Back in the early 1990s two finance professors, Eugene Fama and Ken French, published a paper that described the sources of returns in the stock market. They argued that only three factors accounted for the vast majority of a portfolio’s returns: exposure to the stock market itself, exposure to size (small-cap stocks vs. large-cap stocks), and style exposure (value stocks vs. growth stocks).
The paper opened up a debate that has raged lo these many years about why it is that small stocks and value added stocks outperform. There still is no single accepted answer, but it has been argued that higher risk profiles cause these stocks to generate stronger returns. Remember, the financial theory states that higher returns are only possible by accepting higher risk. Behavioral biases have also been cited as a possible reason for of the outperformance. Regardless of the reason, the outperformance of small stocks and value stocks is so pervasive in the historical data, both in the U.S. and abroad, that the inclusion of these types of stocks in portfolio construction is almost mandatory by competent practitioners. The ubiquity of the outperformance in most data series has ruled out data mining (see newsletter sidebar).
One of the failings of Fama and French’s work is that it did not take into account a fourth factor that has proven to be meaningful in explaining investment returns: momentum. Momentum is simply buying stocks that have been going up and avoiding stocks that have been going down. While this may sound basic, it was not documented until 1993 and has not really been accepted until much more recently.
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