The Polaris stock-selection guidance system, is based on an innovative multi-factor model where the focus is on performance. The model utilizes proprietary metrics and includes a machine learning algorithm that performs investor behavior pattern recognition. The objective is to provide portfolio managers and analysts with independent, unbiased insight that leads to benchmark outperformance.
As a means of providing accountability to our clients, we routinely update the charts and tables herein to report the historical performance of top-ranked stocks in our model in comparison to bottom-ranked stocks. While past results do not guarantee future results, our comprehensive back-testing reveals that investors who trafficked in our top-ranked stocks would have very likely outperformed their benchmarks consistently.