The Efficient Market Hypothesis - Case Study Example

A Critique of Efficient Market Hypothesis:When the price of a stock can be influenced by a “herd” on Wall Street with prices set at the margin by themost emotional person, or the greediest person, or the most depressed person, it is hard to argue that the market always prices rational...in fact market prices are frequently nonsensical.” The Efficient Market Hypothesis has been praised by some security analysts as an enduring truth about financial markets. Ever since Eugene Fama coined the theory of the efficient markets in 1970, it has held a prominent position in investment theory. According to him, “in an efficient market any new information would be immediately and fully reflected in equity prices. Consequently, a financial market quickly, if not instantaneously, discounts all available information. Therefore, in an efficient market, investors should expect an asset price to reflect its true fundamental value at all times.” (Stanley & Samuelson, 2009, p.183) Seeing the apparent logical soundness of the EMH, Michael Jensen had famously stated that “there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.” (Stout, 2003, p.635) Looking back in retrospect, it is easy to see how popular the EMH had been during the middle of the century. In fact, not only did ‘market efficiency’ become a buzzword among financial analysts by the 1980s but the concept was recognized as fact even by regulators, judges and research scholars from other allied fields. (Shleifer & Summers, 1990, p.704) But the fad has faded over the last three decades. In the article titled The Superinvestors of Graham and Doddsville, author Warren Buffett gives a classic rebuttal of the Efficient Market Hypothesis. Buffett employs wit and humour alongside statistical evidence to present arguments in support of market inefficiency. Buffett gathers the investment performance of some eminent pupils of Benjamin Graham’s school of value investing – all of whom have also worked under Graham during the 1950s. These include Walter Schloss, Tom Knapp, Ed Anderson, etc, not to mention Buffett himself. The funds conceived and run by these stalwarts is now part of investment folklore, as they managed to outperform the markets year in and year out for decades. When we compare the annual published reports of funds such as Walter J. Schloss (WJS) Ltd. Partners, Tweedy Browne Inc., Buffett Partnership Ltd, and Sequoia Fund Inc, there is compelling evidence that contradicts EMH. For example, the annualized return of WJS Ltd. Partners is an impressive 16.1%, which is double the return fetched by S&P’s Index Fund over the corresponding 28 year period. Similar anomalies to the EMH are evident in Tweedy, Browne (TBK) Inc’s returns between 1968 and 1983. In this period, TBK’s overall annual compounded rate of return stood at 16% compared to S&P’s rather modest returns of 7%. Similar divergences are seen between S&P’s annualized returns and those of funds run by Buffett Partnership Ltd., and Sequoia Fund Inc. (Buffett, 1984, p.3) Hence, it is fairly obvious to the discerning analyst that Michael Jensen’s famous 1978 proclamation doesn’t hold good anymore. The proponents of EMH have empirical evidence stacked up against them. Prominent examples are that of Warren Buffett and his guru Benjamin Graham, who have ‘beaten the market’ consistently enough to disprove the claims of the EMT. The empirical evidence undermining EMH is growing by the year. For much of the history of financial markets, the idea of market efficiency has co-existed with a darker view that stock prices can at times disconnect from underlying economic reality. The events of the last three decades have only fed this sceptical view. “The seeds of doubt were first sown widely on October 19, 1987, when the Dow Jones Index of industrial stocks mysteriously lost twenty three percent of its value in a single trading session. More recently we have seen the appearance and subsequent bursting of a remarkable price bubble in technology stocks that rivals the famous Dutch Tulip Bulb Craze of 1637. To some extent, the entire stock market seemed to have been caught in the turbulence: in the Spring of 2000, the Standard & Poors 500 Index of 500 leading companies topped 1,500.7 By October 2002, the S&P Index was hovering near 775, a nearly fifty percent decline in value.” (Stout, 2003, p.635) In the light of such repetitive patterns, it is impossible for a discerning analyst to not suspect a breach in the Efficient Market Hypothesis. With powerful data repository systems and automated mathematical tools at the disposal of the analyst, it is possible today to look through the flawed assumptions and lack of rigor in the works of earlier generation of financial market experts who promoted EMH. As author Lynn A. Stout propounds in her journal article, the gaping holes of the EMH apparent to “anyone who cared to look for them within a few years after the theory was first developed and disseminated...one need not have waited several decades to develop this suspicion. Nor need we have suffered through the Crash of 1987 and the 1990s tech stock bubble to find enlightenment.” (Stout, 2003, p.636) Gilson and Kraakman’s pioneering work on the financial markets was condensed and presented in their article The Mechanisms of Market Efficiency (published in 1984). This work went a long way in exposing the weaknesses inherent in EMH. For a minority of EMH contrarians, it offered a meticulous and detailed enquiry into the Achilles heel of efficient market theory, namely, ‘how exactly does information flow into prices’. The EMH is only valid when market prices fully account for all available information pertaining to a stock. But, as Gilson and Kraakman point out, information is expensive to obtain, process, and verify. Consequently, it is near impossible for all market participants to “actually acquire, understand, and validate all the available information that might be relevant to valuing securities. Efficient market theory nevertheless predicts that even though information is not immediately and costlessly available to all participants, the market will act as if it were.” (Stout, 2003, p.635) This assertion is not true because arbitrageurs can ‘correct’ market prices only to a certain extent. In other words, arbitrageurs are not a homogenous lot, but instead comprised of distinct groups with different priorities and goals. In this context, as Gilson and Kraakman observe, “the answer could be found in the complex interaction of at least four imperfect price-moving market mechanisms: "universally informed trading;" "professionally informed trading;" "derivatively informed trading" (including both "trade decoding" and "price decoding"); and "uninformed trading." (Stout, 2003, p.637) The fact that market transactions are carried out today in fast digital networks with an abundance of relevant information has not altered this arrangement in any significant way. Gilson and Kraakman suggest another explanation for market inefficiency –that of “uninformed" trading. They assert that even if all investors had the same opportunity and facilities to access information relating to securities, one category of information remains out of their reach, namely, the prediction of future events and price movements. Consequently, investors tend to disagree in terms of their forecasts. But this disagreement is not a trivial matter in the securities market, as the following passage suggests: “Securities are nothing more than claims to a stream of future income, so minor disagreements in predictions can lead to major disagreements about valuations. Nevertheless, investors divergent forecasts may not lead to inaccurate securities prices, so long as mistakes in forecasting are random. In other words, the random biases of individual forecasts will cancel one another out, leaving price to reflect a single, best-informed aggregate forecast." (Stout, 2003, p.636) When we add human emotion to the mix of factors affecting decision making, then the projected trajectories of future earnings can vary widely from one analyst to another. Hence, another explanation for EMH’s weakness comes from the staples of Behavioural Finance, which shows how otherwise rational people often times make irrational choices. This is as true in the domain of financial markets as in any other human activity. The basic insight offered by scholars of Behavioural Finance is that “human emotion and error can influence investment choices just as they influence choices to play lotteries or wear seatbelts. The trick, of course, is to figure out in advance just how this influence operates. To do this, behavioural finance theorists rely on the psychological literature, and especially on empirical studies of human behaviour in experimental games, to identify predictable forms of "cognitive bias" that lead people consistently to make mistakes. They then examine whether these systematic biases can help explain or predict empirically-observed market anomalies that cannot be explained or predicted by rational-actor-based traditional finance.” (Stout, 2003, p.639) More explanations for inaccurate stock valuations are to be found in empirical research on specific stock market data. In an interesting study on the behaviour of the Austrian Stock Market, researchers Darrol J. Stanley and Bruce A. Samuelson find that the EMH generally works, but still throws up paradoxes on a regular basis. (Stanley & Samuelson, 2009, p.183) Some other theoretical challenges to the EMH are laid out below. Firstly, it is difficult to maintain the case that market participants are fully rational in the choices they make. As Fischer Black (1986) have identified, traders (especially) tend to trade on noise rather than substance. Lay investors too, in their own way, act on advice acquired from an investment guru who’s in fad. Lay investors are also susceptible to the habit of diversifying inadequately, churning over stocks too frequently in their portfolio, and to hold onto losing stocks on the back of hope as against real prospects, etc. There is also the tendency to buy mutual funds that charge a heavy fee and to follow stock quotations obsessively. All these behaviour patterns of investors, lay and professional alike, suggest that they barely pursue passive strategies expected of uninformed market participants by the efficient markets theory. (DeBondt & Thaler, 1987, p.6) Further, as Kahneman and Riepe (1998) note, “people deviate from the standard decision making model in a number of fundamental areas. We can group these areas, somewhat simplistically, into three broad categories: attitudes toward risk, non-Bayesian expectation formation, and sensitivity of decision making to the framing of problems.” (Shleifer, 2000, p.10) In terms of individuals’ attitudes toward risk, the precepts of Neumann-Morgenstern rationality hardly ever holds good. Empirical evidence suggests that investors look not at the overall returns that they could avail through a stock, but instead look at gains in the backdrop of an arbitrary reference point they’ve set. This reference point that denotes their perception of good and bad performance depends on numerous prevailing circumstances. They also “display loss aversion—a loss function that is steeper than a gain function. Such preferences—first described Prospect Theory—are helpful for thinking about a number of problems in finance. One of them is the notorious reluctance of investors to sell stocks that lose value, which comes out of loss aversion). Another is investors aversion to holding stocks more generally, known as the equity premium puzzle.” (Shleifer, 2000, p.10) Another phenomenon that counteracts the theory of efficient markets is the systematic violation of some theories of probability (including the Bayes rule). This manifests in investors’ predictions of uncertain outcomes. For instance, market players usually base their predictions on analyzing short history of price movements and try to understand what broader picture this history is representing. But such an understanding betrays the fact that they are not paying sufficient attention to the “possibility that the recent history is generated by chance rather than by the model they are constructing. Such heuristics are useful in many life situations—they help people to identify patterns in the data as well as to save on computation—but they may lead investors seriously astray.” (Shleifer, 2000, p.11) In conclusion, despite being a popular theory during the 1970s and 1980s, the EMH’s basic premise that stock value is fully reflected in quoted price has not stood the tests of time. As a result, few people talk of EMH with any degree of conviction. The market crash of October1987 was a major blow to believers in EMH. This event raised this important question: ‘How could the fundamental value of the stocks on the New York Stock Exchange fall almost twenty-five percent in two days when no significant macroeconomic event could be identified?’ As no analyst has since presented a satisfactory answer to this question, the theory’s grander aspirations remain far off. (Shleifer & Summers, 1990, p.704) Further, the pricing of Internet securities and the crash that followed should be “a fatal blow to the idea that security markets could effectively segregate the effects of noise traders and thus should be the end to the claim that market price and fundamental value are synonymous in an active securities market. Even financial economists now customarily use the term "bubble" to refer to the late 1990s stock market or elements of it. And while asset bubbles present mysteries of their own, they are of course quite incompatible with the supposed fact that prices in securities markets result from a rational incorporation of all available information bearing on value.” (Allen, 2003, p.551) References: Allen, W. T. (2003). Securities Markets as Social Products: the Pretty Efficient Capital Market Hypothesis. Journal of Corporation Law, 28(4), 551+. J. Bradford DeLong, Andrei Shleifer, Lawrence H. Summers, and Robert J. Waldmann (1990), "Noise Trader Risk in Financial Markets," Journal of Political Economy 98: 4 (August 1990), pp. 703-738. Glen, P. J. (2005). The Efficient Capital Market Hypothesis, Chaos Theory, and the Insider Filing Requirements of the Securities Exchange Act of 1934: the Predictive Power of Form 4 Filings. Fordham Journal of Corporate & Financial Law, 11(1), 85+. Shleifer, A. (2000). Inefficient Markets: An Introduction to Behavioral Finance. Oxford, England: Oxford University Press. Stanley, D. J., & Samuelson, B. A. (2009). The Efficient Market Hypothesis, Price Multiples and the Austrian Stock Market. Journal of Global Business Issues, 3(1), 183+. Stout, L. A. (2003). The Mechanisms of Market Inefficiency: an Introduction to the New Finance. Journal of Corporation Law, 28(4), 635+. De BONDT, Werner F. M. and Richard H. THALER, 1987, Further Evidence on Investor Overreaction and Stock Market Seasonality. Warren E. Buffett (1984), The Super Investors of Graham and Dodsville, transcript of a talk given at Columbia University in 1984, Columbia Business School Magazine, available at http://www.grahamanddoddsville.net/wordpress/Files/Gurus/Warren%20Buffett/Superinvestors%20of%20Graham%20and%20Doddsville%20-%20Hermes.pdf [accessed 10 October 2011]. Read More