Why Stock Prices Move

Stock prices move up and down but much of their movement is difficult to explain. We often see headlines explaining that changes in the price of oil or the Japanese yen affected stock prices but that seems unlikely to be the real reason the price of a company that sells sports collectibles in California, for example, moves up or down 3% in a day. In addition to headlines, there are a couple of academic theories about why stock prices move. The Efficient Market Hypothesis (EMH) is probably the most popular academic theory but a new theory, the Adaptive Market Hypothesis (AMH), may do a better job explaining why markets move.

In general terms, the EMH tells us that the current price of a stock fully reflects all available information about that company because markets aggregate information efficiently. This means investors, as a group, know everything that is possible to know about a company and they price the stock, as a group, based on that information. Under this theory, the stock price then reflects the net present value of all future cash flows. No one person can accurately forecast those cash flows but as a group, all traders acting together are capable of this.

In specific terms, the EMH is based on the assumption that individual investors form rational expectations about the future prospects of a company and they make buy and sell decisions based on these expectations. Markets aggregate all of this information into the current price of the stock. Whenever new information comes into the market, traders instantly incorporate that information into the stock price. This explains why prices can move a large amount after an earnings report. The stock’s move shows the process of new information being efficiently incorporated into the price.


Under the weak form of the hypothesis, fundamental analysis of financial statements can help an investor beat the market. Changes in the price of a stock are random so studying stock charts won’t provide useful information. But the financial statements may show trends or factors that are difficult to spot. Investors who successfully spot unusual information in the financial statements can beat the market. Warren Buffett is an example of the successful investor under this form of the theory but few others will be able to duplicate his success.

The semi-strong form of the EMH goes one step further and says current market prices reflect all publicly available information and the current price is always the “best estimate” of the value of the company. With this assumption, neither technical analysis nor fundamental analysis can be used to generate excess returns. The only way to beat the market is to trade on inside information.

The strong form of the EMH says even inside information won’t be enough to beat the market. Under this theory, current prices accurately summarize all information, private as well as public.


Defenders of the EMH go to great lengths to prove their theory. Of course there are some examples of investment managers who have outperformed the market in the long run but this doesn’t disprove the EMH, according to proponents, because their success is due to chance. They argue that with thousands of managers actively trying to beat the market, the existence of a few successful ones is expected if we assume that the returns of all those managers follows a normal distribution.

This idea has been studied by a number of researchers. The general conclusion is that there are some ways to beat the market. For example, value stocks tend to outperform growth stocks in the long run. Small cap stocks generally deliver larger gains than large caps. Momentum tends to continue and buying stocks with high momentum tends to outperform the market over time periods ranging from three to twelve months. These are considered exceptions to the EMH and are named the value anomaly, the size anomaly and the momentum anomaly. In other words, the EMH, which dates back to the 1960s, works except for these anomalies.

In more recent years, a researcher with the Massachusetts Institute of Technology has come up with an alternative way of looking at market moves. Dr. Andrew Lo has developed the Adaptive Market Hypothesis (AMH). Lo takes a biological, rather than physical, view of the markets. This theory assumes:

  • Individuals act in their own self-interest
  • Individuals make mistakes
  • Individuals learn from their mistakes and adapt
  • Competition drives adaptation and innovation
  • Natural selection shapes market ecology
  • Evolution determines market dynamics

This theory fits what we see in the markets more than the EMH. Think of how you approach the markets. For most is, the EMH is simply a theory while the AMH describes our actions.


Under the EMH, before buying a stock we would complete a rational and detailed analysis. We would review financial statements and develop assumptions about economic growth and the future prospects of the company. We would then model the future performance of the company, estimating future sales and expenses. We would need to make assumptions about the company’s operations to assess whether they will be issuing bonds or borrowing money to fund expansion or possibly to fund share buybacks because assumptions about the number of outstanding shares in the future would be needed. With all these assumptions we would build a discounted cash flow model requiring more assumptions about interest rates in the future and risk premiums assigned to different kinds of stocks. This model would give us the fair value of the stock and we would then compare that value to the current market price. If the expected returns from the stock deliver our required rate of return (a value derived from yet another model), the stock is a buy.

Remember that under the strong form of the EMH prices are perfectly efficient. This means after doing all that analysis there would be nothing to buy because the market price would always reflect the stock’s fair value.

Under the AMH, investors are basically battling with each other for gains. Every trader in a stock has an opinion that the price will go up or down. That opinion is likely based on heuristics, or problem-solving techniques in which the best solution is selected using rules that are based on rules of thumb or experience. Sometimes, the trade will go against us and we adapt to the mistake we made by closing the trade. Hopefully we learn from the mistake and change our heuristics based on experience. This sounds like how many of us actually invest and trade.

While the AMH seems to make the most sense, there is valuable information in both theories. The anomalies to the EMH provide us with general rules for success. Value investing can help us beat the market. As academics would say, we are analyzing stocks in an effort to exploit the value anomaly. Small caps tend to be less widely followed by analysts and offer more opportunities for us, as individual investors, to find information large investors might have missed. In the words of academics, small caps are less efficient and offer greater rewards because the risks are less well understood. Individual investors can manage the risks by using stop losses or other risk management strategies. The momentum anomaly can help us decide which undervalued stocks to buy. High momentum shows other investors are buying the stock and helps us avoid value traps where undervalued stocks remain undervalued for years.

The AMH emphasizes the importance of learning from mistakes. This is perhaps the most important lesson for investors because mistakes are inevitable.  Stock prices move because some investors are learning from past mistakes and selling while other investors are making the mistake of undervaluing the stock and selling too soon. Because every investor has a different time frame and different objectives, buying and selling will continue to push prices up and down.