The EMH was developed by Professor Eugene Fama at the University of Chicago Graduate School of Business as an academic concept of study through his published Ph.D. thesis in the early 1960s at the same school.
The efficient-market hypothesis emerged as a prominent theoretic position in the mid-1960s. Paul Samuelson had begun to circulate Bachelier's work among economists. In 1964 Bachelier's dissertation along with the empirical studies mentioned above were published in an anthology edited by Paul Coonter . In 1965 Eugene Fama published his dissertation arguing for the random walk hypothesis and Samuelson published a proof for a version of the efficient-market hypothesis. In 1970 Fama published a review of both the theory and the evidence for the hypothesis. The paper extended and refined the theory, included the definitions for three forms of market efficiency: weak, semi-strong and strong (see below).
Note that it is not required that the agents be rational (which is different from rational expectations; rational agents act coldly and achieve what they set out to do). EMH allows that when faced with new information, some investors may overreact and some may underreact. All that is required by the EMH is that investors' reactions be random and follow a normal distribution pattern so that the net effect on market prices cannot be reliably exploited to make an abnormal profit, especially when considering transaction costs (including commissions and spreads). Thus, any one person can be wrong about the market — indeed, everyone can be — but the market as a whole is always right.
There are three common forms in which the efficient-market hypothesis is commonly stated — weak-form efficiency, semi-strong-form efficiency and strong-form efficiency, each of which have different implications for how markets work.
Proponents of Behavioral Finance, Technical, Quantitative and Fundamental Analysis dispute the notion that markets behave consistently with the efficient-market hypothesis, especially in its stronger forms. Some economists, mathematicians and market practitioners cannot believe that man-made markets are strong-form efficient when there are prima facie reasons for inefficiency including the slow diffusion of information, the relatively great power of some market participants (e.g., financial institutions), and the existence of apparently sophisticated professional investors . The way that markets react to surprising news is perhaps the most visible flaw in the efficient-market hypothesis. For example, news events such as surprise interest rate changes from central banks are not instantaneously taken account of in stock prices, but rather cause sustained movement of prices over periods from hours to months.
Only a privileged few may have prior knowledge of laws about to be enacted, new pricing controls set by pseudo-government agencies such as the Federal Reserve banks, and judicial decisions that affect a wide range of economic parties. The public must treat these as random variables, but actors on such inside information can correct the market, but usually in a discreet manner to avoid detection. Another observed discrepancy between the theory and real markets is that at market extremes what fundamentalists might consider irrational behavior is the norm: in the late stages of a bull market, the market is driven by buyers who take little notice of underlying value. Towards the end of a crash, markets go into free fall as participants extricate themselves from positions regardless of the unusually good value that their positions represent. This is indicated by the large differences in the valuation of stocks compared to fundamentals (such as forward P/E ratios) in bull markets compared to bear markets. A theorist might say that rational (and hence, presumably, powerful) participants should always immediately take advantage of the artificially high or artificially low prices caused by the irrational participants by taking opposing positions, but this is observably not, in general, enough to prevent bubbles and crashes developing. It may be inferred that many rational participants are aware of the irrationality of the market at extremes and are willing to allow irrational participants to drive the market as far as they will, and only take advantage of the prices when they have more than merely fundamental reasons that the market will return towards fair value. Behavioural finance explains that when entering positions market participants are not driven primarily by whether prices are cheap or expensive, but by whether they expect them to rise or fall. To ignore this can be hazardous: Alan Greenspan warned of "irrational exuberance" in the markets in 1996, but some traders who sold short new economy stocks that seemed to be greatly overpriced around this time had to accept serious losses as prices reached even more extraordinary levels. As John Maynard Keynes succinctly John Maynard Keynes, "Markets can remain irrational longer than you can remain solvent."
The efficient-market hypothesis was introduced in the late 1960s. Prior to that, the prevailing view was that markets were inefficient. Inefficiency was commonly believed to exist e.g., in the United States and United Kingdom stock markets. However, earlier work by Kendall (1953) suggested that changes in UK stock market prices were random. Later work by Brealey and Dryden, and also by Cunningham found that there were no significant dependences in price changes suggesting that the UK stock market was weak-form efficient.
Further to this evidence that the UK stock market is weak-form efficient, other studies of capital markets have pointed toward them being semi-strong-form efficient. Studies by Firth (1976, 1979, and 1980) in the United Kingdom have compared the share prices existing after a takeover announcement with the bid offer. Firth found that the share prices were fully and instantaneously adjusted to their correct levels, thus concluding that the UK stock market was semi-strong-form efficient. The market's ability to efficiently respond to a short term and widely publicized event such as a takeover announcement, however, cannot necessarily be taken as indicative of a market efficient at pricing regarding more long term and amorphous factors.
Other empirical evidence in support of the EMH comes from studies showing that the return of market averages exceeds the return of actively managed mutual funds. Thus, to the extent that markets are inefficient, the benefits realized by seizing upon the inefficiencies are outweighed by the internal fund costs involved in finding them, acting upon them, advertising etc. These findings gave inspiration to the formation of passively managed index funds.
It may be that professional and other market participants who have discovered reliable trading rules or stratagems see no reason to divulge them to academic researchers. It might be that there is an information gap between the academics who study the markets and the professionals who work in them. Some observers point to seemingly inefficient features of the markets that can be exploited e.g., seasonal tendencies and divergent returns to assets with various characteristics. E.g., factor analysis and studies of returns to different types of investment strategies suggest that some types of stocks may outperform the market long-term (e.g., in the UK, the USA, and Japan).
Skeptics of EMH argue that there exists a small number of investors who have outperformed the market over long periods of time, in a way which is difficult to attribute to luck, including Peter Lynch, Warren Buffett, George Soros, and Bill Miller. These investors' strategies are to a large extent based on identifying markets where prices do not accurately reflect the available information, in direct contradiction to the efficient-market hypothesis which explicitly implies that no such opportunities exist. Among the skeptics is Warren Buffett who has Warren Buffett that the EMH is not correct, on one occasion wryly saying "I'd be a bum on the street with a tin cup if the markets were always efficient" and on another saying "The professors who taught Efficient Market Theory said that someone throwing darts at the stock tables could select stock portfolio having prospects just as good as one selected by the brightest, most hard-working securities analyst. Observing correctly that the market was frequently efficient, they went on to conclude incorrectly that it was always efficient." Adherents to a stronger form of the EMH argue that the hypothesis does not preclude - indeed it predicts - the existence of unusually successful investors or funds occurring through chance. In addition, supporters of the EMH point out that the success of Warren Buffett and George Soros may come as a result of their business management skill rather than their stock picking ability.
It is important to note, however, that the efficient-market hypothesis does not account for the empirical fact that the most successful stock market participants share similar stock picking policies, which would seem to indicate a high positive correlation between stock picking policy and investment success. For example, Warren Buffett, Peter Lynch, and George Soros all made their fortunes exploiting differences between market valuations and underlying economic conditions. This notion is further supported by the fact that all stock market operators who regularly appear in the Forbes 400 list made their fortunes working as full time businesspeople, most of whom received college educations and adhered to a strict stock picking philosophy they developed at a relatively early age. If "throwing darts at the financial pages" were as effective an approach to investment as deliberate financial analysis, one would expect to see casual, part time investors appearing in rich lists as frequently as professionals like George Soros and Warren Buffett.
The efficient-market hypothesis also appears to be inconsistent with many events in stock market history. For example, the stock market crash of 1987 saw the S&P 500 drop more than 20% in the Month of October despite the fact that no major news or events occurred prior to the Monday of the crash, the decline seeming to have come from nowhere. This would tend to indicate that rather irrational behavior can sweep stock markets at random.
Burton Malkiel, a well-known proponent of the general validity of EMH, has warned that certain emerging markets such as China are not empirically efficient; that the Shanghai and Shenzhen markets, unlike markets in United States, exhibit considerable serial correlation (price trends), non-random walk, and evidence of manipulation.
Despite the best efforts of EMH proponents such as Burton Malkiel, whose book A Random Walk Down Wall Street achieved best-seller status, the EMH has not caught the public's imagination. Popular books and articles promoting various forms of stock-picking, such as the books by popular CNBC commentator Jim Cramer and former Fidelity Investments fund manager Peter Lynch, have continued to press the more appealing notion that investors can "beat the market."
EMH is commonly rejected by the general public due to a misconception concerning its meaning. Many believe that EMH says that a security's price is a correct representation of the value of that business, as calculated by what the business's future returns will actually be. In other words, they believe that EMH says a stock's price correctly predicts the underlying company's future results. Since stock prices clearly do not reflect company future results in many cases, many people reject EMH as clearly wrong.
However, EMH makes no such statement. Rather, it says that a stock's price represents an aggregation of the probabilities of all future outcomes for the company, based on the best information available at the time. Whether that information turns out to have been correct is not something required by EMH. Put another way, EMH does not require a stock's price to reflect a company's future performance, just the best possible estimate or forecast of future performance that can be made with publicly available information. That estimate may still be grossly wrong without violating EMH.
Further empirical work has since highlighted the impact transaction costs have on the concept of market efficiency with much evidence suggesting that any anomalies pertaining to market inefficiencies are the result of a cost benefit analysis to those willing to incur the cost of acquiring the valuable information in order to trade on it. Tests to return predictability have shown this to be a factor which has been used to make the highlight the existence of an efficient market. Additionally the concept of liquidity is a critical component to capturing "inefficiencies" in tests for abnormal returns. Despite a stronger case being evident for an efficient market, any test of this proposition faces the joint hypothesis problem where it is impossible to ever test for market efficiency, since to do so requires the use of a measuring stick against which abnormal returns are compared. Thus how can one know if the market is efficient if the one does not know if their model correctly stipulates the required rate of return. Consequently, a situation arises where either the asset pricing model is incorrect or the market is inefficient, but one cannot know both answers at the same time.
Behavioural psychology approaches to stock market trading are among some of the more promising alternatives to EMH (and some investment strategies seek to exploit exactly such inefficiencies). A growing field of research called behavioral finance studies how cognitive or emotional biases, which are individual or collective, create anomalies in market prices and returns that may be inexplicable via EMH alone. However, how and if individual biases manifest inefficiencies in market-wide prices is still an open question. Indeed, the Nobel Laureate co-founder of the programme - Daniel Kahneman - announced his skepticism of resultant inefficiencies: "They're [investors] just not going to do it [beat the market]. It's just not going to happen.
Ironically, the behaviorial finance programme can also be used to tangentially support the EMH - or rather it can explain the skepticism drawn by EMH - in that it helps to explain the human tendency to find and exploit patterns in data even where none exist. Some relevant examples of the Cognitive biases highlighted by the programme are: the Hindsight Bias; the Clustering illusion; the Overconfidence effect; the Observer-expectancy effect; the Gambler's fallacy; and the Illusion of control.
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