The Efficient Market Hypothesis has become the cornerstone of financial scholars’ empirical research, using scientific method. Instead of seeking out Warren Buffett or other “gurus”, they collected objective data and critically appraised theories systematic.
The strongest version of this hypothesis asserts that stock prices reflect all available information, making it virtually impossible for investors to outwit the market by strategically picking stocks.
Informational Efficiency
Although empirical evidence to 1970 supports weak-form and semi-strong-form informational efficiency, no definitive proof that markets are efficient has ever been provided. Many obstacles impede testing this hypothesis effectively.
Many studies rely on inaccurate statistical models for price changes, leading to unreliable test results and disconfirming the efficient market hypothesis. When prices diverge from those found in market portfolios, this could imply that certain policies provide greater income than their risk compensation – thus contradicting this assumption of efficiency.
Some studies conflate market inefficiency with deviations from fundamental values and ignore how fluctuations may alter price distribution. Many of the tests that challenge EMH use a Samuelson-type definition of efficiency that doesn’t correspond with actual markets; Lo (2004) uses an alternative method for assessing degrees of efficiency using statistical measures of autocorrelation between past and future prices.
Transaction Costs
Problems encountered while testing The Efficient Market Hypothesis are typically related to transaction costs, which include those related to research and trading as well as those inherent to making trades. Overall, transaction costs impede investors in finding inefficiencies within markets to exploit for financial gain.
An additional issue lies with the concept of risk tolerance. Investors may opt for policies with greater profits but also pose higher levels of risk than market portfolios; such strategies raise questions as to whether their existence contradicts The Efficient Market Hypothesis.
Note, however, that any inefficiencies discovered by investors will self correct as soon as investors systematically sell or purchase shares to reflect this information. This process makes markets an effective self correcting mechanism, thus decreasing inefficiency found within them – in which case, The Efficient Market Hypothesis remains valid despite its weak form.
Market Frictions
Market efficiency is an increasingly relevant concept to grasp in an age when news outlets, analysts, and Internet gurus provide investors with constant advice about what to do (or not do) with their money. According to the Efficient Market Hypothesis, security prices generally reflect fundamental value accurately.
Market frictions prevent markets from operating perfectly efficiently at all times; for instance, search costs and switching costs make it more difficult for consumers to learn about the quality of different firms’ products.
These costs also play a part in how quickly traders respond to information about a firm’s product, leading to anomalies like the small-firm effect and January effect that persist for longer than expected. As a result, studies in the tradition of AMH must employ process-based definitions of efficiency in order to explain such phenomena.
Allowable Risk
There can be numerous reasons for markets not to be fully efficient; these could include information asymmetries, transaction costs, trading delays or market psychology. Yet the EMH remains one of the most influential theories in financial research.
One of the major shortcomings of EMH is that it fails to explain material nonpublic information (MNPI). MNPI could be acquired by professional analysts or insiders and then released publically; security prices would then adjust accordingly.
EMH faces another difficulty in its failure to explain why investors can beat the market; this may be caused by behavioral biases like overconfidence, overreaction, representative bias and information bias. Furthermore, standard statistical tests cannot assess degree of efficiency as this depends on data sets chosen; some scholars have attempted to develop tests which assess degrees of efficiency within individual markets.
