When money is put into the stock market, the goal is to generate a return on the capital invested. Many investors try not only to make a profitable return, but also to outperform, or beat, the market.
However, market efficiency - championed in the efficient market hypothesis (EMH) formulated by Eugene Fama in 1970, suggests that at any given time, prices fully reflect all available information on a particular stock and/or market. Fama was awarded the Nobel Memorial Prize in Economic Sciences jointly with Robert Shiller and Lars Peter Hansen in 2013. According to the EMH, no investor has an advantage in predicting a return on a stock price because no one has access to information not already available to everyone else.
The Effect of Efficiency: Non-Predictability
The nature of information does not have to be limited to financial news and research alone; indeed, information about political, economic and social events, combined with how investors perceive such information, whether true or rumored, will be reflected in the stock price. According to the EMH, as prices respond only to information available in the market, and because all market participants are privy to the same information, no one will have the ability to out-profit anyone else.
In efficient markets, prices become not predictable but random, so no investment pattern can be discerned. A planned approach to investment, therefore, cannot be successful.
This "random walk" of prices, commonly spoken about in the EMH school of thought, results in the failure of any investment strategy that aims to beat the market consistently. In fact, the EMH suggests that given the transaction costs involved in portfolio management, it would be more profitable for an investor to put his or her money into an index fund.
Anomalies: The Challenge to Efficiency
In the real world of investment, however, there are obvious arguments against the EMH. There are investors who have beaten the market - Warren Buffett, whose investment strategy focuses on undervalued stocks, made billions and set an example for numerous followers. There are portfolio managers who have better track records than others, and there are investment houses with more renowned research analysis than others. So how can performance be random when people are clearly profiting from and beating the market?
Counter arguments to the EMH state that consistent patterns are present. For example, the January effect is a pattern that shows higher returns tend to be earned in the first month of the year; and the weekend effect is the tendency for stock returns on Monday to be lower than those of the immediately preceding Friday.
Studies in behavioral finance, which look into the effects of investor psychology on stock prices, also reveal that investors are subject to many biases such as confirmation, loss-aversion and overconfidence biases.
The EMH Response
The EMH does not dismiss the possibility of market anomalies that result in generating superior profits. In fact, market efficiency does not require prices to be equal to fair value all the time. Prices may be over- or undervalued only in random occurrences, so they eventually revert back to their mean values. As such, because the deviations from a stock's fair price are in themselves random, investment strategies that result in beating the market cannot be consistent phenomena.
Furthermore, the hypothesis argues that an investor who outperforms the market does so not out of skill but out of luck. EMH followers say this is due to the laws of probability: at any given time in a market with a large number of investors, some will outperform while others will underperform.
How Does a Market Become Efficient?
For a market to become efficient, investors must perceive that the market is inefficient and possible to beat. Ironically, investment strategies intended to take advantage of inefficiencies are actually the fuel that keeps a market efficient.
A market has to be large and liquid. Accessibility and cost information must be widely available and released to investors at more or less the same time. Transaction costs have to be cheaper than an investment strategy's expected profits. Investors must also have enough funds to take advantage of inefficiency until, according to the EMH, it disappears again.
Degrees of Efficiency
Accepting the EMH in its purest form may be difficult; however, three identified EMH classifications aim to reflect the degree to which it can be applied to markets:
| 1. Strong efficiency - This is the strongest version, which states that all information in a market, whether public or private, is accounted for in a stock price. Not even insider information could give an investor an advantage.
2. Semi-strong efficiency - This form of EMH implies that all public information is calculated into a stock's current share price. Neither fundamental nor technical analysis can be used to achieve superior gains.
3. Weak efficiency - This type of EMH claims that all past prices of a stock are reflected in today's stock price. Therefore, technical analysis cannot be used to predict and beat a market.
The Bottom Line
In the real world, markets cannot be absolutely efficient or wholly inefficient. It might be reasonable to see markets as essentially a mixture of both, wherein daily decisions and events cannot always be reflected immediately into a market. If all participants were to believe that the market is efficient, no one would seek extraordinary profits, which is the force that keeps the wheels of the market turning.
In the age of information technology (IT), however, markets all over the world are gaining greater efficiency. IT allows for a more effective, faster means to disseminate information, and electronic trading allows for prices to adjust more quickly to news entering the market. However, while the pace at which we receive information and make transactions quickens, IT also restricts the time it takes to verify the information used to make a trade. Thus, IT may inadvertently result in less efficiency if the quality of the information we use no longer allows us to make profit-generating decisions.