Factors
Kerry Back
- Groups of stocks with certain characteristics seem to have higher expected returns.
- These stocks also usually tend to move together.
- Maybe they are exposed to some risk that some investors regard as undesirable.
- Maybe you want to take on that risk to get the return.
- The return of the group of stocks is called a factor.
- Investing in the factor means you will be correlated with the factor.
- So, if we regress your return on the factor, you will have a positive slope coefficient (beta).
- Hence the name “smart beta.”
- Example: Fama-French factors: Small Minus Big, High book-to-market Minus Low book-to-market, Conservative Minus Agressive, Robust Minus Weak.
- The “exposed to some risk” story is a way to reconcile factor investing with the efficient markets hypothesis.
- It is also possible that stocks are just mispriced in systematic ways.
- For example, there is evidence that analysts recognize that “quality” stocks are worth more than “junk” stocks, but they underestimate how much more.
Industry examples
Some data 
- Sort into quintiles each month.
- Value weighted return of each group
- Re-sort at the beginning of the next period and continue.
Factor investing with machine learning
- Find factors worth investing in.
- Decide how to optimally combine them.
- Using ML, we can in principle throw in lots of characteristics and let the machine decide which are useful, but preprocessing is usually useful.
- Need to backtest, which is a variation of the usual ML train-and-test.
- Gu, Kelly, and Xiu, 2020
Factors Kerry Back