What is the Efficient Market Hypothesis?

The efficient market hypothesis (EMH) is an investment theory that states it is impossible to "beat the market" because stock market efficiency causes existing share prices to always incorporate and reflect all relevant information.

The EMH was first proposed by University of Chicago professor Eugene Fama in his 1970 paper "Efficient Capital Markets: A Review of Theory and Empirical Work." Fama's paper built on the work of earlier scholars, including Nobel laureate Harry Markowitz and economist Paul Samuelson.

How the Efficient Market Hypothesis Works

The efficient market hypothesis states that at any given time, stock prices fully reflect all available information. This means that it is impossible for investors to achieve returns in excess of the average market return simply by analyzing publicly available information. All current information is already priced into a security, so there is no "edge" to be gained.

In an efficient market, new information is rapidly disseminated throughout the market and reflected in stock prices very quickly. Prices may still fluctuate in the short term due to irrational investor behavior or other factors, but over time these fluctuations should even out and prices should reflect true underlying value.

There are three different levels of market efficiency: strong form, semi-strong form, and weak form efficiency.

Strong Form Efficiency: In a strong form efficient market, all information—public as well as private—is already reflected in stock prices. This means that even insider trading would not allow an investor to achieve above-average returns.

Semi-Strong Form Efficiency: A semi-strong form efficient market is one where all public information—such as company financials, earnings releases, etc.—is reflected in stock prices. However, private information—such as analyst research reports or tips from industry insiders—may not be fully incorporated into prices yet. This means that there may be some opportunities for investors who have access to this type of information to achieve above-average returns.

Weak Form Efficiency: In a weak form efficient market, only past price data is reflected in current stock prices. This means that there may be patterns in stock price movements that can be exploited by investors to achieve above-average returns. Technical analysis falls into this category; proponents of this strategy believe that they can identify patterns in past price data that will give them an edge in predicting future price movements.

The Efficient Market Hypothesis Today

The EMH has been widely studied and there is a great deal of academic research on the topic. While the theory has been challenged over the years, it still is widely referenced in practice. Many studies have found evidence supporting at least weak form efficiency in the U.S. markets, though there is less agreement on whether strong form or semi-strong form efficiency exists.

The efficient markets hypothesis remains a controversial topic among investors and academics alike, but its impact on investing cannot be understated. The EMH has been influential in shaping modern portfolio theory and asset pricing models, which are used by investors around the world to make decisions about how to allocate their capital.

The biggest critique for EMH is that it doesn't account for market biases that are created due to behavior of investors and traders as well as the impact of algorithms in modern times.

There are several alternatives proposed to EMH. One of them is the Adaptive Market Hypothesis (AMH).
And then there are metrics like the Adjusted Market Inefficiency Magnitude (AMIM) that are researched to provide a quantifiable way to measure the level of efficiency in the market.


It is important to be aware of these theories that are prevalent in the market as it helps us form our own investing and trading hypothesis to create a systematic way to trade. Every trading system should go through a rigorous phase of backtesting, simulation testing, and forward testing before it is used in practice to make trading and investing decisions. Researchfin.ai makes it extremely simple for anyone to create trading systems irrespective of their trading or coding experience.

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