Market Efficiency Hypothesis Overview

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Page count 7
Word count 2055
Read time 9 min
Subject Economics
Type Essay
Language 🇺🇸 US


The efficient market hypothesis (EMH) popularly known as the Random walk theory asserts that stock prices fully reflect information about their past performance and probable future events. Reliance on the power of markets proved fleeting when the tension of the 2008 credit crunch and market bubbles all come to represent. The consensus towards efficiency and predictability relationship has challenged the reputation of the EMH since the collapse of real estate with stocks markets losing 50% of their value. The failing of the EMH system attacks the theory of efficient-market hypothesis which brings us to the conclusion that markets are more efficient and less predictable than what econometric would have us believe.

Credit Crunch and Market bubbles

The market Efficiency hypothesis has over the years received numerous criticisms due to its impractical theories and policies that prove insignificant to today’s dynamic economy. EMH has major limitations evidenced to be the source of the 2007-2008 global financial turmoil. The purported irregularities or anomalies of stocks markets in relation to their behavioral underpinnings are reported to represent strong evidence against the EMH in relation to their predictability and efficiency. The 2007-2008 credit bubbles for example proved that relationships between predictability and efficiency no longer prove significant since they are contradictory in nature. These irregularities transfer and spread risks to global markets causing credit and price growth. The most controversial issue in financial markets is the possibilities of whether the financial markets are efficient in allocating or using economic resources and information (Mizen 2; Brunnermeie and Abreu 24; Bernanke and Lown 205).

Efficient market hypotheses have also been unable to perform market tests that provide the basis for a scheme to beat the market and earn excess returns. These inefficiencies have always been attributed to the inability of stocks to trade hence higher transactions costs and the existence of profit-maximizing investors who are unable to recognize the potential for excess returns and improvise schemes that will replicate excess returns and provide resources to trade on stock on unstable markets (Bollerslev and Hodrick 75). Investors always try to identify securities that are undervalued and are expected to increase in the future. They often think that they can select securities that will outperform the markets by using this market information which apparently never works (Brunnermeie et al 13). According to Clarke and his colleague’s theory of efficient markets, attempts to use forecasting and valuation techniques as aiding tools in investment decision does not prove effective since the advantage gained does not exceed the transaction and research costs incurred, therefore no one can predictably outperform the markets (22). This theory that claims that investors cannot outperform the markets seems incorrect since many successful market analysts such as Peter Lynch, George Soros among others have used the same techniques and outperformed the markets.

The most crucial hypothesis of EMH is the inherent slogan of trust market prices stated by Clarke, Jannik, and Mandelker as “At any point in time, prices of securities inefficient markets reflect all known information available to investors” (22). This literally means that investors entirely rely on this market information for investment decisions and in this case, all stocks are fairly priced and investors get what they paid for which is not usually the case. Under normal circumstances, investors do not usually get what they paid for as they do not perform similarly since some are likely to experience profits and losses at some point. The capital market theory according to Clarke, Jandik and Mandelker means that “the price of a security reflects the present value of its future expected cash flow” (22). In their explanation, they include factors such as volatility, liquidity, and risk of bankruptcy as components of price determination which further explains that the rationality of the price is based on changes in prices which are expected to be random and unpredictable-hence the name, the random walk (Winton 5; Shin and Tobias 2).

The introduction of new information to the markets can be efficient to some investors and inefficient to others in relation to differential tax ratios and transactions costs, which serves as an advantage to some and relative to others. Also, Bacon & Gerdorff’s (8) hypothesis that claims information announcements either increase or decrease stock prices is inconsistent with Clarke’s and his colleague’s (22) argument of market hypothesis theory that provides markets benefit from predicting prices (Cutler et al 5).

Malkiel also argues that the profitability of market information depends on investors’ ability to identify over and undervalued stocks which evidently requires a significant amount of time and money to determine miss-priced stocks (5). In this regard, the global liquidity that led to the rise of asset prices subsequently leading to excessive leverage by the otherwise efficient market hypothesis should have been detected on time. The EMH was not flexible to respond to the crisis event increasing volatility which severely impaired market liquidity. The rise in demand for liquid assets directly distorted the underlying EMH fundamentals that provide that market prices accurately reflect all available information. Secondly, based on the uncontrolled market liquidity, it’s quite evident that EMH only focuses only on the mispricing of financial assets and disregards the impacts it has on the mispriced assets. Incentive systems based on quick up-front payouts encouraged banks to generate returns of low risks acted as a short-term mechanism to lower market pressures. This quick offload risk as a result of negligence from investors led to poor underwriting of mortgage brokers forcing banks to undergo huge losses in market values once markets started drying out (Wehinger 4).

Below is a detailed analysis of the change in the market value of the largest banks in (USD billion)

Banks losses in Market Value

2008 b) 2007 2006 2005
United States -423.7 -338.8 190.5 -26.7
United Kingdom -307.1 -101.5 127.0 -20.0
Belgium -204.3 5.5 54.0 20.0
Italy -175.9 73.3 61.6 46.9
France -157.0 -31.4 109.0 13.2
Switzerland -107.5 -44.5 55.7 22.0
Canada -105.5 12.2 31.1 37.2
Japan -104.4 -112.3 -49.2 204.4
Germany -83.8 -3.7 34.1 14.8
Sweden -58.0 -4.3 26.7 0.7
Netherlands -0.7 0.5 0.5 0.1
G10 total -1.727.9 -545.1 641.0 315.0
EMU total -938.0 79.2 421.1 116.0
Global c) -3,068.0 -106.4 1,220.7 518.0

Source: Thomson Financial, OECD

Global Bank losses in Market Value

C. Market Anomalies
C. Market Anomalies

Damodaran defines market anomalies as those market practices that deviate from the normal common rules (45). The persistence of these theory patterns suggests that there exist problems in some of the anomalies used in measuring risks and returns which ignores financial markets behaviors. For example, the market bubbles that occurred during 1999 would have not occurred if stocks reflected new information. In my perception, predictable patterns are predicted to be sufficiently robust, which may mean investment opportunities for investors, and after they have been published, they certainly can not make any profits (Fama & French 150). On the other hand, a non-random walk theory provides that stock markets only hold on to information that affects stock prices at the present and does not reflect on how they behave in the future. Ross and Randolph’s classification on weak theory stipulate that it’s impossible for an investor to achieve positive abnormal returns by using past information on the stock prices (312) while the semi-strong form reflects on all the available public information and investors entirely rely on this for market analysis. Evidently, these theories do not prove sufficient since none of the market analysts have tested the hypothesis by examining the adjustment of the market to publicly available information such as merger announcements.

Another linkage of short-term momentums of psychological behavioral feedback mechanisms is the tendency of investors to under-react to new information. This, therefore, means that the full impact of new information in the markets can only be affected over a period of time, and stock prices for this case will exhibit a positive serial correlation. Behavioral finance of momentum, as opposed to EMH of randomness, seems reasonable in interpreting markets results as an indication that markets are inefficient (Fama and French 46). The behavioral hypothesis about the bandwagon effect and under-reaction of new information does not provide enough evidence to support the hypothesis that stipulates such effects occur systematically. Fama and French findings also argue that under-reaction to information is just as common as an overreaction, and post-event continual is just as common as post-event reversals of abnormal returns. For example, during the 1990s, stock prices seemed to produce positive returns and produced highly negative returns during the year 2000 (Fama and French 52).

Temporary anomalies are calendar tests that measure returns across certain periods such as weekends and Januarys. The weekend effect in market analysis refers to the differences between Mondays to Fridays which are believed to negatively affect Monday returns. However, Bollerslev and Hodrick (78) argue that since the investors already expect bad news over the weekend, the prices will not be affected yet another inconsistency in the rational market hypothesis. The January effect on the other hand is assumed to yield higher returns in the first two weeks of the month may be only favourable to smaller firms and ineffective to bigger ones (Bollerslev and Hodrick 78).

Bailouts, Regulations, and Derivatives

Governments and policymakers have been struggling to implement idiosyncratic measures that are significant to the 2007-2008 financial turmoil. Such strategies included actions such as capital injections and financial support from the government and central banks to enhance liquidity and prevent bank failures. This is evident in the government bailouts to support AIG (American International Groups) before its collapse. But it was not the case for the Lehman Brothers Bank. However, the question that everyone asks is why AIG deserved to be saved by the Public power and not the Lehman Brothers Investment Bank, which also had profitable branches close to its “toxic” assets. In fact, the authorities have ruled that the bankruptcy of the number one global insurance, given its size, could lead to a systemic crisis. It’s called the syndrome of “too big to fail”.

The AIG episode reminds a Donald Trump formula, the eccentric New Yorker businessman: “If you owe the bank a million dollars the bank owns you, but if you owe the bank a billion dollars you own the bank.” As pointed out already by some American financial analysts, this philosophy does not encourage prudence and penalizes smaller actors, who they will be not saved in case of a real blow.

Such structural responses to the crisis included interventions such as the ‘Troubled Assets Relief Program (TARP) and Emergency Economic Stabilization Act (EESA). Though proposed to mitigate losses, many of these interventions are argued by Wehinger not be adequate in responding to the crisis when he stated “reforms may be needed to mend a system in which gains are privatized and losses are socialized, which would no doubt strike the median voter as being fundamentally unfair” (10). It has also been claimed that the collapse of Lehman Brothers Holdings and AIG are strong indications of market inefficiencies that led to their crash. Gerald (1) and RayBall (1) argue that the crash would have been predicted if the market were indeed efficient and minimized what Benton (3) terms as huge government bailouts (Brunnermeie and Pederson 3).

Risks inherent in derivatives trading such as credit-default swaps were brought to light during the current crisis Preliminary research evidence that CDS markets continued to grow and expand and gained tremendous interests rates regardless of the financial turmoil and became unstable when the U.S government took over in September 2008 triggering large defaults in market derivatives forcing marker derivatives into conservatorship (Wehinger 28). In fact, AIG had in its accounts $ 440 billion of credit-default swaps. And that was just a part of the $ 2.7 trillion of AIG Finacial Products. In the end, losses on certain credit default swaps and collateral calls by other actors that are counterparties to these CDS are the main source of AIG’s problems.


It has always been believed that markets are efficient in reflecting information about stocks and stock markets. The relationship between efficiency and predictability proves that EMH does not reflect current information that investors can fully rely on. The failing of the EMH system attacks the theory of efficient-market hypothesis which brings us to the conclusion that markets are more efficient and less predictable than what econometric would have us believe.


Bacon, Frank., & Gerdorff, Newton. “U.S Mergers and Acquisition: A Test of Market Efficiency.” Journal of Finance and Accountancy, 1 (2007): 8.

Benton, Gup. Too big to fail: policies and practices in government bailouts. Westport, United States: Praeger Publishers, 2004

Bernanke, Benjamin., Gertler, Mark., & Gilchrist, Simon. The Financial Accelerator in a Quantitative Business Cycle Framework. Princeton University Press: New York, 1998

Bernanke, Benjamin., & Lown, Cara. “The Credit Crunch.” Brookings Papers on Economic Activity, 2 (1991): 205-47

Bollerslev, Tim, & Hodrick, Robert. “Financial Market Efficiency Tests.” National Bureau of Economic Research, 1081(992): 78

Brunnermeie, Markus. Bubbles, Liquidity and the Macroeconomy. NBER, 2538 (2008): 1-7

Brunnermeier, Markus.,& Abreu, David., “Bubbles and Crashes.” Econometrica, 67.1 (2003): 1-24

Brunnermeier, Markus.,& Pedersen, Lasse. “Market Liquidity and Funding Liquidity.” NBER WP, 12939 (2007): 1-15

Clarke, Jonathan., Jandik, Tomas., & Mandelker, Gershon. “The Efficient Markets Hypothesis.” Journal of Finance, 2 (1991): 22

Cutler, David., Poterba, James.,& Summers, Lawrence. “What moves stock prices?” NBER, 2538 (1989): 1-67

Damodaran, Andrew. “Market Efficiency: Definitions and Tests.” Financial Review Journal , 2 (2007): 45

Fama, Eugene., & French, Kenneth. “Permanent and Temporary Components of Stock Prices.”Journal of Political Economy, 6(1988): 46-273.

Gerald, Keith. “The Efficient Market Fallacy and How Investors Can Profit From It.” Jutia Group, 1(2010): 1

Malkiel, Burton. A Random Walk Down Wall Street. New York: Norton & Company, 1973

Mizen, Paul. “The Credit Crunch of 2007-2008: A Discussion of the Background Market Reactions, and Policy Responses.” Journal of Finance, 90.5 (2008): 1-38

Ray Ball, Ubrer. “The Efficient Markets Hypothesis: What Have We Learned?” Macromania, 1(2010): 1

Ross, Stephen., & Randolph, Westerfield. Corporate Finance. United States, McGraw-Hill Companies, 2008

Shin, Hyun Sung.,& Tobias., Adrian. “Liquidity, Monetary Policy, and Financial Cycles: Federal Reserve Bank of New York. Current Issues in Economics and Finance, January/February 14.1 (2008): 2

Wehinger, Gert. “Lessons from the financial market turmoil: Challenges ahead for the financial industry and policy makers.” Financial Market Trend, 2864 (2008): 1-40

Winton, Harding. “The Wizards of Winton.” Trader Daily, 1 (2008): 1-5

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EduRaven. (2022, March 23). Market Efficiency Hypothesis Overview. Retrieved from


EduRaven. (2022, March 23). Market Efficiency Hypothesis Overview.

Work Cited

"Market Efficiency Hypothesis Overview." EduRaven, 23 Mar. 2022,


EduRaven. (2022) 'Market Efficiency Hypothesis Overview'. 23 March.


EduRaven. 2022. "Market Efficiency Hypothesis Overview." March 23, 2022.

1. EduRaven. "Market Efficiency Hypothesis Overview." March 23, 2022.


EduRaven. "Market Efficiency Hypothesis Overview." March 23, 2022.


EduRaven. 2022. "Market Efficiency Hypothesis Overview." March 23, 2022.

1. EduRaven. "Market Efficiency Hypothesis Overview." March 23, 2022.


EduRaven. "Market Efficiency Hypothesis Overview." March 23, 2022.