Random Walk Theory: Definition, How It’s Used, and Example

What Is Random Walk Theory?

Random walk theory suggests that changes in asset prices are random. This means that stock prices move unpredictably, so that past prices cannot be used to accurately predict future prices. Random walk theory also implies that the stock market is efficient and reflects all available information.

A random walk challenges the idea that traders can time the market or use technical analysis to identify and profit from patterns or trends in stock prices. Random walk has been criticized by some traders and analysts who believe that stock prices can be predicted using various methods, like technical analysis.

Understanding Random Walk Theory

Economists had long argued that asset prices were essentially random and unpredictable—and that past price action had little or no influence on future changes. This, indeed, was a key assumption of the efficient market hypothesis (EMH). Random walk theory is based on the idea that stock prices reflect all available information and adjust quickly to new information, making it impossible to act on it.

Economist Burton Malkiel’s theory aligns with the semi-strong efficient hypothesis, which also argues that it is impossible to consistently outperform the market. The theory thus has important implications for investors, suggesting that buying and holding a diversified portfolio may be the best long-term investment strategy.

Random walk theory was popularized by Malkiel in his 1973 book, A Random Walk Down Wall Street. In the book, Malkiel argues that trying to time or beat the market, or using fundamental or technical analysis to predict stock prices, is a waste of time and can lead to underperformance. Instead, he claims that investors are better off buying and holding a broad index fund.

While random walk theory has been met with critics who believe that there are, in fact, ways to predict stock prices and outperform using various techniques, it remains a widely accepted theory in the world of financial economics. By accepting that stock prices are unpredictable and efficient, investors can focus on long-term planning and avoid making rash decisions based on short-term market movements. Ultimately, random walk theory reminds investors of the importance of remaining disciplined, patient, and focused on their long-term investment goals.

Criticisms of Random Walk Theory

The main criticism of random walk theory is that it oversimplifies the complexity of financial markets, ignoring the impact of market participants’ behavior and actions on prices and outcomes. Prices can also be influenced by nonrandom factors, such as changes in interest rates or government regulations, or less ethical practices like insider trading and market manipulation.

Market technicians argue that historical patterns and trends can, in fact, provide useful information about future prices, challenging the theory’s assertion that past prices are not informative. They claim that technical analysis can intuit market psychology to identify. Other investors have also challenged the theory by pointing to examples of successful stock pickers, such as Warren Buffett, who have consistently outperformed the market over long periods of time by looking closely at company fundamentals. 

Another critique is that a random walk implicitly assumes that all investors have the same information, when in reality, some investors have access to more and better information than others (such as large, institutional investors). Indeed, information asymmetries have been found in real-world markets that cause markets to be inefficient.

One key critic was Benoit Mandelbrot, a mathematician who argued that stock prices are not random and do not follow a normal distribution, which are key assumptions of random walks. He observed that stock prices exhibit long-term dependence and are better modeled by fractal geometry, where investors should consider the risks associated with extreme black swan events. These ideas were influential in the development of the field of chaos theory in finance.

Dow Theory: A Nonrandom Walk

One competing theory to a random walk is known as Dow Theory. Dow Theory is made up of several tenets, which include the idea that stock prices move in trends, that these trends have distinct phases (accumulation, markup, and distribution), and that volume is an important indicator of the strength of a trend. Developed by Charles Dow, the founder of Dow Jones & Co. and The Wall Street Journal in the late 19th century, his theory is based on the idea that stock prices can be analyzed to predict future movements based on current trends.

Dow Theory is generally at odds with random walk theory, which claims that stock prices are unpredictable and that investors cannot consistently outperform the market. Dow Theory does not dispute the fact that stock prices are subject to random fluctuations in the short term, but it argues that long-run prices do reflect underlying economic trends and that these trends can be identified through technical analysis.

Random Walk Theory in Action

A historical example of random walk theory in practice occurred in 1988, when The Wall Street Journal sought to test Malkiel’s theory by creating the annual Wall Street Journal Dartboard Contest, pitting professional investors against darts for stock-picking supremacy. Journal staff members played the role of the dart-throwing monkeys.

After more than 140 contests, the Journal presented the results, which showed the experts won 87 of the contests and the dart throwers won 55. However, the experts were only able to beat the Dow Jones Industrial Average (DJIA) in 76 contests. Malkiel commented that the experts’ picks benefited from the publicity jump in the price of a stock that tends to occur when stock experts make a recommendation. Passive management proponents contend that, because the experts could only beat the market half the time, investors would be better off investing in a passive fund that charges far lower management fees.

The Bottom Line

Random walk theory claims that stock prices move randomly and are not influenced by their history. Because of this, it is impossible to use past price action or fundamental analysis to predict future trends or price action. If markets are indeed random, then markets are efficient, reflecting all available information.

The theory remains popular among economists; however, it has been criticized by technical and fundamental traders alike for being overly simplistic and discounting real-world outperformance achieved by some traders.