Sanda (2009) found otherwise. Therefore, much work remains. Quite interesting is Smith et al (2002) which rejected the random walk hypothesis for Nigeria in a study on African stock markets. Yet they posed a question: where the random walk hypothesis is presently rejected, do those markets approach a random walk as they become more liquid and more institutionally mature? Since Smith et al. (2002) study, the Nigerian Stock Exchange has grown rapidly, operating in a continuously changing regulatory environment. The stock market is now one of the biggest in Africa. The speculation is that the securities market has the potentials to rank among the largest in the world in the coming decades. Therefore, a step further is necessary in the study of EMH in Nigeria. In the next section, the model that we use and the econometric method are described in more details. 190 METHODOLOGY The unit root tests literature have developed one framework after another, with different assumptions and incorporating different levels of less nonlinearity, less volatility and structural breaks. While the previous unit root tests in the literature are on the basis of a time domain analysis, the present study uses a different test in the framework of wavelet analysis. The usage of the wavelets eases the decomposition of the stochastic processes into its wavelet components, with each related to a specific frequency band. According to Tiwari and Kyophilavong (2014, p. 39) “the wavelet power spectrum measures the contribution of the variance at a particular frequency band in comparison to the overall variance of the process”. In order to develop the wavelet-based unit root tests, Fan and Gençay (2010) decomposed the variance of the underlying processes into the variance in its high and low frequency components by means of discrete wavelet transformation (DWT) process. Specifically, to develop the wavelet-based unit root tests, Fan and Gençay (2010) defined {X}Tt = 1 as a univariate time series which can be represented as xt  xt 1   t t (1) is a weakly stationary zero mean error with a strictly positive long-run variance which can be represented as;     0  2  j (2)  j  E ( t  t  j ) (3) 2 j 1 The test is only applicable to the linear trend and non-zero mean cases. Assuming that the process {xt} can be defined as: xt    t  xts Where, (4) xts is produced from equation (1). s If the null hypothesis H0: β = 1, then { xt } is a unit root process. On the other hand, if s H0: β < 1, then { xt } is a zero mean stationary process. If γ = 0, then the demeaned series is ( xt Where, x 1 T  xt T t  x ). , (5) defines the sample mean of { x t }. If γ ≠0, then the detrended series is ( x t  x ). 191 T Where, xt   (x j   x) (6) j 1 defines the sample mean of { x t }. x is the sample mean of xt . Where, And xt  xt  xt 1 (7)  x t is the mean of xt . Subject to the unit scale discrete wavelet transformation (DWT), Fan and Gençay (2010) established two test statistics, for the aforementioned demeaned and the detrended series. The test statistics for the demeaned series is defined as: T /2 S LM T ,1   (B t 1 T  (x t 1 M t ,1 )2 (8) t  x) 2 Where BMt,1 denotes the scaling coefficient of the demeaned series. The test statistics for the detrended series is defined as: T /2 S LM T ,1   (B t 1 ) (9) T  (x d 2 t ,1 t  x) 2 t 1 Where Bdt,1 denotes the scaling coefficients of the detrended series. These two can be used to test the null hypothesis, H0: β = 1 against the alternative hypothesis, H1: β < 1in model (1). We use the monthly average stock index of the Nigerian Stock Exchange for the period of January 1985 to June 2015. The data is collected from the Central Bank of Nigeria (CBN) Statistical Bulletin. EMPIRICAL RESULTS The outcomes of the wavelet-based unit root tests of the test statistics for Equations. (8) and (9) are as shown in Table 1. 192 TABLE 1: WAVELET UNIT ROOT TESTS Stock Indices Test Statistics Ld LM Lag 5 Lag 10 Lag 15 Lag 20 Lag 25 Lag 30 S T ,1 S T ,1 -97.2* -96.2* -96.1* -95.2* -95.8* -94.9* -412.2* -408.2* -407.5* -403.4* -402.7* -402.3* Notes: * Denotes significance at the 1% level. The test statistic based on Eq. (3) clearly rejects the null hypothesis. The test statistic based on Eq. (4) affords sufficient evidence to reject the null hypothesis despite the different lag lengths. The use of six different lags: 5, 10, 15, 20 (the optimal choice), 25 and 30 ensures the robustness of our results. In the final analysis, we compare our wavelet results with a battery of traditional unit root tests such as Augmented DickeyFüller (ADF), Phillips and Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS). The ADF, PP, ADF-GLS, and KPSS reveal the fact that the series are non-stationary in levels, irrespective of the level of confidence (i.e. 1 %, 5 % or 10 %). On the contrary, the same tests in first-order differences confirmed that the series evolution is I(1) process as shown in Table 2. TABLE 2: TRADITIONAL UNIT ROOT TESTS Constant Constant and Trend ADF -6.501754* (9) -7.430542* (9) DF-GLS -0.849515* (9) -4.488887* (9) PP -6.288269* (3) -7.267419* (3) KPSS 0.195439* (3) 0.085535* (3) Notes: * Denotes significance at the 1% level. “(k)” denotes the lag length. Selection of lag length in ADF DF-GLS test is based on the SIC, NP test is based on the Spectral GLSdetrended AR based on the SIC and the PP test is based on the Newey–West with a Bartlett kernel. Evidence from this study has therefore shown that the prices of stocks on the Nigerian Stock Exchange are random. According to Nwosa and Oseni (2012; p. 42): “The efficient market hypothesis is based on the proposition that stock price fully reflect all available information in the market and investors cannot use available information or any trading rules to earn extraordinary returns or use available information to exploit the market.” While contrary evidence of the Nigerian stock market has been reported in Olowe (1999), Vitali and Mollah (2010) and Nwosa and Oseni (2012), similar evidence 193 was found by Ajao and Osayuwu (2012). Although some empirical evidence from Nigeria and other emerging stock markets negates the efficient market hypothesis, however our empirical evidence shows that the Nigerian stock market is informational efficient. That is to say, stock prices actually possess all available information in the market and hence financial analysts cannot earn abnormal returns from stocks, using previous stock prices to foresee the pattern of future stock returns. Evidence from this study has therefore shown that the prices of stocks on the Nigerian Stock Exchange are random. CONCLUSIONS This paper investigates the efficient market hypothesis in Nigeria, testing for the efficiency of the Nigerian stock market, using the Fan and Gençay’s (2010) wavelet unit root test approach with different lag lengths. Further, we used a battery of traditional unit root tests to ensure the robustness of our results. The wavelet-based unit root tests show clear and conclusive evidence that the Nigerian Stock Market follows the random walk behavior during the studied period. That is, the market is efficient. In other words, the stock prices fully reflect all available information in the Nigerian Stock Market and investors, armed with the available information or the trading rules, cannot exploit the market to earn extraordinary returns. Although some empirical evidence from Nigeria and other emerging stock markets negates the efficient market hypothesis, however our empirical evidence shows that the Nigerian stock market is informational efficient. That is to say, stock prices actually possess all available information in the market and hence financial analysts cannot earn abnormal returns from stocks, using previous stock prices to foresee the pattern of future stock returns. Evidence from this study has therefore shown that the prices of stocks on the Nigerian Stock Exchange are random. This has vital consequences on the fortunes of equity investors. Since the Nigerian Stock Market is efficient, investors should desist from futile attempts to forecast share prices. Policy makers can come to the aid of potential investors, to enlighten them of the opportunities available in the market in order to stimulate their interest and thus deepen the breadth of the capital market. As well, to augment the informational efficiency of the Nigerian stock market, durable and adequate supervision by the regulatory authorities is necessary. Coupled with appropriate policies, this would preclude any stock price bubble while ensuring that information about stock prices is a true reflection of share values. 194 ENDNOTES The term “beat the market,” refers to the ability of investors to produce a better return than the market average which is usually benchmarked with S&P 500 or the Dow Jones industrial Average Index. 2The weak form of efficient market hypothesis describes a market in which historical price data are efficiently digested and, therefore, are useless for predicting subsequent stock price changes (see Hagin. 1979). 1 APPENDIX FIGURE 1 TREND IN STOCK PRICE INDEX, CRUDE OIL PRICE AND EXCHANGE RATE IN NIGERIA 2010-2014 Movement Stock Price Index, Crude Oil Price and Exchange Rate 2010-2014 200 150 100 50 0 2010-M1 2010-M4 2010-M7 2010-M10 2011-M1 2011-M4 2011-M7 2011-M10 2012-M1 2012-M4 2012-M7 2012-M10 2013-M1 2013-M4 2013-M7 2013-M10 2014-M1 2014-M4 2014-M7 2014-M10 50,000.00 40,000.00 30,000.00 20,000.00 10,000.00 0.00 All Share Price Index IFEMDollar Crudeoilprice Note IFEM Dollar implies interbank foreign exchange market while Crude oil price is Price of Nigeria Burning Light Crude oil. 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The Efficient Market Hypothesis: A Critical Review of the Literature Mehwish Naseer* and Yasir bin Tariq** An efficient capital market is one in which security prices adjust rapidly to the arrival of new information. The Efficient Market Hypothesis (EMH) suggests that security prices that prevail at any time in market should be an unbiased reflection of all currently available information and return earned is consistent with their perceived risk. Theoretical and empirical literature on EMH offers mixed evidences. Some studies have supported the hypothesis, while others have revealed some anomalies, i.e., deviations from the rules of EMH. This review paper presents an analysis of EMH and possible causes and evidences of anomalies. It also examines stock market efficiency in Karachi Stock Exchange. Introduction A market is said to be efficient with respect to information if the price ‘fully reflects’ all available information regarding securities. Efficient Market Hypothesis (EMH), one of the most eminent and influential of modern financial theories, assumes that all relevant information is rapidly incorporated in security prices as released. However researchers and investors disagree with EMH both empirically and theoretically. The emergence of Behavioral Finance (study of finance from the perspective of psychology and sociology) by the start of 21st century has opened new avenues of research. The focus of discussion shifted from efficient market model to the behavioral and psychological aspects of market players. It comprehended that unlike traditional economic theory, psychological theory could account for the irrationality and illogicality in behaviors. It is claimed that stock prices are predictable and it is possible to consistently and purposefully outperform a given market using these predictable patterns. The ‘Stock Market Crash of 1987’, when the DJIA fell by over 20% in a single day, also empirically contradicted EMH. Supporters of behavioral finance attributed market inefficiency to the combination of conventional economic and financial theory with behavioral psychological theories and cognitive biases like personal judgment, overconfidence, overreaction, expectations regarding future, word-of-mouth optimism/pessimism, ego involvement, self-esteem and self-attributed * ** Research Scholar, Department of Management Sciences, COMSATS Institute of Information Technology, Abbottabad, Khyber Pakhtunkhwa, Pakistan. E-mail: mehwishnaseer77@gmail.com Assistant Professor, Department of Management Sciences, COMSATS Institute of Information Technology, Abbottabad, Khyber Pakhtunkhwa, Pakistan. E-mail: yasirtariq@ciit.net.pk © 48 2015 IUP. All Rights Reserved. The IUP Journal of Financial Risk Management, Vol. XII, No. 4, 2015 biases. Calendar effects, predictable patterns of valuation parameters (P/E and B/MV ratios), short-term momentum and tendency of returns to reverse over long run also contradict EMH. EMH was mostly attacked on the grounds of the speed with which information is supposed to reach market players. Critics argued that information cannot be readily incorporated in security prices as assumed by EMH. Empirical evidences, though, have shown mixed results, not strongly supporting EMH. The present paper aims to review the status of EMH with special emphasis on Karachi Stock Exchange. This review paper explains market anomalies with respect to market efficiency and Behavioral Finance. The paper is structured as follows: it explains the EMH and the assumptions and forms of EMH with theories related to market efficiency., followed by a review of the existing literature regarding tests of three forms of EMH along with existence. Subsequently, it provides evidences and possible causes of market anomalies and focuses on previous research related to market efficiency in developing countries with special reference to Karachi Stock Exchange. Finally, it offers the conclusion. The Efficient Market Hypothesis The EMH, one of the most accepted and eminent financial theories, stated that new information readily incorporated in security prices and market activities or analysis of historical and present data cannot help investors to predict future or to earn above average risk adjusted profit. Moreover, expected return based on this price is consistent with risk, implying that arbitrage opportunities are not viable to consistently identify and exploit. EMH is primarily based on random walk model, according to which information comes into market in random and unpredictable manner and price changes are thus expected to be random and independent. It is suggested that above average return is associated with above average risk. Efficient market hypothesis rests on three crucial arguments or assumptions: 1. Investors are assumed to be rational and value securities on the basis of maximum expected utility. 2. If investors are not rational, their trades are assumed to be random, offsetting any effect on prices. 3. Rational arbitragers are assumed to eliminate any influence irrational investors have on market/security prices. Forms of Efficient Market Hypothesis Efficient market hypothesis can be categorized into weak form, semi-strong form and strong form EMH (Figure 1). Weak form EMH is consistent with random walk hypothesis, i.e., stock prices move randomly, and price changes are independent of each other. It states that security prices reflect all market information regarding the security, i.e., historical price data. Therefore, it is not possible to beat the market by earning abnormal returns on the basis of technical (trend) analysis (where analysts accurately predict future price changes through the chart of The Efficient Market Hypothesis: A Critical Review of the Literature 49 Figure 1: Forms of Market Efficiency Strong Form (All Public and Private Information) Semi-Strong Form (All Public Information) Weak Form (All Security Market Information) past price movements of stocks). According to semi-strong form EMH, prices adjusted rapidly according to market and public information, i.e., dividend and earning announcements and political or economic events. So it is not possible to earn abnormal returns on the basis of fundamental analysis. Strong form EMH states that prices reflect market, public and private information, i.e., no investor has monopolistic access to information. Theories of Efficient Markets Fair Game Model Empirical literature on market efficiency also suggested that market equilibrium can be stated in terms of expected return and equilibrium expected return is a function of risk associated with securities; somehow it follows the Sharpe-Lintner ‘two parameter model’ and leads to ‘fair game model’. Fair game model depicts that as current prices reflect all new information, investors trading at prevailing market prices earn a return consistent with risk. Competition among a large number of profit-maximizing and price-sensitive investors adjusts prices rapidly to the arrival of new information, so no investor can anticipate the information or market pattern. Moreover, numerous and assertive transactions among a large number of traders move the prices quickly to the new equilibrium, reflecting all new information and thus making the market more efficient. Submartingale Literature also suggested that price sequences for securities follow a submartingale. Submartingale is a fair game model which states that next period prices are expected to be greater than current period prices, so knowledge of past events never help to predict the future values. Trading rules based on past information cannot help investors earn above average risk adjusted profit than a simple buy-and-hold policy. 50 The IUP Journal of Financial Risk Management, Vol. XII, No. 4, 2015 Random Walk Model Early studies on market efficiency were mostly based on random walk model; stock price changes are independent of each other, having the same distribution, and so past trends or movements cannot be used to predict future movement and it is not possible to outperform the market without assuming risk. Random walk model as an extension of fair game model strongly supported the independent and unpredictable pattern of information. Literature Review Weak Form Efficient Market Hypothesis Weak form hypothesis assumes that security prices are adjusted rapidly on the arrival of new market information, i.e., past price and return trends. So it is not possible for investors to earn abnormal return on the basis of previous information. Researchers test the weak form efficient market hypothesis through measuring autocorrelation among returns and by examining the impact of different trading rules on stock prices. Studies indicated that over a short time period like 1, 4, 9 and 16 days, a serial correlation is found among returns of 30 stocks of DJIA for the period of 1957-1962. But these correlations are always found to be equal to zero, representing a linear independency among returns and thus consistent with market efficiency model (Fama, 1970). In order to justify the presence of nonlinear independency among stock returns, researchers also tested the performance of various trading rules. Y filter test that is basically ‘one security and cash’ trading rule is approved to be consistent with Fair Game Model. Alexander (1961) tested price indices from 1897-1959 for filters ranging from 1% to 50%. Fama and Blume (1966) tested and compared the effectiveness of various filters to buyand-hold policy for Dow Jones Industrial Average’s stocks. They empirically proved that filters cannot beat the simple buy-and-hold policy. Although some contradictory evidence also revealed that small filters (0.5%-1%) are inconsistent with submartingale, these filters outperform the buy-and-hold policy only if ignoring commissions and transactions cost. Fair game model also supported market efficiency when tested for Treasury bill market. Osborne (1962) and Fama (1965) also used run tests to support the random walk model and proved the independence of stock price changes over time. Security prices adjusted rapidly on the arrival of new information. Price adjustment may be imperfect, i.e., sometimes prices will be over-adjusted and in some cases it will be under-adjusted, but their randomness makes unbiased adjustments. Neiderhoffer and Osborne (1966) observed two deviations from randomness in common stock (limit order) prices in successive transactions. In a given series of price changes, where + is assigned to a positive change and – to a negative change, continuation (+ + +, – – –) is more likely to happen than reversal (+ + –, – – +). They justify this non-random behavior The Efficient Market Hypothesis: A Critical Review of the Literature 51 by arguing that inefficiency is due to the specialist’s activity on NYSE trading floor as they have monopolistic access to unexecuted limit orders in a given stock. Semi-Strong Form Efficient Market Hypothesis Semi-strong form market hypothesis is concerned with the assumption that current prices fully reflect the publicly available information (announcement regarding earnings, dividends, stock splits, new issues, etc. and other economic or political events). Studies revealed that information regarding stock split is fully reflected in stock prices when actual stock split happens. Investors cannot gain from split information once it is announced publicly (Fama et al., 1969). Ball and Brown (1968) used three classes of data, i.e., contents of income reports, dates of report announcement and security price movements around announcement dates of 261 larger firms. The data obtained from Standard & Poor’s Compustat tapes examine the effect of annual earnings announcements. Residuals from a time series regression of firm’s annual earnings are used to classify earning as decreased or increased. Results revealed that only 1015% of the information regarding annual earnings announcement has been anticipated. A similar study was conducted by Waud (1970) to measure the impact of announcement of discount rate changes by Federal Reserve Bank. The first trading day following the announcement depicted a statistically significant announcement effect, but the magnitude was just 5%. Scholes (1969) examined the impact of new issues of stock and large secondary offerings of common stock on security prices. He proved that market on the average has fully adjusted to the information and followed a random pattern as corporate insiders needed to report to the Security and Exchange Commission within six days of sale. Alford and Guffey (1996) observed seasonality over two time periods: 1970 to 1994 and 1983 to 1994 in 18 countries (including the G7). ANOVA and Friedman Rank Sums were used to analyze return data stated in terms of dollar. The data from 1970 to 1994 revealed some calendar effect for Canada, France, Germany, and Italy. No significant evidence was found for seasonality in US, UK and Japan. They inferred that seasonalities may not exist and that investors cannot utilize the patterns to predict prices. All available evidences were found to be consistent with efficient market model. Strong Form Efficient Market Hypothesis Strong form market hypothesis is concerned with the assumption that all available information is incorporated in security prices and no investor has monopolistic access to the private information. So no investor is able to earn above average risk-adjusted profit by anticipating the information. Jensen (1968) used the Sharpe and Lintner model of equilibrium expected return and analyzed the returns of 115 mutual funds for a time period of 10 years (1955-1964). As a proxy/norm of market portfolio, he used Standard & Poor’s 500 index. He proved empirically that regardless of the fact that fund managers, specialists and market insiders have a wide 52 The IUP Journal of Financial Risk Management, Vol. XII, No. 4, 2015 range of business and financial contacts, no group has access to the private information and they cannot anticipate the future returns. Financial Market Anomalies The literary meaning of the word ‘anomaly’ is an unusual or odd occurrence. Frankfurter and McGoun (2001) defined anomaly as indiscretion or a deviation from an ordinary or natural order or an extraordinary condition. According to them, anomaly is generic in nature and applies to any underlying novelty of fact, new or unanticipated phenomenon or a surprise regarding any theory, hypothesis or model. The presence of anomalies indicates market efficiency. Anomalies exhibit different behaviors with respect to time; some occur only once and then vanish, while others occur recurrently, or continuously. An anomaly represents divergence from the currently accepted standard that is too extensive, systematic and too fundamental to be ignored, cannot be rejected as random error or dismissed by relaxation of the normative scheme (Tversky and Kahneman, 1986). Latif et al. (2011) discussed different anomalies, their causes and some behavioral aspects of such anomalies. Anomalies are categorized into calendar anomalies (weekend effect, turn of the month effect, year effect and January effect), fundamental anomalies (value anomaly, low price to book, low price to earnings, neglected stocks, high dividend yield) and technical anomalies (moving averages, i.e., buying stocks when short-run average return rises over long-run averages and selling the stocks when short-run averages fall below the long-run averages, trading range break, i.e., buying of a stock when the prices rise above last peak and selling when prices fall below last trough). It is concluded that calendar, fundamental, technical analysis and insider trading can be used to earn abnormal profit, thus negating the efficient market hypothesis. Value Versus Growth Anomaly Funds with above average rate of growth and earnings are referred to as growth funds/stocks, while those with lower than average sales and earnings as value stocks. Graham (1962) suggested that value strategies outperform the growth strategies. According to Lakonishok et al. (1994) the market overestimates the potential growth of growth funds, though the value stocks perform as well compared to growth stocks. Individual investors overestimate growth funds on two main grounds, either because of judgmental errors or they attributed future performance to past performance or growth though that growth rate is not likely to persist in future. Institutional investors, though, rarely make judgmental error; however they prefer growth stocks because of sponsor’s preferences of outperforming firms. Lakonishok et al. (1994) are of the view that time horizon is also of considerable importance and investors favor growth stocks over value stocks as they desire above average return in a short period of time. Some researchers attributed superior performance of value stocks to the risk factor associated with these stocks. Calendar Anomalies Calendar anomalies are the anomalies related to particular time period. Researchers documented some unusual seasonal returns like strong January return (Haugen and Jorion, The Efficient Market Hypothesis: A Critical Review of the Literature 53 1996), Monday return (Fama, 1980) and around holidays return (Ariel, 1990). Patel and Evans (2003) examined monthly return data of representative stock indexes for the G7 countries from 1960 to 2001. Stock return data exhibited a much broader seasonal pattern and was found consistent with efficient market theory. The study revealed a significantly higher average monthly return from December through May than from June through November and confirmed the presence of higher January effect in all G7 countries. Agrawal and Tandon (1994) examined five different seasonal patterns (weekend, turn of the month, Friday, January and monthly effect), for 18 countries, including the G7, from 1971 to 1987. The results suggested a broad seasonal pattern of stock returns than the January effect. Chen and Chan (1997) also tested seasonality of the US financial data series for eleven different securities (stock, bonds, bills) for the period 1926 to 1990, under controlled economic condition. No seasonality was found in six of the eleven series, while a stronger January effect was exhibited by small stock firms during periods of economic expansions. Chen and Chan suggested a broader seasonal pattern of stock returns as large stocks showed strong summer returns. A very complex and differing pattern of seasonality was demonstrated by the rest of the series in different economic conditions across differing time intervals. However, after the consideration of the transaction cost, these calendar effects are found to be very small and ineffective. ‘January Effect’ (rise of prices in very early days of New Year), seemed to disappear as soon as they got considerable publicity. Under-Reaction and Overreaction Wouters (2006) suggested that the security market’s over and under reaction is due to investor’s psychological and cognitive behaviors. Barberis and Shleifer (2003) attributed the under-reaction to the conservatism of the investors as they remain stuck to the previous information with the expectation that the security would behave in the same manner as it did earlier. The slow reaction of the investor (the investors do react to the prior information but not in the same manner as required by the information to do and stick to the prior information expecting that the security would do the same as it was doing in the past), named as conservatism, causing the under-reaction. These arguments seemed to be consistent with the conservatism described by Edwards (1968) as slow reaction ...
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