Efficient-market hypothesis

From Wikipedia, the free encyclopedia
  (Redirected from Efficient market hypothesis)
Jump to navigation Jump to search

The efficient-market hypothesis (EMH) is a hypothesis in financial economics that states that asset prices reflect all available information. A direct implication is that it is impossible to "beat the market" consistently on a risk-adjusted basis since market prices should only react to new information. Since risk adjustment is central to the EMH, and yet the EMH does not specify a model of risk, the EMH is untestable.[1] As a result, research in financial economics since at least the 1990s has focused on market anomalies, that is, deviations from specific models of risk.[2]

The efficient-market hypothesis was developed by Eugene Fama in the 1960s, following up on work by Bachelier, Muth, Samuelson, and Mandelbrot. Fama original proposed "weak" and "strong" forms of the hypothesis, but he later said he "came to regret" using these terms.[3] Fama's 2013 Nobel prize address on the topic almost completely ignores these concepts.[4]

Despite its lack of testability, the EMH still provides the basic logic for modern risk-based theories of asset prices. Indeed, modern frameworks such as consumption-based asset pricing and intermediary asset pricing can be thought of as the combination of a model of risk with the hypothesis that markets are efficient.[4]

Historical background[edit]

Benoit Mandelbrot claimed the efficient markets theory was first proposed by the French mathematician Louis Bachelier in 1900 in his PhD thesis "The Theory of Speculation" describing how prices of commodities and stocks varied in markets.[5] It has been speculated that Bachelier drew ideas from the random walk model of Jules Regnault, but Bachelier did not cite him,[6] and Bachelier's thesis is now considered pioneering in the field of financial mathematics.[7][6] It is commonly thought that Bachelier's work gained little attention and was forgotten for decades until it was rediscovered in the 1950s by Leonard Savage, and then become more popular after Bachelier's thesis was translated into English in 1964. But the work was never forgotten in the mathematical community, as Bachelier published a book in 1912 detailing his ideas,[6] which was cited by mathematicians including Joseph L. Doob, William Feller[6] and Andrey Kolmogorov.[8] The book continued to be cited, but then starting in the 1960s the original thesis by Bachelier began to be cited more than his book when economists started citing Bachelier's work.[6]

The efficient markets theory was not popular until the 1960s when the advent of computers made it possible to compare calculations and prices of hundreds of stocks more quickly and effortlessly. In 1945, F.A. Hayek argued that markets were the most effective way of aggregating the pieces of information dispersed among individuals within a society. Given the ability to profit from private information, self-interested traders are motivated to acquire and act on their private information. In doing so, traders contribute to more and more efficient market prices. In the competitive limit, market prices reflect all available information and prices can only move in response to news. Thus there is a very close link between EMH and the random walk hypothesis.[9]

Empirically, a number of studies indicated that US stock prices and related financial series followed a random walk model in the short-term.[10] Whilst there is some predictability over the long-term, the extent to which this is due to rational time-varying risk premia as opposed to behavioral reasons is a subject of debate. Research by Alfred Cowles in the 1930s and 1940s suggested that professional investors were in general unable to outperform the market.


The efficient-market hypothesis emerged as a prominent theory 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 Cootner.[11] In 1965, Eugene Fama published his dissertation arguing for the random walk hypothesis.[12] Also, Samuelson published a proof showing that if the market is efficient, prices will exhibit random-walk behavior.[13] This is often cited in support of the efficient-market theory, by the method of affirming the consequent,[14][15] however in that same paper, Samuelson warns against such backward reasoning, saying "From a nonempirical base of axioms you never get empirical results."[16] 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 financial market efficiency: weak, semi-strong and strong (see below).[17]

It has been argued that the stock market is "micro efficient" but not "macro efficient". The main proponent of this view was Samuelson, who asserted that the EMH is much better suited for individual stocks than it is for the aggregate stock market. Research based on regression and scatter diagrams has strongly supported Samuelson's dictum.[18] This result is also the theoretical justification for the forecasting of broad economic trends, which is provided by a variety of groups including non-profit groups as well as by for-profit private institutions.[citation needed]

Further to this evidence that the UK stock market is weak-form efficient, other studies of capital markets have pointed toward their being semi-strong-form efficient. A study by Khan of the grain futures market indicated semi-strong form efficiency following the release of large trader position information (Khan, 1986). 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. However, the market's ability to efficiently respond to a short term, widely publicized event such as a takeover announcement does not necessarily prove market efficiency related to other more long term, amorphous factors. David Dreman has criticized the evidence provided by this instant "efficient" response, pointing out that an immediate response is not necessarily efficient, and that the long-term performance of the stock in response to certain movements are better indications.

Theoretical background[edit]

Beyond the normal utility maximizing agents, the efficient-market hypothesis requires that agents have rational expectations; that on average the population is correct (even if no one person is) and whenever new relevant information appears, the agents update their expectations appropriately. Note that it is not required that the agents be rational. 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 has different implications for how markets work.

Weak-form efficiency[edit]

In weak-form efficiency, future prices cannot be predicted by analyzing prices from the past. Excess returns cannot be earned in the long run by using investment strategies based on historical share prices or other historical data. Technical analysis techniques will not be able to consistently produce excess returns, though some forms of fundamental analysis may still provide excess returns. Share prices exhibit no serial dependencies, meaning that there are no "patterns" to asset prices. This implies that future price movements are determined entirely by information not contained in the price series. Hence, prices must follow a random walk. This 'soft' EMH does not require that prices remain at or near equilibrium, but only that market participants not be able to systematically profit from market 'inefficiencies'.[19] and that, moreover, there is a positive correlation between degree of trending and length of time period studied (but note that over long time periods, the trending is sinusoidal in appearance).[20] Various explanations for such large and apparently non-random price movements have been promulgated.

There is a vast literature in academic finance dealing with the momentum effect identified by Jegadeesh and Titman.[21][22] Stocks that have performed relatively well (poorly) over the past 3 to 12 months continue to do well (poorly) over the next 3 to 12 months. The momentum strategy is long recent winners and shorts recent losers, and produces positive risk-adjusted average returns. Being simply based on past stock returns, the momentum effect produces strong evidence against weak-form market efficiency, and has been observed in the stock returns of most countries, in industry returns, and in national equity market indices. Moreover, Fama has accepted that momentum is the premier anomaly.[23][24]

The problem of algorithmically constructing prices which reflect all available information has been studied extensively in the field of computer science.[25][26]

Semi-strong-form efficiency[edit]

In semi-strong-form efficiency, it is implied that share prices adjust to publicly available new information very rapidly and in an unbiased fashion, such that no excess returns can be earned by trading on that information. Semi-strong-form efficiency implies that neither fundamental analysis nor technical analysis techniques will be able to reliably produce excess returns. To test for semi-strong-form efficiency, the adjustments to previously unknown news must be of a reasonable size and must be instantaneous. To test for this, consistent upward or downward adjustments after the initial change must be looked for. If there are any such adjustments it would suggest that investors had interpreted the information in a biased fashion and hence in an inefficient manner.[citation needed]

Strong-form efficiency[edit]

In strong-form efficiency, share prices reflect all information, public and private, and no one can earn excess returns. If there are legal barriers to private information becoming public, as with insider trading laws, strong-form efficiency is impossible, except in the case where the laws are universally ignored. To test for strong-form efficiency, a market needs to exist where investors cannot consistently earn excess returns over a long period of time. Even if some money managers are consistently observed to beat the market, no refutation even of strong-form efficiency follows: with hundreds of thousands of fund managers worldwide, even a normal distribution of returns (as efficiency predicts) should be expected to produce a few dozen "star" performers.


Price-Earnings ratios as a predictor of twenty-year returns based upon the plot by Robert Shiller (Figure 10.1,[27] source). The horizontal axis shows the real price-earnings ratio of the S&P Composite Stock Price Index as computed in Irrational Exuberance (inflation adjusted price divided by the prior ten-year mean of inflation-adjusted earnings). The vertical axis shows the geometric average real annual return on investing in the S&P Composite Stock Price Index, reinvesting dividends, and selling twenty years later. Data from different twenty-year periods is color-coded as shown in the key. See also ten-year returns. Shiller states that this plot "confirms that long-term investors—investors who commit their money to an investment for ten full years—did do well when prices were low relative to earnings at the beginning of the ten years. Long-term investors would be well advised, individually, to lower their exposure to the stock market when it is high, as it has been recently, and get into the market when it is low."[27] Burton Malkiel, a well-known proponent of the general validity of EMH, stated that this correlation may be consistent with an efficient market due to differences in interest rates.[28]

Investors, including the likes of Warren Buffett,[29] and researchers have disputed the efficient-market hypothesis both empirically and theoretically. Behavioral economists attribute the imperfections in financial markets to a combination of cognitive biases such as overconfidence, overreaction, representative bias, information bias, and various other predictable human errors in reasoning and information processing. These have been researched by psychologists such as Daniel Kahneman, Amos Tversky and Paul Slovic and economist Richard Thaler. These errors in reasoning lead most investors to avoid value stocks and buy growth stocks at expensive prices, which allow those who reason correctly to profit from bargains in neglected value stocks and the overreacted selling of growth stocks.[citation needed]

Empirical evidence has been mixed, but has generally not supported strong forms of the efficient-market hypothesis[30][31][32] According to Dreman and Berry, in a 1995 paper, low P/E stocks have greater returns.[33] In an earlier paper Dreman also refuted the assertion by Ray Ball that these higher returns could be attributed to higher beta,[clarification needed][34] whose research had been accepted by efficient market theorists as explaining the anomaly[35] in neat accordance with modern portfolio theory.

Behavioral psychology[edit]

Behavioral psychology approaches to stock market trading are among some of the more promising[citation needed] alternatives to EMH (and some[which?] investment strategies seek to exploit exactly such inefficiencies). But Nobel Laureate co-founder of the programme Daniel Kahneman —announced his skepticism of investors beating the market: "They're just not going to do it. It's just not going to happen." Indeed, defenders of EMH maintain that Behavioral Finance strengthens the case for EMH in that it highlights biases in individuals and committees and not competitive markets. For example, one prominent finding in Behaviorial Finance is that individuals employ hyperbolic discounting. It is demonstrably true that bonds, mortgages, annuities and other similar financial instruments subject to competitive market forces do not. Any manifestation of hyperbolic discounting in the pricing of these obligations would invite arbitrage thereby quickly eliminating any vestige of individual biases. Similarly, diversification, derivative securities and other hedging strategies assuage if not eliminate potential mispricings from the severe risk-intolerance (loss aversion) of individuals underscored by behavioral finance. On the other hand, economists, behaviorial psychologists and mutual fund managers are drawn from the human population and are therefore subject to the biases that behavioralists showcase. By contrast, the price signals in markets are far less subject to individual biases highlighted by the Behavioral Finance programme. Richard Thaler has started a fund based on his research on cognitive biases. In a 2008 report he identified complexity and herd behavior as central to the global financial crisis of 2008.[36]

Further empirical work has 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 made by those willing to incur the cost of acquiring the valuable information in order to trade on it. Additionally the concept of liquidity is a critical component to capturing "inefficiencies" in tests for abnormal returns. 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 —one cannot know if the market is efficient if one does not know if a 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 has no way of knowing which is the case.[citation needed]

The performance of stock markets is correlated with the amount of sunshine in the city where the main exchange is located.[37]

A key work on random walk was done in the late 1980s by Profs. Andrew Lo and Craig MacKinlay; they effectively argue that a random walk does not exist, nor ever has.[38] Their paper took almost two years to be accepted by academia and in 1999 they published "A Non-random Walk Down Wall St." which collects their research papers on the topic up to that time.

EMH anomalies and rejection of the Capital Asset Pricing Model (CAPM)[edit]

While event studies of stock splits are consistent with the EMH (Fama, Fisher, Jensen, and Roll, 1969), other empirical analyses have found problems with the efficient-market hypothesis. Early examples include the observation that small neglected stocks and stocks with high book-to-market (low price-to-book) ratios (value stocks) tended to achieve abnormally high returns relative to what could be explained by the CAPM.[clarification needed][30][31] Further tests of portfolio efficiency by Gibbons, Ross and Shanken (1989) (GJR) led to rejections of the CAPM, although tests of efficiency inevitably run into the joint hypothesis problem (see Roll's critique).

Following GJR's results and mounting empirical evidence of EMH anomalies, academics began to move away from the CAPM towards risk factor models such as the Fama-French 3 factor model. These risk factor models are not properly founded on economic theory (whereas CAPM is founded on Modern Portfolio Theory), but rather, constructed with long-short portfolios in response to the observed empirical EMH anomalies. For instance, the "small-minus-big" (SMB) factor in the FF3 factor model is simply a portfolio that holds long positions on small stocks and short positions on large stocks to mimic the risks small stocks face. These risk factors are said to represent some aspect or dimension of undiversifiable systematic risk which should be compensated with higher expected returns. Additional popular risk factors include the "HML" value factor (Fama and French, 1993); "MOM" momentum factor (Carhart, 1997); "ILLIQ" liquidity factors (Amihud et al. 2002). See also Robert Haugen.

View of some economists[edit]

Economists Matthew Bishop and Michael Green claim that full acceptance of the hypothesis goes against the thinking of Adam Smith and John Maynard Keynes, who both believed irrational behavior had a real impact on the markets.[39]

Economist John Quiggin has claimed that "Bitcoin is perhaps the finest example of a pure bubble", and that it provides a conclusive refutation of EMH.[40] While other assets used as currency (such as gold, tobacco) have value independent of people's willingness to accept them as payment, Quiggin argues that "in the case of Bitcoin there is no source of value whatsoever".

Tshilidzi Marwala surmised that artificial intelligence influences the applicability of the theory of the efficient market hypothesis in that the more artificial intelligence infused computer traders there are in the markets as traders the more efficient the markets become.[41][42][43]

Warren Buffett has also argued against EMH, most notably in his 1984 presentation The Superinvestors of Graham-and-Doddsville, saying the preponderance of value investors among the world's best money managers rebuts the claim of EMH proponents that luck is the reason some investors appear more successful than others.[44] However, as Malkiel[45] has shown, over the 30 years prior to 1996 more than two-thirds of professional portfolio managers have been outperformed by the S&P 500 Index and, more to the point, there is little correlation between those who outperform in one year and those who outperform in the next.

In his book The Reformation in Economics economist and financial analyst Philip Pilkington has argued that the EMH is actually a tautology masquerading as a theory [46]. He argues that, taken at face value, the theory makes the banal claim that the average investor will not beat the market average -- which is a tautology. When pressed, proponents will then say that any actual investor will converge with the average investor given enough time and so no investor will beat the market average. But Pilkington points out that when proponents of the theory are presented with evidence that a small minority of investor do, in fact, beat the market over the long-run, these proponents then say that these investors were simply 'lucky'. Pilkington argues that introducing the idea that anyone who diverges from the theory is simply 'lucky' insulates the theory from falsification and so, drawing on the philosopher of science and critic of neolcassical economics Hans Albert, Pilkington argues that the theory falls back into being a tautology or a pseudoscientific construct [47].

Late 2000s financial crisis[edit]

The financial crisis of 2007–08 led to renewed scrutiny and criticism of the hypothesis.[48] Market strategist Jeremy Grantham stated flatly that the EMH was responsible for the current financial crisis, claiming that belief in the hypothesis caused financial leaders to have a "chronic underestimation of the dangers of asset bubbles breaking".[49] Noted financial journalist Roger Lowenstein blasted the theory, declaring "The upside of the current Great Recession is that it could drive a stake through the heart of the academic nostrum known as the efficient-market hypothesis."[50] Former Federal Reserve chairman Paul Volcker chimed in, saying it's "clear that among the causes of the recent financial crisis was an unjustified faith in rational expectations [and] market efficiencies."[51] One financial analyst noted "by 2007–2009, you had to be a fanatic to believe in the literal truth of the EMH."[52]

At the International Organization of Securities Commissions annual conference, held in June 2009, the hypothesis took center stage. Martin Wolf, the chief economics commentator for the Financial Times, dismissed the hypothesis as being a useless way to examine how markets function in reality. Paul McCulley, managing director of PIMCO, was less extreme in his criticism, saying that the hypothesis had not failed, but was "seriously flawed" in its neglect of human nature.[53][54]

The financial crisis led Richard Posner, a prominent judge, University of Chicago law professor, and innovator in the field of Law and Economics, to back away from the hypothesis. Posner accused some of his Chicago School colleagues of being "asleep at the switch", saying that "the movement to deregulate the financial industry went too far by exaggerating the resilience—the self healing powers—of laissez-faire capitalism."[55] Others, such as Fama, said that the hypothesis held up well during the crisis and that the markets were a casualty of the recession, not the cause of it. Despite this, Fama has conceded that "poorly informed investors could theoretically lead the market astray" and that stock prices could become "somewhat irrational" as a result.[56]

Efficient markets applied in securities class action litigation[edit]

The theory of efficient markets has been practically applied in the field of Securities Class Action Litigation. Efficient market theory, in conjunction with "fraud-on-the-market theory," has been used in Securities Class Action Litigation to both justify and as mechanism for the calculation of damages.[57] In the Supreme Court Case, Halliburton v. Erica P. John Fund, U.S. Supreme Court, No. 13-317, the use of efficient market theory in supporting securities class action litigation was affirmed. Supreme Court Justice Roberts wrote that "the court’s ruling was consistent with the ruling in "Basic" because it allows "direct evidence when such evidence is available” instead of relying exclusively on the efficient markets theory."[58]

See also[edit]


  1. ^ Fama, Eugene (1970). "Efficient Capital Markets: A Review of Theory and Empirical Work". Journal of Finance.
  2. ^ Schwert, G. William (2003). "Anomalies and market efficiency". Handbook of the Economics of Finance.
  3. ^ "Fama on Finance: Interview on EconTalk with Russ Roberts".
  4. ^ a b Fama, Eugene (2013). "Two Pillars of Asset Pricing" (PDF). Prize Lecture for the Nobel Foundation.
  5. ^ "Benoit mandelbrot on efficient markets (interview - 30 September 2009)". www.ft.com. Financial times. Retrieved 21 November 2017.
  6. ^ a b c d e Jovanovic, Franck (2012). "Bachelier: Not the forgotten forerunner he has been depicted as. An analysis of the dissemination of Louis Bachelier's work in economics". The European Journal of the History of Economic Thought. 19 (3): 431–451. doi:10.1080/09672567.2010.540343. ISSN 0967-2567.
  7. ^ Courtault, Jean-Michel; Kabanov, Yuri; Bru, Bernard; Crepel, Pierre; Lebon, Isabelle; Le Marchand, Arnaud (2000). "Louis Bachelier on the Centenary of Theorie de la Speculation". Mathematical Finance. 10 (3): 339–353. doi:10.1111/1467-9965.00098. ISSN 0960-1627.
  8. ^ Jarrow, Robert; Protter, Philip (2004). "A short history of stochastic integration and mathematical finance: the early years, 1880–1970". A Festschrift for Herman Rubin. Institute of Mathematical Statistics Lecture Notes - Monograph Series. pp. 75–80. doi:10.1214/lnms/1196285381. ISBN 978-0-940600-61-4. ISSN 0749-2170.
  9. ^ Kirman, Alan. "Economic theory and the crisis." Voxeu. 14 November 2009.
  10. ^ See Working (1934), Cowles and Jones (1937), and Kendall (1953), and later Brealey, Dryden and Cunningham.
  11. ^ Cootner (ed.), Paul (1964). The Random Character of StockMarket Prices. MIT Press.CS1 maint: extra text: authors list (link)
  12. ^ Fama, Eugene (1965). "The Behavior of Stock Market Prices". Journal of Business. 38: 34–105. doi:10.1086/294743.
  13. ^ Samuelson, Paul (1965). "Proof That Properly Anticipated Prices Fluctuate Randomly". Industrial Management Review. 6: 41–49.
  14. ^ Schwager, Jack D. (19 October 2012). Market Sense and Nonsense: How the Markets Really Work (and How They Don't). John Wiley & Sons. ISBN 9781118523162 – via Google Books.
  15. ^ Collin Read (15 December 2012). The Efficient Market Hypothesists: Bachelier, Samuelson, Fama, Ross, Tobin, and Shiller. ISBN 9781137292216.
  16. ^ "The efficient market hypothesis: problems with interpretations of empirical tests".
  17. ^ Fama, Eugene (1970). "Efficient Capital Markets: A Review of Theory and Empirical Work". Journal of Finance. 25 (2): 383–417. doi:10.2307/2325486. JSTOR 2325486.
  18. ^ Jung, Jeeman; Shiller, Robert (2005). "Samuelson's Dictum And The Stock Market". Economic Inquiry. 43 (2): 221–228. CiteSeerX doi:10.1093/ei/cbi015.
  19. ^ Saad, Emad W., Student Member, IEEE; Prokhorov, Danil V. Member, IEEE; and Wunsch, II, Donald C. Senior Member, IEEE (November 1998). "Comparative Study of Stock Trend Prediction Using Time Delay, Recurrent and Probabilistic Neural Networks". IEEE Transactions on Neural Networks. 9 (6): 1456–1470. CiteSeerX doi:10.1109/72.728395. PMID 18255823.CS1 maint: multiple names: authors list (link)
  20. ^ Granger, Clive W. J.; Morgenstern, Oskar (5 May 2007). "Spectral Analysis Of New York Stock Market Prices". Kyklos. 16 (1): 1–27. doi:10.1111/j.1467-6435.1963.tb00270.x.
  21. ^ Jegadeesh, N; Titman, S (1993). "Returns to Buying winners and selling losers: Implications for stock market efficiency". Journal of Finance. 48 (1): 65–91. doi:10.1111/j.1540-6261.1993.tb04702.x.
  22. ^ Jegadeesh, N; Titman, S (2001). "Profitability of Momentum Strategies: An evaluation of alternative explanations". Journal of Finance. 56 (2): 699–720. doi:10.1111/0022-1082.00342.
  23. ^ Fama, E; French, K (1996). "Multifactor explanation of asset pricing anomalies". Journal of Finance. 51 (1): 55–84. doi:10.1111/j.1540-6261.1996.tb05202.x.
  24. ^ Fama, E; French, K (2008). "Dissecting Anomalies". Journal of Finance. 63 (4): 1653–78. doi:10.1111/j.1540-6261.2008.01371.x.
  25. ^ Kleinberg, Jon; Tardos, Eva (2005). Algorithm Design. Addison Wesley. ISBN 978-0-321-29535-4.
  26. ^ Vazirani, Vijay V.; Nisan, Noam; Roughgarden, Tim; Tardos, Éva (2007). Algorithmic Game Theory (PDF). Cambridge, UK: Cambridge University Press. ISBN 0-521-87282-0.
  27. ^ a b Shiller, Robert (2005). Irrational Exuberance (2d ed.). Princeton University Press. ISBN 978-0-691-12335-6.
  28. ^ Burton G. Malkiel (2006). A Random Walk Down Wall Street. ISBN 0-393-32535-0. p.254.
  29. ^ "Here's What Warren Buffet Thinks About The Efficient Market Hypothesis". Business Insider.
  30. ^ a b Empirical papers questioning EMH:
    • Francis Nicholson. Price-Earnings Ratios in Relation to Investment Results. Financial Analysts Journal. Jan/Feb 1968:105–109.
    • Basu, Sanjoy (1977). "Investment Performance of Common Stocks in Relation to Their Price-Earnings Ratios: A test of the Efficient Markets Hypothesis". Journal of Finance. 32 (3): 663–682. doi:10.1111/j.1540-6261.1977.tb01979.x.
    • Rosenberg B, Reid K, Lanstein R. (1985). Persuasive Evidence of Market Inefficiency. Journal of Portfolio Management 13:9–17.
  31. ^ a b Fama, E; French, K (1992). "The Cross-Section of Expected Stock Returns". Journal of Finance. 47 (2): 427–465. doi:10.1111/j.1540-6261.1992.tb04398.x.
  32. ^ Chan, Kam C.; Gup, Benton E.; Pan, Ming-Shiun (4 March 2003). "International Stock Market Efficiency and Integration: A Study of Eighteen Nations". Journal of Business Finance & Accounting. 24 (6): 803–813. doi:10.1111/1468-5957.00134.
  33. ^ Dreman David N.; Berry Michael A. (1995). "Overreaction, Underreaction, and the Low-P/E Effect". Financial Analysts Journal. 51 (4): 21–30. doi:10.2469/faj.v51.n4.1917.
  34. ^ Ball R. (1978). Anomalies in Relationships between Securities' Yields and Yield-Surrogates. Journal of Financial Economics 6:103–126
  35. ^ Dreman D. (1998). Contrarian Investment Strategy: The Next Generation. Simon and Schuster.
  36. ^ Thaler RH. (2008). 3Q2008. Fuller & Thaler Asset Management.
  37. ^ Hirshleifer, David A.; Shumway, Tyler (June 2003). "Good Day Sunshine: Stock Returns and the Weather". Journal of Finance. 58 (3): 1009–1032. doi:10.1111/1540-6261.00556. SSRN 411135.
  38. ^ "A Non-Random Walk Down Wall Street". Princeton University Press.
  39. ^ Hurt III, Harry (19 March 2010). "The Case for Financial Reinvention". The New York Times. Retrieved 29 March 2010.
  40. ^ Quiggin, John (16 April 2013). "The Bitcoin Bubble and a Bad Hypothesis". The National Interest.
  41. ^ "Herausforderung künstliche Intelligenz". 9 November 2015.
  42. ^ GmbH, finanzen.net. "Datenschutz: Wir brauchen Schutz vor künstlicher Intelligenz - 12.10.15 - BÖRSE ONLINE".
  43. ^ Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: Springer. ISBN 978-3-319-66104-9.
  44. ^ Hoffman, Greg (14 July 2010). "Paul the octopus proves Buffett was right". Sydney Morning Herald. Retrieved 4 August 2010.
  45. ^ Malkiel, A Random Walk Down Wall Street, 1996
  46. ^ Pilkington, P (2017). The Reformation in Economics: A Deconstruction and Reconstruction of Economic Theory. Palgrave Macmillan. Pp261-265. [1]
  47. ^ Pilkington, P (2014). Hans Albert Expands Robinson's Critique of the Law of Demand. Fixing the Economists. [2]
  48. ^ "Sun finally sets on notion that markets are rational". The Globe and Mail. 7 July 2009. Retrieved 7 July 2009.
  49. ^ Nocera, Joe (5 June 2009). "Poking Holes in a Theory on Markets". The New York Times. Retrieved 8 June 2009.
  50. ^ Lowenstein, Roger (7 June 2009). "Book Review: 'The Myth of the Rational Market' by Justin Fox". The Washington Post. Retrieved 5 August 2011.
  51. ^ Paul Volcker (27 October 2011). "Financial Reform: Unfinished Business". New York Review of Books. Retrieved 22 November 2011.
  52. ^ Siegel, Laurence B. (2010). "Black Swan or Black Turkey? The State of Economic Knowledge and the Crash of 2007–2009". Financial Analysts Journal. 66 (4): 6–10. doi:10.2469/faj.v66.n4.4. Quote on p. 7.
  53. ^ "Has 'guiding model' for global markets gone haywire?". Jerusalem Post. 11 June 2009. Archived from the original on 8 July 2012. Retrieved 17 June 2009. Cite uses deprecated parameter |dead-url= (help)
  54. ^ Stevenson, Tom (17 June 2009). "Investors are finally seeing the nonsense in the efficient market theory". The Telegraph.
  55. ^ "After the Blowup". The New Yorker. 11 January 2010. Retrieved 12 January 2010.
  56. ^ Jon E. Hilsenrath, Stock Characters: As Two Economists Debate Markets, The Tide Shifts Archived 6 April 2012 at the Wayback Machine. Wall Street Journal 2004
  57. ^ Sommer, Jeff (28 June 2014). "Are Markets Efficient? Even the Supreme Court Is Weighing In". The New York Times.
  58. ^ Liptak, Adam (23 June 2014). "New Hurdle in Investors' Class Actions". The New York Times.


  • Bogle, John (1994). Bogle on Mutual Funds: New Perspectives for the Intelligent Investor, Dell, ISBN 0-440-50682-4
  • Cowles, Alfred; H. Jones (1937). "Some A Posteriori Probabilities in Stock Market Action". Econometrica. 5 (3): 280–294. doi:10.2307/1905515. JSTOR 1905515.
  • Kendall, Maurice. "The Analysis of Economic Time Series". Journal of the Royal Statistical Society. 96: 11–25.
  • Khan, Arshad M. (1986). "Conformity with Large Speculators: A Test of Efficiency in the Grain Futures Market". Atlantic Economic Journal. 14 (3): 51–55. doi:10.1007/BF02304624.
  • Lo, Andrew and MacKinlay, Craig (2001). A Non-random Walk Down Wall St. Princeton Paperbacks
  • Malkiel, Burton G. (1987). "efficient market hypothesis," The New Palgrave: A Dictionary of Economics, v. 2, pp. 120–23.
  • Malkiel, Burton G. (1996). A Random Walk Down Wall Street, W. W. Norton, ISBN 0-393-03888-2
  • Pilkington, P (2017). The Reformation in Economics: A Deconstruction and Reconstruction of Economic Theory. Palgrave Macmillan.
  • Samuelson, Paul (1972). "Proof That Properly Anticipated Prices Fluctuate Randomly." Industrial Management Review, Vol. 6, No. 2, pp. 41–49. Reproduced as Chapter 198 in Samuelson, Collected Scientific Papers, Volume III, Cambridge, M.I.T. Press.
  • Sharpe, William F. "The Arithmetic of Active Management"
  • Working, Holbrook (1960). "Note on the Correlation of First Differences of Averages in a Random Chain". Econometrica. 28 (4): 916–918. doi:10.2307/1907574. JSTOR 1907574.

External links[edit]