High risk, high returns?
It is a common saying that high risk is associated with high returns. However, what kind of risk should investors take to be systematic in their investment? As discussed in our first article, investment choices that have long-term return predictability and economic basis are the two characteristics of systematic investing. One such risk is aptly named systematic risk, which is also known as the market risk premium (or factor). Since it was discovered in the 1960s independently by four researchers1, the capital asset pricing model (CAPM is the formal model for market risk) has been the main explanatory factor for stock returns.
It has been estimated that CAPM can explain around 70% of cross-sectional stock returns (distribution of returns across all stocks) over the long term. What this means is that a large part of the return of a stock can be explained by the proportion of market risk factor the stock has. One has to take note that systematic risk factors are true for most of the time when the portfolio is held over a long period (so that the law of large numbers can kick in).
William Sharpe, who has the entire fund management industry chasing for him (the Sharpe ratio)
Why have one when you can have three?
In 1993, Eugene Fama and Kenneth French added two additional factors2 to explain cross-sectional returns further. They observed that firms with smaller market capitalisation outperformed their larger counterparts when it comes to stock returns. They also observed that high book-value-to-market-value firms (also known as value stocks) outperformed those with low book-value-to-market-value companies (also known as growth stocks).
They constructed the two risk factors by buying (or longing) the companies in the group that outperform while selling (or shorting) those that are in the group that under perform. They termed the first long-short risk factor as the Small-minus-Big (SMB) risk factor while the latter as the High-minus-Low (HML) risk factor. In their study, they found that including the market factor, their three-factor model explained about 90% of cross-sectional returns. Since then, this Fama-French three-factor model is the benchmark for most studies that attempt to price stocks.
Eugene Fama, the father of the Efficient Market Theory
Implementation versus theory
Factor-based investing is one of the most common methods used by fund managers to construct their investment portfolio. While the research field is interested in using risk factors to price assets, using the risk factors in actual stock selection is a little different, especially to the common investor. For many investors, they do not have tools to efficiently short stocks. Thus the most common method of factor-based investing involves a set of rules for selecting and filtering companies based on their attributes and historical price movement.
In the case of applying the Fama-French three-factor model, the investor is looking for value firms that have smaller market capitalisation than the median (or average) and is exposed to some amount of market risk. By doing that, the investor is exposed to the priced risk that is higher than the market (because he took more systematic priced risk than just the market risk) and thus should be rewarded with the market-beating return he so deserves. Other factors have been discovered and many others have not been discovered (and thus priced) yet. One must take note that not all factors give the same long-term sustainable return; they should be tested rigorously before deployed to actual use.
Still not sure what systematic investing is? Check out our introduction in part 1.
 Treynor (1961, 1962), Sharpe (1964), Lintner (1965a, b) and Mossin (1966) independently formulated CAPM, but it was Sharpe who won the Nobel Prize in Economics for it. His paper: Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The journal of finance, 19(3), 425-442.
 Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of financial economics, 33(1), 3-56.