RT Journal Article
SR Electronic
T1 The Decision Tree Approach to Stock Selection
JF The Journal of Portfolio Management
FD Institutional Investor Journals
SP 42
OP 52
DO 10.3905/jpm.2000.319781
VO 27
IS 1
A1 Eric H. Sorensen
A1 Keith L. Miller
A1 Chee K. Ooi
YR 2000
UL https://pm-research.com/content/27/1/42.abstract
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.