PT  - JOURNAL ARTICLE
AU  - Eric H. Sorensen
AU  - Keith L. Miller
AU  - Chee K. Ooi
TI  - The Decision Tree Approach to Stock Selection
AID  - 10.3905/jpm.2000.319781
DP  - 2000 Oct 31
TA  - The Journal of Portfolio Management
PG  - 42--52
VI  - 27
IP  - 1
4099  - https://pm-research.com/content/27/1/42.short
4100  - https://pm-research.com/content/27/1/42.full
AB  - A frequent question regarding quantitative investing is: What are good variables for stock selection? Traditional quantitative strategies are variations of screening techniques. Quantitative investment managers seek to narrow the investable universe to a manageable number of stocks that have desirable characteristics. The authors introduce an alternative approach to traditional methods of stock screening based on a statistical technique known as classification and regression tree (CART). CART allows screening factors to interact on a conditional basis. The end result is a hierarchical (tree) structure that assigns a probability of outperformance (or underperformance) for each stock. The authors apply two alternative CART strategies to the selection of technology stocks, and evaluate their performance. The models demonstrate significant improvement over the more ad hoc stock ranking techniques.