The Efficient Market Hypothesis (EMH) is a financial theory that posits that financial markets are “efficient”, meaning that prices reflect all available information at any given time.Eugene Fama in the 1960s, the hypothesis states that it’s impossible to “beat the market” because the stock market efficiency causes existing share prices always to incorporate and reflect all relevant information.
Developed by economistThe fundamental implication of EMH is that barring insider trading, no amount of analysis can give an investor an edge over other investors. It’s a principle that puts every investor on an equal footing, but it’s not without its detractors and limitations.
Critics of EMH argue that it underestimates the impact of human error, cognitive biases, and herd behaviour on market outcomes. Despite this, the EMH has significantly influenced financial and investment theories and strategies.
Three Forms of EMH
The three forms of efficient market hypothesis are differentiated by their assumptions about the types of information the market absorbs. These three forms of EMH are:
- Weak-form EMH: This form of EMH asserts that all the past prices of a stock are reflected in the current stock price. Therefore, it would be impossible to profit from patterns in historical prices since they don’t predict future prices. In other words, technical analysis methods will not be able to produce excess returns consistently.
- Semi-strong form EMH: This form of EMH posits that all publicly available information is incorporated into a stock’s current price. Hence, neither fundamental analysis, which looks at factors like company earnings, economic reports, and other market indicators, nor technical analysis methods can predict future prices reliably and gain superior results.
- Strong-form EMH: The strongest form of EMH asserts that all information, public and private, is fully accounted for in a stock’s current market price. In other words, even insiders with private information cannot achieve superior results consistently. This form of EMH implies perfect market conditions, which is generally considered an overly idealistic scenario.
Challenges to Efficient Market Hypothesis
Despite its profound influence, EMH has been criticised and challenged. One primary critique is that EMH underestimates the impact of human behaviour and cognitive biases in driving market outcomes. Several key factors can influence the degree to which a market conforms to the principles of EMH. Below are some of them:
- Information accessibility and dissemination: The speed and accuracy with which information is disseminated among investors significantly influence the efficiency of the markets. If all investors have equal and instant access to all relevant information, prices can adjust quickly to reflect new information, promoting market efficiency. However, discrepancies in information access can create inefficiencies.
- Market anomalies: EMH doesn’t account for market anomalies such as stock market bubbles and crashes. These phenomena often involve price deviations from intrinsic values, suggesting markets may not always efficiently reflect all available information.
- Behavioural factors: Behavioral finance, a field of study that explores how psychological factors influence investors’ decisions, offers insights into why markets might not always be efficient. Factors such as overconfidence, overreaction, herd behaviour, information cascades and other biases can cause prices to deviate from their true value. However, EMH assumes that investors are rational and respond logically to information.
- Limits to arbitrage: Arbitrage refers to taking advantage of price differences in different markets. EMH assumes that rational investors will quickly arbitrage away any mispricings, but arbitrage can be risky and costly. These limitations can prevent arbitrageurs from fully correcting mispricings, leading to potential deviations from market efficiency. Risks and constraints, for example, the difficulty of finding a perfect hedge, can limit arbitrage, allowing mispricing to persist.
- Transaction costs: Transaction costs, including brokerage fees and bid-ask spreads, can inhibit the immediate reflection of price information. For instance, if transaction costs are high, investors might choose not to trade, even when they have information that should affect prices. This delay in trading can prevent prices from fully reflecting available information.
- Information interpretation: Even when all investors have access to the same information, they might interpret it differently. Differences in analysis methods, expertise, and judgment can lead to different conclusions about an asset’s value, causing prices to diverge from the predictions of the EMH.
- Market structure: The structure and regulations of a market can also affect its efficiency. For instance, restrictions on short-selling can prevent negative information from being fully incorporated into prices. Similarly, market mechanisms like circuit breakers, which halt trading after extreme price moves, can delay the reflection of price information.
- Market participants: The diversity and number of market participants can influence market efficiency. Markets with more participants, each with different information sources and perspectives, are more likely to be efficient because they can better interpret and react to new information collectively.
EMH and investment strategies
Despite its limitations, the EMH remains highly relevant to investors. It underscores the inherent difficulty of consistently outperforming a well-diversified market portfolio, thereby highlighting the importance of passive investment strategies such as buying and holding index funds. Below is a discussion on EMH and investment strategies.
- Passive investing and EMH: If markets are efficient and prices reflect all available information, as EMH suggests, it’s impossible to consistently achieve higher returns without taking on additional risk. This is where passive investing comes into play. A passive investment strategy, for example, investing in an index fund tracking ASX 300, involves buying a diversified set of assets and holding them for a long period. Since this approach involves minimal buying and selling, it incurs lower transaction costs and typically outperforms actively managed funds in the long run.
- Active investing and EMH: On the other hand, active investing involves frequent buying and selling of securities intending to outperform the market. While EMH suggests this strategy will fail over the long term, some active investors beat the market, at least for a while. But critics often attribute these instances to luck rather than skill. Still, the potential for higher returns continues to attract investors to active investing.
EMH underscores that a higher return can only be achieved by taking on higher risk. Therefore, an investor’s strategy should align with their risk tolerance.
Research conducted to arrive at Efficient Market Hypothesis
The formulation of EMH resulted from extensive research and analysis of historical stock prices. The critical technical research that underpins the EMH can be broadly grouped into:
- Empirical analysis: Empirical evidence plays a significant role in formulating the EMH. In his 1965 paper ‘Random Walks in Stock Market Prices’, Fama summarised the empirical findings, illustrating that stock price changes are unpredictable and follow a ‘random walk’. This means that past movements or trends of a stock price cannot help predict its future movement. The paper comprehensively analysed the statistical properties of stock market prices, concluding that they strongly support the random walk hypothesis.
- Theoretical framework: While EMH relies heavily on empirical evidence, it also requires a solid theoretical foundation. This theoretical foundation was provided by the model of competitive markets and equilibrium from microeconomic theory, which suggests that prices in a competitive market reflect all available information as participants are always looking for profitable opportunities.
- Statistical techniques: EMH uses sophisticated statistical methods to analyse stock market data. These techniques test whether stock returns follow a random walk and whether deviations from the random walk hypothesis can be exploited for profit. For example, in the 1960s and 1970s, Fama and his co-authors used advanced econometric techniques to test the three forms of market efficiency (weak, semi-strong, and strong).
- Event studies: The event study is a standard method of testing the semi-strong form of the EMH. This study analyses the market’s reaction to new information (such as earnings announcements, mergers, or dividend announcements). If the market is semi-strong efficient, the price should adjust almost instantly to reflect that new information. Much of this study has found that markets are relatively quick to incorporate publicly announced new information into prices.
Evolution of Efficient Market Hypothesis
EMH has evolved since its inception in the 1960s, mostly in response to empirical challenges and the development of new theories and perspectives.
One of the significant developments has been the emergence of behavioural finance. This field, which studies the impact of investor psychology on financial decisions, has challenged the notion that markets always behave rationally. Researchers in behavioural finance have documented numerous biases and cognitive errors that can cause investor behaviour to deviate from rationality, potentially leading to market anomalies inconsistent with the EMH.
For example, phenomena like overreaction and underreaction to news, momentum and mean-reversion in stock returns, and bubbles and crashes in asset markets have been linked to psychological biases. As a result, they are difficult to reconcile with the EMH. These insights have led to modifications of the EMH, such as the Adaptive Market Hypothesis (AMH), which combines principles from EMH and behavioural finance.
Another significant development has been the recognition of limits to arbitrage. Traditional EMH assumes that when assets are mispriced, rational investors will quickly take advantage of the mispricing, bringing prices back to their fair value. However, research has shown that arbitrage is often risky and costly, which can prevent arbitrageurs from fully correcting mispricings.
Moreover, empirical research has identified several anomalies that seem inconsistent with the EMH, such as the small-firm effect, the January effect, and the momentum effects. These anomalies have spurred further modifications to the EMH and the development of new asset pricing models.
While the core principle of the EMH – that prices reflect all available information – has remained relatively stable, our understanding of market efficiency and the factors that influence it has evolved substantially since the 1960s. Researchers continue to refine the hypothesis and develop new theories to explain market behaviour.
EMH and the University of Chicago
Chicago School of Economics is a school of economic thought from the University of Chicago. It emphasises free-market principles, such as minimal government intervention, fiscal responsibility, and individual autonomy. Eugene Fama, a prominent Chicago School member, is often called the ‘father of modern finance’. Fama was a student and later a professor at the University of Chicago Booth School of Business. In his doctoral thesis at the University of Chicago and subsequent research, he proposed the idea of market efficiency.
The University of Chicago has long been a leading institution for the study of financial economics, and many other academics associated with the university have contributed significantly to the field. The Chicago School has been influential in developing several fundamental economic theories and concepts, including the Efficient Market Hypothesis (EMH). EMH aligns with the Chicago School’s emphasis on rationality and the power of free markets. Furthermore, the Center for Research in Security Prices (CRSP) at the University of Chicago has provided comprehensive data on stock prices, returns, and other market information, which has been widely used in empirical tests of the EMH.
However, it’s worth noting that while EMH aligns with the principles of the Chicago School, it has also faced challenges and criticisms, even from within the school. For example, Richard Thaler, another economist from the University of Chicago, is a prominent behavioural economics figure highlighting cognitive biases and irrational behaviour in economic decision-making. These factors can lead to market anomalies and deviations from efficiency, challenging the assumptions of the EMH.
Other theories related to EMH
Several financial and economic theories are closely related to the Efficient Market Hypothesis (EMH). Here are a few of them:
- Random Walk Hypothesis: The Random Walk Hypothesis states that price changes in securities are random and not predictable. This idea is closely linked with the weak form of the EMH, which asserts that all past market prices and data are fully reflected in current prices. Therefore, according to both theories, technical analysis cannot consistently produce superior investment results.
- Fama-French Three-Factor Model: This is an asset pricing model developed by Eugene Fama and Kenneth French, who are both associated with the University of Chicago and the development of the EMH. The model suggests that three factors – market risk, the size effect, and the value effect – explain a large portion of the differences in returns between diversified portfolios. Like the EMH, this model assumes that markets are rational and efficient.
- Modern Portfolio Theory (MPT): MPT offers a mathematical framework for assembling a portfolio of assets to maximise the expected return for a given level of risk. It is predicated mainly on the notion that markets are efficient, as it assumes that market risk, as measured by variance or standard deviation of return, is fully reflected in the price of a security. Also, refer to the ‘Relation between MPT and Efficient market hypothesis‘ section in our An introduction to Modern Portfolio Theory (MPT) page.
- Capital Asset Pricing Model (CAPM): The CAPM describes the relationship between expected return and risk in a security. It proposes that the expected return on an investment is proportional to its systematic risk (also known as market risk). If markets are efficient, as suggested by EMH, then prices would adjust to the level where the expected return equals the return predicted by CAPM. CAPM, therefore, supports the EMH by providing a model of how asset prices should behave in an efficient market.
- Arbitrage Pricing Theory (APT): APT is another asset pricing model that, like CAPM, describes how securities should be priced in an efficient market. It proposes that one can model the expected return of a financial asset as a linear function of different macroeconomic factors. If markets are efficient, then prices should adjust until there are no arbitrage opportunities, which is the central idea behind APT.
- Behavioural Finance: Although not always in agreement with EMH, the field of behavioural finance is nonetheless closely related. It focuses on how cognitive biases and irrational behaviours can lead to anomalies in financial markets. While EMH assumes that investors are perfectly rational, behavioural finance explains why markets might deviate from perfect efficiency.
- Adaptive Market Hypothesis (AMH): AMH combines principles from EMH and behavioural finance. It suggests that markets are not always efficient but can adapt to become more efficient over time. This perspective acknowledges that investors may behave irrationally in the short term, leading to inefficiencies, but argues that competition among investors and learning over time can help markets become more efficient.
Related information
Refer to the related knowledge resources:
- An introduction to Modern Portfolio Theory (MPT)
- Myths about Modern Portfolio Theory (MPT)
- Common questions about Modern Portfolio Theory (MPT)
- An introduction to Random Walk Hypothesis
- Efficient Market Hypothesis (EMH)
- Risk-adjusted returns
- Relevance of covariance and correlation in portfolio construction
- An introduction to reversion to the mean
QuietGrowth has been publishing content in this blog or in other sections of the website. Contributors for this content may include the employees of QuietGrowth, or third-party firms, or third-party authors. Unless otherwise noted, such content does not necessarily represent the actual views or opinions of QuietGrowth or any of its employees, directors, or officers.
Any links provided in our website to other websites are for the purpose of convenience, or as required by any such other websites. Unless otherwise noted, this does not imply that QuietGrowth endorses, is affiliated, and/or promotes any information, or products or services of those websites. Please read the advice disclaimer section of the website too.