Quantitative Stock Selection: Practical Insights Campbell R. Harvey Duke University National Bureau of Economic Research

Practical Insights 1.Factors are often viewed in terms of a continuous distribution. We standardize the factor by subtracting the cross- sectional mean and dividing by the cross-sectional standard deviation. 2.A simple equally weighted scoring system would add up these standardized values. Sorting by the sum is the scoring screen.

Practical Insights 3. The ability of factors to separate good and bad performance is probably sector specific. It is important to run sector based univariate screens. 4. In implementing a scoring screen with sector differences, it is probably not practical to have different factor scores for each sector. Best to flag the sectors where the factor works well (or works very poorly). The scoring screen will take that information into account.

Practical Insights 5. It is important to evaluate not just the historical consistency of your screens but to understand the fundamental economic determinants of historical performance. This involves looking at the month by month and correlating with the macro financial environment.

Practical Insights 6. Attribution analysis is also important. This involves a regression of portfolio returns on a set of known styles, i.e. value, growth, etc. You can determine how much of fund performance came from each source. The regression usually uses 12 months of data and about 4 or five style factors. Note: if you know the scoring weights then you already know your portfolio’s tilt. However, if we are evaluating someone, the attribution analysis is crucial.

Practical Insights 7. There is another optimization after the scoring screen optimization (which gives optimal scores for each factor). 8. Given each stock’s score, an optimization is run which maximizes the total score (for longs) but includes a number of practical constraints (such as the must but stocks, caps and floors on sector weights, caps and floors on style exposure).