Our stock screener comes with a set of popular composite factors out of the box such as the Greenblatt Magic Formula, ERP5, and the O'Shaughnessy Value Composite. By ranking on a combined score based on multiple factors, one can easily find stocks that rank relatively well on both factors. The Greenblatt Magic formula for instance ranks companies based on ROC and Earnings yield and then sums up the 2 ranks. It then ranks companies on the combined score. Companies with a bad ROC or Earnings Yield tend to drop to the bottom of the screener, so you're left with companies that score quite well on the 2 different ratios. As opposed to multifactor analysis, all factors get equal weight in the overall result.
But what if you want to use a different set of factors or just build a customized version with for instance an extra factor like price index 6M? This is now possible by using custom factors.
Click on the Custom Factors button to open the custom factors window. Click inside the factor 1 textbox and select a factor from the list. You can repeat this process and add as many factors as required. After selecting the factor, you can pick the calculation method. We support 2 calculation methods:
- Value: each factor will be ranked individually first. In a second step, the sum of the rakings is ranked again. Companies where one of the ratios is missing automatically get a bad score. Examples of factors that use this calculation method are the magic formula and ERP5.
- Percentile: Each factor will be used to create 100 buckets with the same number of stocks. (percentiles) Group 1 contains the best stocks, group 100 contains the worst. A company for which this ratio is missing will get be put in group 50. The sum of the percentiles of the different ratios is used to again create overall percentiles. Examples of factors that use this calculation method are O'Shaugnessy's VC1, VC2, and VC3.
We provide 2 custom factors that act just like any other column in the list. To display these custom factors, you use the display/hide column functionality. Custom factors can be used to sort the results in the grid, to set specific filters, to run multifactor analysis, etc...