Thanks for paper. They are using classifiers algorithms (ex. RandomForestClassifier) with total return targets:
| 12-month return Target variable | Target Variable |
|---|---|
| 𝑟𝑒𝑡𝑢𝑟𝑛 ≥ 0.15 | 4 |
| 0.05 ≤ 𝑟𝑒𝑡𝑢𝑟𝑛 < 0.15 | 3 |
| 0 ≤ 𝑟𝑒𝑡𝑢𝑟𝑛 < 0.05 | 2 |
| −0.15 ≤ 𝑟𝑒𝑡𝑢𝑟𝑛 < 0 | 1 |
| 𝑟𝑒𝑡𝑢𝑟𝑛 < −0.15 | 0 |
It's strange that they used total return. I tried using a total return target (although with a regressor since we have not added classifier at the moment) also with SP500 universe, and it completely destroys the High - Low bucket performance. The High bucket I guess still shows some performance, but I would not use total return targets.
Intuitively only relative performance targets make sense, whether you use classifiers or regressors. Thoughts?