Revisiting CAPM in Egypt: A Fama–MacBeth Analysis of Beta, Nonlinearity, and Idiosyncratic Risk

Investors have long searched for a reliable compass to navigate the turbulent waters of the stock market. They want to know which risks will be rewarded with higher profits and which will simply lead to losses. For decades, the most popular map for this journey has been a theory called the Capital Asset Pricing Model. This idea suggests a simple, straight-line relationship: the more a stock moves in sync with the overall market, the more return an investor should expect. In this view, the only risk that matters is the risk you cannot escape by spreading your money around, known as systematic risk. If you hold a well-diversized portfolio, the unique problems of any single company should not cost you anything, because you can simply buy shares in other companies to cancel them out. This theory has guided billions of dollars in investment decisions, from pension funds to individual savings accounts, because it promises a clear rule for pricing risk.

However, the real world is rarely as neat as a straight line. Markets are messy, influenced by human emotion, sudden shocks, and complex local conditions. Researchers have long wondered if this simple map still holds true in places where markets behave differently than in the developed West. Egypt, with its unique economic history and rapid changes, offers a perfect place to test these old rules. A recent study by researchers Mohammad Abuamsha and Osama Sallam set out to revisit this classic theory on the Egyptian Stock Exchange. They wanted to see if the old rules still applied, or if the relationship between risk and reward in Egypt was more complicated, perhaps curved or influenced by factors the original theory ignored.

The researchers gathered a massive amount of data, looking at the weekly performance of over a hundred Egyptian companies every year for a decade, from 2015 to 2024. This span covered more than 1,300 individual snapshots of company performance, allowing them to see patterns that shorter studies might miss. They used a rigorous two-step method to analyze the data. First, they measured how much each company's stock moved in relation to the broader market index, the EGX30, to determine its sensitivity to market swings. Then, they checked if that sensitivity actually predicted how much money the stock made in the following year. They also looked for hidden complexities, such as whether the relationship between risk and return was actually a curve rather than a straight line, and whether the specific, unique risks of a company—risks that should theoretically be ignored by smart investors—were actually being priced into the stock.

In their initial, simplest test, the results seemed to support the old theory. The data showed a positive link: stocks that moved more with the market tended to have higher returns. This suggested that investors were indeed being paid for taking on market risk. However, a closer look revealed a persistent problem. The model consistently predicted a baseline return that did not match reality, indicating that the market was mispricing stocks in a way the simple theory could not explain. It was as if the map showed a straight path, but the terrain was actually full of unexpected dips and rises that the map failed to capture.

When the researchers added more detail to their analysis, the picture changed dramatically. They introduced a test for nonlinearity, checking if the relationship between risk and return curved, and they included a measure of the unique, company-specific volatility. Once these factors were included, the simple, positive link between market risk and returns disappeared. Instead, the data showed that the more sensitive a stock was to the market, the lower its returns tended to be. Furthermore, the unique risks of individual companies were not being ignored by the market; they were actually being priced, meaning investors were demanding compensation for risks that the old theory said should be diversifiable. The study found that the relationship between risk and reward in Egypt is not a straight line, but a complex curve where the usual rules of thumb break down.

The researchers also tested how robust these findings were by changing the way they measured time and returns. They looked at daily data, monthly data, and different ways of calculating annual profits. They even removed the years affected by the global pandemic to see if the results were just a reaction to that specific crisis. In almost every variation, the simple, straight-line theory failed to hold up. The results were sensitive to how the data was handled, but the core finding remained: the classic model does not work mechanically in Egypt. The market does not reward risk in the simple, predictable way the theory promises.

This study concludes that while the concept of market risk is still relevant, the Capital Asset Pricing Model cannot be used as a standalone tool for valuing stocks in Egypt. The relationship between risk and return is conditional, shaped by nonlinear factors and specific company risks that the old model ignores. For investors and financial planners, this means that relying on a single, static formula is dangerous. Instead, they must look at a broader set of conditions, understanding that in this market, the path to returns is not a straight line, and the risks that can be diversified away are not as easily ignored as once thought. The old map is not entirely useless, but it is incomplete, and navigating the Egyptian market requires a more nuanced, flexible approach.