THE DEGREE OF MARKET EFFICIECNY/ INEFFICIENCY
A Look at Academic and Professional Research
by Hassan Adil
There is abundant amount of research done on the efficiency of the markets. However, the academics and professionals have yet to come to a conclusion about the degree of efficiency. This study will contribute to the understanding of the efficient market hypothesis, as first proposed by Fama. Later the paper will discuss the weak form, semi-strong, and briefly, the strong form of the market efficiency. This paper will synthesize academic research spanning from the 1960’s to 2010 regarding market efficiency. Finally this still will also provide a conclusion regarding the degree of the market efficiency after weighing and discussing the research conducted so far about the efficiency of the markets.
For the full text, continue to the article.
The financial world suffered one of the worst financial meltdowns since the “Great Depression” in 2008, and it has triggered the decades old debate of the degree of the efficiency in financial markets (Elliot, 2008). This is a controversial topic and it is heatedly debated among academics and professionals. However, the public has much to gain and lose from this debate as well, because inefficiencies in the stock market can affect general economic conditions. For example the most recent financial crisis that began in the U.S in 2008 has caused recession and other economic woes worldwide. The financial meltdown of 2008 highlighted the discrepancy in the academic and professional world, where professionals argue that it was the lack of the efficiency of the financial markets that caused the meltdown. Some academics agree with this thought; however research shows that the financial markets can be efficient and still have instances of mispricing.
For a passive investor the debate of market efficiency is important because it determines whether doing their own research is worth the effort or would they be better off giving their investments to a fund manager or buy major indices. For business analysts, this research influences their way of business valuations. If markets are inefficient then the Capital Asset Pricing Model (CAPM) will not hold, as there is a disconnect between perceived risk and pricing of securities, therefore alternative means of valuing businesses will be required.
The research on market efficiency includes a wide array of quantitative and mathematical analysis, along with behavioural studies. This paper, however, does not focus on the mathematical analysis itself, but the results and the conclusions of the various researches. The paper will begin with a brief background on the definition of efficiency, including the various forms of efficient markets. It will use the groundbreaking research paper by Fama, written in 1970, to discuss the proposed degrees of market efficiency. The paper will later discuss the various academic and professional views on the efficient market hypothesis (EMH) and the degree of the market efficiency. Finally, the paper will combine the various academic and professional findings and analyze these studies to conclude on the degree of the market efficiency.
2.1 The Efficient Market Hypothesis (EMH)
The efficient market hypothesis was first discussed in the ground breaking journal “Efficient Capital Markets: A Review of Theory and Empirical Work” in 1970 by Eugene F. Fama. Accordingly an efficient market is the one in which the current price of a security “fully reflects” all available information. However, there are three assumptions associated with this efficient market: (i) no transaction costs (ii) information is free to all market participants, and (iii) “all agree on the implications of current information for the current price and distributions of future prices of each security” (Fama, May 1970). According to Fama, these conditions are “sufficient, but not necessary” for efficient markets, and therefore a market with transaction costs will be efficient, but only to a certain degree.
2.2 An Introduction to the Three forms of Market Efficiency
Fama proposes three degrees of market efficiency: weak-form, semi-strong form, and strong-form efficient. The weak-form efficiency uses all the historical set of information. Semi-strong efficient market uses all the historical prices and the all publicly available information. Finally, the strong form market uses all information, whether public or private to determine the price of the stock (Fama, May 1970).
The weak-form of market efficiency dictates that investors cannot make abnormal profits trading on historical prices. Weak-form efficiency fully discounts technical analysis. The semi-strong form of market hypothesis suggests that investors cannot make abnormal return on the publicly available information because the stock price adjusts quickly enough to minimize any abnormal profits. The semi-strong form of market efficiency dictates that the fundamental or technical analysis will be useless in getting abnormal profits in an efficient market.
The last form of the EMH is also the stringiest form of efficiency, where it dictates that share prices incorporate all private and public information. Due to its rigour, this hypothesis is seldom accepted, and it is rarely true. There is lack of sufficient evidence that strong-form efficient is possible in any market. This paper is going to focus primarily on the weak and the semi-strong form of the EMH.
3.0 Review of Literature
3.1 Exploring the Three Forms of Market Efficiency
I am going to discuss the professional views before diving deeper into the more elaborate academic literature.
3. 2 Finance and Banking Industry and the EMH
The professional world, money managers, traders, and financial engineers are wondering the impact of the financial crisis on the EMH. According to the article Efficiency and beyond; Financial Economics in the “The Economist”, EMH theory was used to develop many financial models, which in-effect were the reason for the demise of the entire system (Anonymous, 2009). Financial engineers were developing financial products and selling it to customers with the confidence that these products are safe. They justified their fees with arguing that their activity was making the financial system “safer and the economy healthy” (Anonymous, 2009). Pablo Tarina writes in “Efficient market theory is not to blame” that investors were putting enormous faith in the market to price stocks and other financials correctly. Finance and banking professionals were also relying on the market to adjust itself automatically and did not pay attention to bubbles forming in market which eventually lead the housing market crash of 2008. Triana emphasizes that the EMH leads to reduced and careless policy making for the financial world, as the world views that the financial market mechanics are self-regulating. However, he further argues that the EMH isn’t the one to be blamed; it is the quantitative finance, and the “lax attitude” in regulations that caused the housing crisis of 2008 (Triana, 2009). But there are other critics that argue that the market has failed over and over again to price financial instruments correctly, showing irrational behaviour in multiple occasions, especially during the Internet Bubble and more recent housing crisis of 2008. Heath Hinegardner quotes Benjamin Garham, the father of value investing, in his article “Inefficient Markets are still hard to beat”, to be rather skeptical of EMH. Mr. Graham mentions EMH as a theory that “could have great practical importance if it coincided with reality” (Hinegardner, 2010). Hinegardner further argues that the markets are not efficient, referring to the semi-strong form of the market. Richard Thaler further improves on Hinegardner’s argument in his article “The price is not always right and markets can be wrong”, and says that the EMH’s proposition of stock price fully reflecting all available information is not correct as there are many instances where the stocks are priced inaccurately. He also mentions that there would have been no financial crisis if the stock market was truly efficient, as the prices would be efficient in adjusting if there was any error in the first place (Thaler, 2009).
There are some professionals that argue that EMH is actually true, say that the markets are semi-strong efficient. Swedroe argues in his article “Why a blind faith in market efficiency may not be right” that the best strategy for an individual to make money in the market is to use passive investment vehicles and use a “buy, hold, rebalance and tax-manage” strategy because he believes that the markets are highly efficient, hinting towards semi-strong form of market efficiency (Swedroe, 2010).
Overall, the professional view is split in the efficiency and in-efficient market. Most of the professionals however do agree that the market is at least weak-form efficient, that is, no abnormal profits can be made by using historical data. However there were some recurring trends and anomalies which point that it may be possible to make some profits by using recurring trends.
3.3 Academic Research
The academic research is split into hypothesis testing of the three forms of market efficiency, as proposed by Fama in his early research paper, Efficient Capital Markets: A Review of theory and Empirical Work: weak form, semi-strong form, and strong-form of market efficiency (Fama, May 1970).
3.3.1 Weak Form Market Efficiency Tests
In the study, Efficient Capital Markets: A Review of Theory and Empirical Work , Fama tests the expected return assumption of equilibrium markets (Fama, May 1970). Fama uses the serial correlations to determine whether the expected prices are dependent on historical prices or whether they show the characteristic of a random walk. The important step is to show that the subsequent prices changes are independent of each other, therefore they cannot be predicted by anyone, and thus it will be rather impossible to consistently generate abnormal profits based on this strategy. Fama used serial correlations between successive changes in the natural log prices of each 30 stocks that are part of the Dow Jones Industrial Average from the end of 1957 to September 26, 1962. He concludes that there is no evidence of substantial linear dependence between “lagged price changes or returns”. His results further strengthen earlier studies by Kendall, Moore and Alexander (Moore, 1962) (Kendall, 1953). All of the above tested linear dependence of the lagged prices of stocks. However, Alexander, also tested specific trading strategies. Alexander tested the trading strategy where an investor will hold a stock that has gone up y% and sell the security when it falls another y%. This system is called the “y% filter”. He tested daily data from 1897 to 1959 of 1% to 50% filters and did not find sufficient evidence that a trader can make money from this strategy over long periods of time (Alexander, 1961). Other tests regarding the weak-form of market efficiency deal with the tests of independence in the random walk by Fama (Fama, 1965). Fama found that there are certain departures from the random walk hypothesis, i.e there is a tendency that “large price changes tend to be followed by large daily changes”. However, the signs are random, which further refutes the random walk hypothesis, but improves upon the market efficiency hypothesis later suggested by Fama in 1970.
Simon in her thesis An Examination of the Weak Form of the Efficient Market Hypothesis Within the Context of the NASDAQ Composite Index: A Test of the Forecasting Abilities of Artificial Neural Networks argues the weak form of the EMH is not a viable form of market efficiency. Simon used artificial neural networks (ANNs) model. The ANN model replicates the human learning process, where after certain iterations the ANN learns from its experience. The ANN study used the weighted index of all common stocks listed in the NASDAQ from September 1995 through October 2004. Simon shows results that the R2 is more than 0.70 and there is significant predictable power in the R2. She mentions that “..there are predictable patterns that can be recognized and incorporated into future predictions using the ANN model.” (Simon, 2005).
The above EMH studies were conducted in the U.S markets, and describe the efficient market hypothesis in a well developed and stable financial environment. The study by Jeffery E. Jarret and Zhenzhen Sun, entitled Daily Variation, Capital Market Efficiency and Predicting Stock Returns for the Hong Kong and Tokyo Exchanges, indicates that the weak-form market might not be present in the Tokyo and the Hong Kong stock exchanges (Sun & Jarret, 2007). Jeffery and Sun reinforce Simon’s point that the stock prices are predictable. They collected data from 601 firms listed on the Hong Kong in 2002 and gathered another 1906 firms listed on the Tokyo Stock Exchange as of 2003. The researchers examined the daily variation of the closing prices using ordinary least square method. Jarret and Sun found that the Hong Kong stock exchange has significant patterns in the daily variations after looking at the F-statistic and the t-statistic of the regression for days of the week and the entire regression. Tokyo Stock exchange results were not as strong as the Hong Kong exchange, as in the researchers could not find patterns specific to days of the week, however there was an identifiable patterns for days of the week effect on the closing prices of the securities. Their result refutes the EMH theory in the Asian markets.
3.3.2 Semi-Strong Form Market Efficiency Tests
Semi-strong efficient market uses all the historical prices and the all publicly available information. If there is any new information in the market, the prices of the stock will adjust instantaneously to reflect the fully available information. This new information could include stock splits, mergers and acquisitions, issuance of new securities or debt, change in bank and government interest rates, GDP, inflation and more. The study by Fama, Fisher, Jensen and Roll , The Adjustment of Stock Prices to New Information, was on the integration of new information into the stock prices. They researched 940 firms over the period of 1927 to 1959 to determine effect on stock prices after stock splits. Their hypothesis is that the stock splits do not provide any new quantitative information about the firm. They found that the firms chose to declare stock splits in “abnormally good times”. However there was little movement noticed after the stock split because the market anticipated increase in dividends. They found that approximately 71.5% of the total stocks covered increased dividends, but the ones that did not increase dividends or reduce dividends saw their stock prices go down as a result of lower market expectations. FFJR concluded that the data emphasizes that the stock market is efficient, and it fully adjusts to the new publicly known information of the stock split (Fama, Fisher, Jensen, & Roll, 1969). Groenewold and Kang discuss in their paper, The Semi-Strong Efficiency of the Australian Market, that the Australian market shows signs of semi-strong efficiency. They conducted their research using macro-economic data, as compared to micro-economic data being used by FFJR. Grownewold and Kang use share prices, money supply, real government expenditure and the price level as data inputs from the sample period of 1982 to 1988. The research concluded that the lagged returns have no significant joint explanatory power in regressions for share returns.
Research by Jones and Bacon, Surprise Earnings Announcement: A Test of Market Efficiency, examines the third quarter positive earnings surprises on stock prices. The study analyzed 50 firms from randomly selected dates (October 17, 2006, November 10, 2006 and November 13, 2006). The research uses statistical tests for significance and show that the stock prices adjusted rapidly to new positive prices after a surprise positive earnings announcement. Jones and Bacon say that positive surprise announcements increase an investor’s expectations about the future cash flows of the firm, therefore increasing more demand in the stock market, and increasing its prices. This immediate reaction of the stock market is seemed to be semi-strong (Jones & Bacon, 2007).
There are some academics that disagree with the semi-strong market efficiency. Fugate describes in his paper entitled “An Empirical Investigation of the Market Efficiency of Mutual Thrift Institution Initial Public Offerings” (1997) that the market is not semi-strong efficient as previously thought. Fugate conducted his research on the initial public offerings for mutual thrift institutions from January 1, 1992 through August 31, 1994. There were a total of 133 observations, however 30 were randomly chosen. Prices were collected at different time intervals after the initial public offering to determine the response rate of the market. He recorded that there was under-pricing in the IPO and the share prices changed for the entire 30 days after the IPO till they reached the correct price. This research refutes the semi-strong form market efficiency because the stock prices should have been adjusted automatically (and efficiently) to the right price instead of drifting (Fugate, 1997). In the study, Post-Earnings Announcement Drift and Market Participant’s Information Processing Biases, Liang agrees with lack of semi-strong market efficiency. He describes that the drift that results due to overconfidence in private information, and overconfidence/under-confidence in more reliable information, therefore leading to incorrect stock prices. He uses behavioural finance to discuss that there is an overreaction to news, and stock prices do not efficiently adjust to the new prices, and there is considerable evidence of price drifting. He used the one, and two year earnings forecast for 3,335 different firms from January 1989 to December 2000 and forecasts by the analysts to determine earnings surprises. He used OLS regression to determine whether there is statistical significance and found that there is considerable amount of drift present in the stock market, and the stock market is not semi-strong efficient (Liang, 2003).
3.3.3 Strong Form Market Efficiency Tests
The strong form of market hypothesis is the least realistic and the least tested. It is something that can hardly be ever seen in the real stock market. As proposed by Fama (1970) “the preceding discussions have already indicated the existence of contradictory evidence. In particular, Neidholfer and Osborne have pointed out that the specialists on the N.Y.S.E apparently use their monopolistic access to information concerning unfilled limit orders to generate market profits..” (Fama, May 1970). In particular this form of market efficiency is the least likely to be true. No further work was done on strong form of market efficiency.
In summary, the professional views and academic studies discussed above show that the financial economics is split into two corners, one which is highly skeptical, even of the weak-form of market efficiency, and the second side, which agree with Fama in regards to the efficient market hypothesis, especially the semi-strong form of efficiency. The key arguments are discussed here:
- The supporters of weak form of market efficiency believe that the historical prices do not carry a trend, and technical analysis cannot be used to earn abnormal profits. However, there are many studies that are devoted to market anomalies, but once the anomalies are published in finance journals, they tend to disappear fast. However, there are always new trends or patterns showing up (Bromberg, 1990). Many of the opponents of the EMH use market anomalies as a key point in their argument. Fama clearly mentions that no abnormal profits can be made from technical analysis after accounting for transaction fees. He mentions that the trends are not dependable, and if they were, these anomalies will dry up fast (Fama, May 1970).
- The opponents of the EMH argue that the academic studies are largely devoted to mathematics and its implications; however the real world is a lot more complex than the mathematical world. There are several assumptions that go into the efficient market hypothesis that are taken for granted which should be tested. For example, the assumption that the investors are rational, and they are fully aware of their capacity and also, they have the full information set as any specialist sitting in the trading pit in the N.Y.S.E is completely absurd (Thaler, 2009). This in fact implies that the market can only be efficient to the extent that the general public is rational and its accesses to the information. There are many studies, e.g (Liang, 2003) that describe market irrationality. The market is repeatedly facing bubbles and mispricing due to overconfidence and other behavioural aspects and it is unable to detect them in time to fix them before the bubbles burst. This was true for the 1987 bubble, the tech bubble and then again the housing crisis in 2008.
- Transaction fees and other real-market factors have largely been ignored in some of the studies. Fama (1970) discusses that when the market transaction costs are added to the various anomalies and the few market inefficiencies, then the profits will evaporate fast.
Overall, there is a heated debate about whether the markets are efficient or inefficient. The financial and banking industry is highly involved in this debate because this debate can determine the role of the government in controlling and overseeing the financial markets. The lax attitudes we have seen over the last three decades have given the U.S three bubbles (1987, 1999 and 2008). Even after all these financial bubbles, the government has continued to deregulate the financial industry and reduce policies concerning the various strategies used by banks and the financial statement requirements for publicly traded companies.
Next, we are going to discuss the various anomalies in respect with the EMH.
- Short-term under/over reaction to news announcements
Per (Bromberg, 1990), the market has shown contradictory evidence and one of them is the over and under reaction to news announcements. The market takes its time to fully converge to the appropriate price. He mentions that new shares are habitually offered at a discount. His views are similar to Fugate (Fugate, 1997), that the IPOs are not priced properly. Another addition to the argument is by Sun & Jarret (Sun & Jarret, 2007), who found that the Hong Kong and the Tokyo stock exchanges are not weak-form, and returns are predictable. However, there is a difference between empirical results and the statistical results. If there are too many successive movements of stock in one direction, then it might be implied that the returns are predictable. Behavioural finance dictates that such momentum in stocks can be easily explained by the psychology of the investor. According to Thaler if the investors see the prices rising, they are more prone to buy into it. But deviance from the stock price and drift do not impose that the markets are inefficient (Thaler, 2009). However, the markets are not random walk as described by the books. Per Malikel, “it is important to distinguish statistical significance from economic significance” (Malkiel, 2003). After the trading and holding costs are imposed into the scenario, it is seen, as reported by Odean, that such traders do not make abnormal profits (Odean, 1999). Fama also mentioned that after accounting for transaction costs, there will be minimal profits from such strategies (Fama, May 1970). Fama (1998) suggests again that there are as many under-reactions as there are over-reactions to the new information. Another blow to this particular anomaly is that such trends tend to disappear depending on the methodology, as proposed by Fama (1998) and disappear “when exposed to different methodologies”.
- Day-of-the-week patterns
There are many day-of-the-week patterns as observed by many researchers, and as documented by Broomberg (Bromberg, 1990).Kenneth French describes in his paper “Stock Returns and the Weekend Effect”, that there appear to be significantly higher returns on Mondays (French, 1980). However, Fama argues that such returns are not consistent and they cannot be relied upon in real terms to make abnormal profits, hence they are not breaking the EMH (Fama, 1998). It seems like different mathematical models portray a different results, and these results are not consistent from study to study.
- Small cap vs Big cap firms
The size of the firm has also been known to give different returns. Keim documents in 1983 that small capitalized firms provide 1% more than large capitalized firms. However, the point to consider is that the 1% risk premium is worth the extra risk taken by the investor? Also, there are no dependable trends that can be followed, that will allow investors to achieve these higher returns. This does not prove that the markets are inefficient; however it is just proving that EMH is true. As mentioned in the EMH, the price of a stock includes the risk associated with it, and smaller firms provide higher returns because they have a higher risk associated with them. This principle is reinforced by Fama and French, when they tested the beta of the stocks from 1963 to 1990, and found that the slope was flat, and not upwards (Fama, 1965). Another point to consider is that the small firms are more likely present higher returns because they beat out competition, and this will is reflected in the survivorship bias of the returns.
There are many more examples of market anomalies, such as “Growth vs Value Stocks”, long returns, ratio analysis (P/E, Dividends/ Price etc) and long run return reversals. However there is not enough time or space to discuss all these anomalies in detail. Malikel (Malkiel, 2003) and Fama (Fama, 1998) both discuss these anomalies in detail, and suggest that these anomalies are rather yet to be proven to be able to make abnormal profit. These anomalies are also not dependable from time to time, and they disappear after using different mathematical methodologies.
All in all, there is a lot of data and research done on the weak-form of efficient market hypothesis which leads me to believe that the markets are at least weak-form efficient. There is sufficient evidence support the weak-form of EMH that lead me to believe that technical analysis and historical prices do not have the capacity to predict future stock price. One has to agree that after researching enough data, one might be able to gather a few anomalies. What is important here is the real-life implications of the anomalies, which suggest that anomalies seem to fade away as fast as someone comes up with one. However, determination of the semi-strong of market efficiency is difficult, as there is just enough research and analysis done on it as with the weak-form market efficiency.
Abundant research has been done over the last two decades regarding semi-strong efficient markets, and no conclusive evidence has come forward that would either refute the argument fully, or to accept the semi-strong form. The research done above takes from the various disbelievers of the semi-strong market efficiency primarily because the markets have failed to show semi-strong efficiency and also Fama does not pose a strong argument as well.
As mentioned earlier, the semi-strong form of the EMH has two parts associated to it, the first one is that “no free lunch”, and the second part is that the price is right as mentioned by Thaler (Thaler, 2009). Fama argues that the semi-strong markets “fully reflect the all available public information” (Fama, May 1970). So now we are going to analyze the two parts of the semi-strong market efficiency to see their reasonability in real economic terms: risk adjustment and price adjustment.
- “There is no free lunch!”
The idea of the no free lunch means that there is identifiable risk that is attached to financial securities. This risk guides investors in determining if the specific security is viable for their particular use. For example, some retirement funds will invest a higher percentage in the long-term bonds than equity because equities tend to be more risky. However, in the financial crisis of 2008, there are visible signs that the risk attached to collateralized debt obligation (CDOs) was not fully mentioned in the market, even though it was giving an enormous benefit to the banks and its holders in terms of high returns. However, the EMH mentions that the risk attached to the security cannot be avoided, which in this case is the downfall in the value of the CDOs after the collapse of the housing market. Housing bubbles have been pointed out much earlier than the 2008 crisis. Per (Anonymous, 2009), Thaler mentions “no-free lunch part, and price-is-right part, and if anything the first part has been strengthened as we have learned that some investment strategies are riskier than they look and it really is difficult to beat the market”. Eventually the risk of the asset cannot be avoided, and the market will feel the affect even if the risk is not fully disclosed.
- The Price is Right
Behavioural economics has pointed out investor behaviours such as overconfidence in their own logic, pessimism when the market is doing badly, under/over reaction to news etc point out that the investors are not rational. Anonymous (Anonymous, 2009) , Hinegardner (Hinegardner, 2010) and Thaler (Thaler, 2009) explain that that there is significant evidence that the market is irrational. This irrationality adds to the growing volatility in the market in the recent two years. The question to be asked is: why is the market so volatile, even though there is no change in the fundamentals of some of the companies? Per Hinegardner, the market is measuring the stocks in speculative environment, instead of investment environment, where the prices are based on the intrinsic value of the shares. He quotes Benjamin Graham as saying that the market is a voting mechanism in the short run, and a weighing mechanism in the long-run. Malikel (Malkiel, 2003) and Swedroe (Swedroe, 2010) agree with Hinegardner that the price is not always right, and it is not fully reflective of the intrinsic value. Just because of this, there are bubbles that keep on forming in the market. These bubbles happen when the market bases the stock prices on the future expected cash flows that the company may never achieve, for example the internet stocks in 1999 were primarily based on the growth expectation. There were companies that were being valued solely on the growth perspective, even though the cash flows outlook was much worse. Hinegardner quotes Benjamin Graham regarding speculative environment as “I deny emphatically that because the market has all the information it needs to establish a correct price the prices it actually registers are in fact correct”. His views are now resonating throughout the professional world, adding to the skepticism about the semi-strong market efficiency theory.
The backers of the EMH argue that the “popping” of the bubble implicates that the markets are conforming to the EMH, that is the markets are reflecting the true price. There are several questions that arise after that statement, especially that the prices are supposed to adjust “instantaneously” when new information is released. This latter argument is saying that prices could be wrong for some length of time before reverting to the original price, so are the markets really efficient if the waiting period is as long as a year? The answer will be a definite no. Overall, the turbulent financial history of the U.S has proven overtime that the semi-strong market efficiency is not fully functional. The market seems to be working efficiently only under certain conditions, therefore disproving the fact that semi-strong efficiency is true all the time.
The recent financial turmoil in the world has renewed interest in the decade old debate of market efficiency and inefficiency. This debate has consequences for governments, finance professionals and individuals alike. If the markets are as efficient as thought by the government (semi-strong), then there should be less number of controls and regulations over the financial industry. Professionals will have to be more cautious when selling financial instruments to clients if they cannot rely on the markets to adjust itself. Individual investors will have to determine their investment strategies depending on the efficiency of markets to get the highest return possible. There will be a shift in the market from selling mutual funds to indeces if the semi-strong market efficiency is proven wrong. There are huge financial and economical consequences of this debate.
The studies reviewed here strongly approve of the weak-form of market efficiency, however there are mixed reviews over the various studies about semi-strong market efficiency. The study of the various research papers by academics have proved that the market shows signs of semi-strong efficiency only in certain cases, such as stock splits, dividend announcements, mergers and acquisitions, and initial public offerings. However, time-series and cross-sectional tests give a different picture that the market do not conform to semi-strong. Finance professionals add on by saying that EMH holds in certain cases, however the recent bubbles dictate that the market may not be semi-strong efficient. The paper concludes that the market lies somewhere between weak and semi-strong form efficiency. However, this area of finance requires a lot more research to better understand the true market efficiency.
Alexander, S. S. (1961, May 2). Price Movements in Speculative Markets: Trends or Random Walks. Industrial Management Review , 199-218.
Anonymous. (2009, July 18). Efficiency and Beyond; Financial Economics. The Economist. London. , 392 (8640), p. 68.
Bromberg, M. (1990, May). The Efficient Markets Hypothesis. Management Accounting , 36-39.
Cherny, A., & Madan, D. (2006). On Measuring the Degree of Market Efficiency.
Elliot, L. (2008, March 18). Guardian.co.uk. Retrieved March 20, 2010, from Guardian: http://www.guardian.co.uk/business/2008/mar/18/creditcrunch.marketturmoil1
Fama, E. F. (May 1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, Volume 25, Issue 2, Papers and Proceedings of the Twenty-Eigth Annual Meeting of the American finance Association New York, N.Y. December 28-30 1969 , 1-36.
Fama, E. F. (1998). Market Efficiency, long-term returns and behavioral finance. Journal of Financial Economics , 49, 283-306.
Fama, E. F. (1965, January). The Behaviour of Stock Market Prices. Journal of Business 38 , 34-105.
Fama, E. F., Fisher, L., Jensen, M., & Roll, R. (1969, February). The Adjustment of Stock Prices to New Information. International Economic Review , 1-21.
French, K. (1980). Stock Returns and the Weekend Effect. Journal of Financial Economics (8), 55-69.
Fugate, R. L. (1997). An Empirical Investigation of the Market Efficiency of Mutual Thrift Institution Initial Public Offerings. School of Business and Entrepreneurship Nova Southeastern University , 1-220.
Groenewold, N., & Kang, K. C. (1993). The semi-strong efficiency of the Australian share market. Economic Record , 69 (207), 405.
Hinegardner, H. (2010, January 9). The Wall Street Journal. Retrieved March 18, 2010, from Intelligent Investor: http://online.wsj.com/article/SB10001424052748703535104574646530815302374.html
Jones, N., & Bacon, F. (2007). Surprise Earnings Announcement: A Test of Market Efficiency. Allied Academics International Conference , 43-48.
Kendall, M. G. (1953). The analysis of Economic Time-Series, Part I: Prices . Journal of the Royal Statistical Society , 96.
Liang, L. (2003). Post-Earnings Announcement Drift and Market Participants’ Information Process. Review of Accounting Studies , 321-346.
Malkiel, B. G. (2003). The Efficient Market Hypothesis and its Critics. The Journal of Economic Perspectives 17(1) , 59-82.
Moore, A. (1962). A Statistical Analysis of common Stock Prices. Unpublished Ph.D thesis, Graduate School of Business, University of Chichago .
Odean, T. (1999). Do Investors Trade Too Much. American Economic Review , 1279-1298.
Rattiner, J. H. (2002, June 1). Efficiency Expertise: Relying on the efficient market hypothesis when evaluating portfolios may give your clients a false sense of security. Financial Planning , p. 1.
Simon, H. K. (2005). An Examination of the Weak form of the Efficient Market Hypothesis within the Context of the NASDAQ Composite Index: A Test of Forecasting Abilities of Artificial Neural Networks. The H. Wayne Hulizenga School of Business and Entrepreneurship Nova Southeastern University , 166.
Sun, Z., & Jarret, J. E. (2007). Daily variation, capital market efficiency and predicting stock returns for the Hong Kong and Tokyo Exchanges. Applied Economics (41), 3477-3482.
Swedroe, L. (2010, March 3). Why Blidn Faith in the Market Efficiency May Not Be Right. Retrieved March 19, 2010, from Moneywatch.com: http://moneywatch.bnet.com/investing/blog/wise-investing/why-a-blind-faith-in-market-efficiency-may-not-be-right/1254/
Thaler, R. (2009, August 15). ABI/INFORM. Retrieved March 18, 2010, from Document ID: 1818759001: http://proquest.umi.com.proxy.lib.uwaterloo.ca/pqdweb?index=0&did=1818759001&SrchMode=2&sid=1&Fmt=3&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1269404447&clientId=16746
Triana, P. (2009, June 22). Efficient Markey Hypothesis is not to be blamed. Financial Times. (Surveys Edition), 11. London , UK.