Decision trees at work

MDT’s investment process uses decision trees to help separate signal from noise in stock selection. Rather than relying on one factor, the model adapts to each company and looks for combinations of valuation, profitability, financing, and analyst sentiment that have historically pointed to stronger returns.

This approach can uncover relationships that are easy to miss in traditional models. It also helps the team assess how different characteristics interact across growth and value names.

The opportunity is a more flexible and repeatable way to identify potential alpha across changing market conditions. The main risk is that past patterns may not always hold if market regimes shift or investor behavior changes.