Efficient Market Hypothesis

The Basic Idea

The efficient market hypothesis is an economic theory which stipulates that the prices of traded assets, like stocks, reflect all the publicly available information of the market.1 This means that if you are investing in assets based on public information, it is impossible to outperform the market over time, because buyers and sellers are working with this same information.2 The efficient market hypothesis is part of liberal economic thought, as it follows neoliberal thought of the efficient free-market that does not require any intervention.

In order to better understand the efficient market hypothesis, it is first important to understand basic stock investing. At its simplest level, stock prices will change based on positive or negative information about the corporation to which they belong. This is because if an investor hears good news about a corporation, they will likely go buy stocks of this corporation, thus driving up the stock price. If an investor hears bad news about a corporation, they might sell their stocks, therefore lowering the stock price.

The efficient market hypothesis suggests that there is a direct relationship between news (or information) and prices, as buyers and sellers generally have access to the same information. If prices move according to public information, they occur efficiently (in a timely manner), which means that stocks are trading at their ‘fair’ price.3

Information cannot be predicted by the general public, as proponents of the hypothesis say that the market is random. Therefore, it follows that investors cannot ‘beat’ the market by buying undervalued stocks or selling inflated prices. Although you might get lucky once or twice, the efficient market hypothesis suggests that you cannot consistently outperform the market average when it comes to investment returns.3 Investors therefore have to make decisions through speculation, which has great risks.4

For example, you might now be sitting at home thinking that you should have invested in Zoom, whose stock prices increased by more than 100% since COVID-19 began.5 However, before the pandemic, these stocks weren’t ‘undervalued’, because no one could have predicted a global shutdown that forced millions to work from home. According to the efficient market hypothesis, based on publicly available information, it would have been impossible for you to realize that Zoom stocks would increase in price until they already had, at which point you wouldn’t make as much by buying stocks at the new inflated price.

I’d compare stock pickers to astrologers but I don’t want to bad mouth astrologers.

– Eugene Fama, the ‘father’ of modern finance1

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Key Terms

Fundamental Analysis: a trader analysis strategy that tries to predict price movements in the stock market by gauging if a stock is undervalued or overvalued by examining factors like the state of the economy, industry conditions, or even the effectiveness of a company’s management.6

Technical Analysis: a trader analysis strategy that examines past price movements in order to predict future price movements in the stock market.7

Random walk theory: a theory that suggests that changes in stock prices are completely independent of other stock price changes, which means that trends in a market cannot be used for prediction.8

Economic/Asset Bubble: a surge in asset prices (driven by exhilarated market behavior) which causes the stock price of an asset to greatly exceed its fair market value. Usually, the rapid escalation of market value is followed by a ‘crash’, where the bubble bursts and assets quickly decrease in value.9


People who partake in stock investment are usually motivated by a goal of making money based on the existence and identification of undervalued and overvalued shares. Investors are always trying to ‘beat the market’ – but the efficient market hypothesis challenges the idea that this is ever possible.

Way back in the early 1900s, French mathematician Louis Bachelier performed a stock-market analysis that demonstrated the randomness of the market: today’s returns had no impact on tomorrow’s stocks.10 Although the efficient market hypothesis didn’t come to fruition until 1970, work conducted by people like Bachelier set the groundwork for the hypothesis. By showing that the stock market operated partially according to random action, Bachelier suggested that it would be impossible to predict the movement of stock prices, an important step towards the efficient market hypothesis.10

In 1965, Eugene Fama, who has been a key player in the development of modern finance, used Bachelier’s random walk model to show that the techniques used by technical analysts to predict stock returns had no power.10 At first, the emphasis on the randomness of the market led many economists to abandon the economic meaning of stock returns. However, in the mid-1960s, this view began to change as economists demonstrated that randomness in returns was to be expected from an efficient stock market. Essentially, they suggested that the only thing that could be predicted is the fact that stock market turns would be unpredictable.

Eugene Fama formalized his ideas in his now-famous paper, “Efficient Capital Markets: A Review of Theory and Empirical Work.” In this 1970 paper, he divided the efficient market theory into three hypotheses: the weak form, the semi-strong form, and the strong form.

The weak form states that today’s market price reflects all past data and therefore no form of technical analysis will help investors make predictions, although fundamental analysis can still help. The semi-strong form states that because all publicly available information is part of a stock’s current price, only insider information can help investors, rather than technical or fundamental analysis. The strong form states that both publicly available and non-publicly available information is already reflected within a stock price, so there is no additional information that can help people ‘beat the market’.4

In the 1970s, the semi-strong form of the efficient market hypothesis was most widely accepted. However, in the 1980s, a number of inconsistencies put the belief under question.10


Financial economic theories have large implications for society; often, different theories benefit and cost different groups. The efficient market hypothesis has important political implications by adhering to liberal economic thought.

The efficient market hypothesis suggests that there need not be any governmental intervention within the market because stock prices are always being traded at a ‘fair’ market value. The efficient market hypothesis was used as evidence by researchers at Michigan Business & Entrepreneurial Law to push the notion of deregulation of the financial sector. Deregulation proposes that state regulations should be lifted because the market is self-regulating and self-correcting.11 If the market is efficient by itself, then government intervention and regulation might actually be harmful and stifle competition.

The efficient market hypothesis also has implications for the field of behavioral economics. The hypothesis suggests that investors are rational people who buy and sell stocks based on available information. It therefore gives credence to traditional economic theory instead of behavioral economics, as the former believes in homo economicus, the perfectly rational being, while the latter believes that people are often influenced by ‘irrational’ factors like emotions, beliefs and cultural influences in their financial decisions. Of course, only a certain amount of information is available to any one person at any given time, and therefore decisions are bound by limitations (bounded rationality).

Most directly, however, the efficient market hypothesis has consequences for investors and analysts. By suggesting that predictions on stock returns are based on nothing more than speculation, the hypothesis leaves little room for fundamental or technical analysis. The efficient market hypothesis opposes technical trading strategies and instead suggests that people should invest their money in lower risk markets, like low-cost portfolios.12


Before the efficient market hypothesis emerged in the 1970s, the reigning economic theory on the financial market was that speculation impacted the price of stocks. This belief was perpetuated by John Maynard Keynes in 1936, who suggested that because investors make decisions based on what they think other investors are going to do, stock prices are more closely aligned to speculation than economic fundamentals.10 Today, many people still believe that people’s opinions on the market- for example, how optimistic or pessimistic they feel about the world – can drive excessively high or excessively low stock prices. Stocks, therefore, are not always traded at a fair market price.3

If people make investing decisions based on their predictions of others’ behavior, or based on optimistic and pessimistic moods, then people are not purely rational investors. Behavioral economists, who know that people are often irrational, therefore argue against the efficient market hypothesis. Economist Richard Thaler, for example, conducted a study showing that markets tend to ‘overreact’ following trends: When a stock performed well over a 3-5 year period they often reverted their means over the next 3-5 years. Such extreme swings away from economic foundations suggests that stock prices are not always equated to a ‘fair market value’.10

Other principles, like the neglected firm effect, also provide evidence against the efficient market hypothesis. The neglected firm effect stipulates that because the stocks of lesser-known companies are left out of market analysis, savvy investors can buy their undervalued stocks, which means that the lesser-known companies often end up outperforming better known companies.13

The fact that people do actually often make millions from trading in the stock market also calls the efficient market hypothesis into question. For example, Warren Buffett, John Templeton, Peter Lynch and Paul Tudor Jones are all investors who consistently generate great returns that go beyond the performance of the overall market.3  If the efficient market hypothesis suggests all people have an equal opportunity to make money since prices react to public information, then people would certainly not be able to make so much more than others from investing.

To discuss controversies surrounding the efficient market hypothesis, it is important to discuss the 2008 financial crisis. Some people believe that the financial crisis could have been predicted, but that proponents of the efficient market hypothesis failed to see the bubble in asset prices, and that if they did not blindly follow the hypothesis, they may have been able to give people due warning.14 However, others suggest that it is because not enough people believed in the efficient market hypothesis that the crisis occurred. Proponents of this argument say that because people thought it was easy to beat the market, there was a large amount of investment in short-term trends. Investors had to borrow heavily in order to invest in these short-term trends, which led to banks having heavy debt burdens that contributed to the economic crisis.14 

The 2008 financial crisis also brought under question whether deregulation of the financial sector was in fact beneficial. According to the efficient market hypothesis, the government should not have intervened following the crash, as stocks would eventually have levelled back out by themselves thanks to an efficient market. The government did intervene, however, which means we will never really know if the market could have survived without intervention.

Case Study

COVID-19 and the Financial Market

According to the efficient market hypothesis, prices in the market will quickly adapt to public information and perception. However, American economist Robert Shiller disputes this view in light of the recent global pandemic. The S&P 500 index, which measures the stock performance of 500 large companies, showed an all-time record high on February 19th, 2020, as the virus began to spread across the globe.15 This trend suggests that the U.S market was not rationally responding to publicly available information, as people were investing more than ever even as they were seeing cities shut down and people forced to cease working, which should have indicated that they should hold onto their money to prepare for what might be coming their way. This data suggests that the financial market is more irrational than the efficient market hypothesis suggests.

However, alternatively, COVID-19 demonstrates just how unpredictable the market is: who could have presumed what kind of stocks would shoot up in price, and what kind would crash, if we could not predict the state of the world? Neither fundamental nor technical analysis would have proven to be useful trading strategies during these unprecedented times.

Related TDL Resources

What Can George Costanza Teach Us About Making Better Investment Choices? 

Investing is incredibly difficult. According to our writer Shayan Gose, one of the biggest mistakes people make while investing is the disposition effect: selling assets that have increased in value and keeping assets that have decreased in value because we are driven by  pride, rather than profit. The disposition effect doesn’t make sense for a financial market that adheres to the efficient market hypothesis and homo economicus, leading Gose to lend advice on how to avoid the disposition effect and stick to rational investment decisions.

Phantasy: The Unconscious Process Behind Financial Instability

This article takes the opposing view from the efficient market hypothesis. TDL’s editor Nathan Collett interviews business administration researcher Selim Aren, who suggests that unconscious drivers are often the force behind the fluctuations in today’s financial market. Similarly to Keynes, Aren suggests that speculation and herd behavior influence  stock prices therefore stock prices often do not reflect fair market value.

Warren Buffett: Your $85 Billion Average Joe

A proponent of ‘value investing,’ Warren Buffett has made billions of dollars off the stock market by choosing his investments wisely and sticking with them for decades. Unlike many other investors, Buffett is not eager to trade, and is instead willing to see his investments through until they provide returns, rather than rushing to sell them.


  1. Ting So, S. (2019, July 19). The very annoying efficient market hypothesis and how to beat it. Medium. https://medium.com/endowus-insights/the-very-annoying-efficient-market-hypothesis-and-how-to-beat-it-21794a73754a
  2. Marginal Revolution University. (2018, April 7). What Is the Efficient Market Hypothesis? [Video]. YouTube. https://www.youtube.com/watch?v=AEv9AszJ4_U
  3. Corporate Finance Institute. (2019, July 24). Efficient markets hypothesis – Understanding and testing EMHhttps://corporatefinanceinstitute.com/resources/knowledge/trading-investing/efficient-markets-hypothesis/
  4. Maverick, J. B. (2020, September 30). The weak, strong, and semi-strong efficient market hypotheses. Investopedia. https://www.investopedia.com/ask/answers/032615/what-are-differences-between-weak-strong-and-semistrong-versions-efficient-market-hypothesis.asp
  5. Reinicke, C. (2020, March 23). Zoom video has seen its stock spike more than 100% since January as coronavirus pushes millions to work from home (ZM). Business Insider. https://markets.businessinsider.com/news/stocks/zoom-stock-price-surged-coronavirus-pandemic-video-work-from-home-2020-3-1029023594
  6. Segal, T. (2020, May 14). Fundamental Analysis. Investopedia. https://www.investopedia.com/terms/f/fundamentalanalysis.asp
  7. Chen, J. (2020, May 17). Guide to Technical Analysis. Investopedia. https://www.investopedia.com/terms/t/technical-analysis-of-stocks-and-trends.asp
  8. Smith, T. (2019, June 25). Random Walk Theory. Investopedia. https://www.investopedia.com/terms/r/randomwalktheory.asp
  9. Kenton, W. (2020, August 18). Bubble. Investopedia. https://www.investopedia.com/terms/b/bubble.asp
  10. Jones, S. L., & Netter, J. M. (n.d.). Efficient Capital Markets. The Library of Economics and Liberty. https://www.econlib.org/library/Enc/EfficientCapitalMarkets.html
  11. Kako, P. (2017, August 17). Law and Economics of Financial Deregulation. Michigan Business & Entrepreneurial Law Review. https://mbelr.org/law-and-economics-of-financial-deregulation/
  12. Downey, L. (2020, October 30). Efficient Market Hypothesis (EMH). Investopedia. https://www.investopedia.com/terms/e/efficientmarkethypothesis.asp
  13. Hayes, A. (2020, September 29). Neglected Firm Effect. Investopedia. https://www.investopedia.com/terms/n/neglectedfirm.asp
  14. Ribstein, L. (2009, December 11). Sorry, Folks: The Efficient Market Hypothesis Did Not Cause The Financial Crisis. Business Insider. https://www.businessinsider.com/sorry-folks-the-efficient-market-hypothesis-did-not-cause-the-financial-crisis-2009-12
  15. Carlson, B. (2020, May 11). Does COVID-19 prove the stock market is inefficient? A Wealth of Common Sense. https://awealthofcommonsense.com/2020/05/does-covid-19-prove-the-stock-market-is-inefficient/

About the Authors

Dan Pilat's portrait

Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

Sekoul Krastev's portrait

Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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