This book explores various popular factors that investors use to try to capture a premium on their investments. In the past, successful investors were considered to be skilled at picking stocks. While this was true, current computing power allows for a reverse engineering of their strategies, uncovering the common characteristics of stocks picked by good investors. These characteristics are now called factors, and investors can gain exposure to factors using quantitative methods. Many funds follow factors, so investors can get low-cost, passive exposure to various factors. One of the appendices in this book gives a list of such funds. Diversifying across multiple factors may be even more effective than asset class diversification. Recent academic research has led to an explosion of factors. Swedroe and Berkin try to narrow down this list, narrowing the “factor zoo” from six hundred purported factors to eight usable ones.
The book uses five criteria to determine whether a factor is useful. Of course, the factor needs to produce excess returns. Additionally, it needs to be persistent, meaning the excess returns are relatively steady over time and not limited to a one-time surge. It needs to be pervasive, working across different geographies and asset classes. It needs to be robust, meaning the results aren’t based on a narrow definition of the factor. (This would be a sign of data snooping.) It needs to be investable, meaning it can work in practice, not just in theory. (Here is where some factors that are dependent on thinly traded microcaps fail.) Finally, it needs to be intuitive. There must be a logical reason for why the factor works. If a factor passes all these tests, we can be confident it truly worked to deliver outsized returns. Before an investor decides to include the factor in his portfolio, he should also consider whether anything has changed that could affect the factor going forward, and whether the factor’s performance is picked up by another factor, making it redundant.
The eight factors endorsed by Swedroe and Berkin are: market beta, size, value, momentum, profitability, quality, term and carry. There is a table that shows average return for the various factors, along with standard deviation and Sharpe ratio (a measure of return adjusted for risk.) Market beta means having exposure to the risk of the overall market. Size means that smaller stocks have historically earned a higher return than large stocks. Value means that stocks that sell for a cheaper price relative to underlying fundamentals have historically done better than more expensive stocks. Momentum means that investments that are trending in the short-term tend to continue their trends for a while. Profitability and quality are related, and are covered in the same chapter. Profitability is measured by gross profit divided by assets. Stocks that generate more profit per dollar of assets have shown greater returns than the low profit stocks. Profitability is measured looking backwards, so there is no look-ahead bias here. Quality looks at profitability plus other measures, so it is really is an expansion of the profitability factor, rather than a separate factor. Term applies to credit instruments. Longer-term bonds earn more than short-term bonds on average, which makes sense because they have greater interest rate risk. Carry is usually applied to currency, but the factor works across asset classes. Theoretically, something with a higher current yield should have an offsetting lower appreciation rate, but this hasn’t worked to offset all of the higher yield, leaving excess returns for carry. Two popular investment strategies the authors reject as useful factors are dividends and low-volatilty. Both of these have generated excess returns, but this return is captured by other factors (mostly value), so they are not additive.
The book asks whether risk premia have shrunk since they have been discovered. The answer is yes, somewhat, but the premia still exist. The book also looks at ways to combine factors, and suggests that rather than just trying to increase returns, investors can think of each factor as a way to earn an independent return, which then allows a reduction in market beta risk.
My take: This is an excellent book, exploring each of the factors and evaluating them according to the factor tests. It looks at both behavioral-based explanations as well as risk-based explanations for the factors working. The conclusion is the factors generally work due to both behavioral and risk-based reasons, but taking on risk should not dissuade an investor from exposure to a factor. Since the risks are compensated, they provide more sources of return and thus more diversification. I do have a couple of quibbles with the book. First, the factor premia are calculated on a long-short portfolio, where stocks (or bonds) with the highest factor exposure are held and securities with the lowest factor exposure are shorted. This makes sense from an academic perspective, but is not always investable by average investors, who mostly do not short. A factor could look very good because of the negative exposure to the worst stocks. Second, a greater focus on the interaction of factors would have been helpful. This was touched on, but deserves more focus. For instance, while the small cap factor in general is fairly weak, when combined with value, it gets stronger. Quality has worked on average, because investors have underappreciated the persistence of quality on average. Glamor stocks, however, are often quality stocks with valuations that overestimate the persistence of quality. The quality factor may be much stronger when paired with value. Finally, I take issue with market beta as a factor in the same sense the other criteria are factors. While the market risk premium is well established (stocks earn more than bonds), higher beta stocks do not necessarily outperform low beta stocks in a linear manner. I agree that taking risks in stocks earns a return over time, but if beta were a factor in the same sense as the others, high beta (riskier) stocks should outperform low beta (defensive) stocks in a linear fashion. This is the basis of the Capital Asset Pricing Model (CAPM), but it has not played out empirically. These are minor issues. The book shows why investors should carefully consider including factor exposure in their portfolios.