Swedroe: The Truth About Stock Prices

November 08, 2016

In the last few weeks, I’ve unpacked studies addressing both the nominal price illusion and the nominal price premium. So today I’ll answer a related question: Do nominal stock prices really matter?

Because the level of a company’s stock price is arbitrary—it can be manipulated, for example, by firms via adjustments in the number of shares outstanding—if markets were fully efficient, nominal stock prices should be randomly chosen by firms. However, until just recently, the average nominal price of U.S. stocks had remained around $30 over the last several decades.

Why has this been the case? The academic literature provides the answer: Firms are well aware that individual investors are influenced by nominal prices. This leads them to adopt a higher allocation to lower-priced stocks than institutions.

The preference for low-priced stocks is illustrated through findings that individual investors increase their holdings after a split to lower a stock’s price level. Academic research has sought to provide explanations for this anomalous behavior (meaning that it’s irrational from an economic perspective).

One explanation is that individuals are looking for a cheap bet, as with lottery tickets. Therefore, they find lower-priced stocks attractive. Another is that investors might perceive low-priced stocks as being closer to zero and farther away from infinity. They thus have more upside potential and less to lose (of course, no matter how low the price is, you can always lose 100% of the investment). Both of these explanations are supported by research.

Price Matters
Vijay Singal and Jitendra Tayal, authors of the July 2015 paper “Nominal Stock Prices Matter,” contribute to the literature on the nominal price effect by segregating the size (a small company could have a low stock price, but that isn’t necessarily the case because it could also have a small number of shares outstanding) and price effects, then examining the relationship between nominal prices and returns by explicitly controlling for size.

To ensure their results were not driven by small, economically insignificant firms, they formed portfolios by choosing the largest 3,000 companies using Center for Research in Security Prices data from December 1962 to December 2013. These firms were then categorized into size deciles, followed by price deciles within each of the size deciles. Following is a summary of the authors’ findings:


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