Strategy. The Adviser actively manages the Fund?s portfolio by using a quantitative, model-based approach to security selection. Under normal market circumstances, the Fund invests at least 80% of its assets (plus the amount of borrowings, if any) in common stocks and American Depositary Receipts (?ADRs?). The Fund holds at least 50 U.S. listed stocks or American Depository Receipts (?ADRs?). The stocks selected are among the highest-ranking stocks as determined by quantitative models. The quantitative approach uses results from the Counterpoint Machine Learning Model to rank stocks of U.S. domiciled companies and ADRs of any market capitalization. Machine learning is a type of artificial intelligence (?A.I.?) that finds relationships between variables and outcomes, and uncovers interactions between multiple variables. The Fund?s models … Show more… The Adviser actively manages the Fund?s portfolio by using a quantitative, model-based approach to security selection. Under normal market circumstances, the Fund invests at least 80% of its assets (plus the amount of borrowings, if any) in common stocks and American Depositary Receipts (?ADRs?). The Fund holds at least 50 U.S. listed stocks or American Depository Receipts (?ADRs?). The stocks selected are among the highest-ranking stocks as determined by quantitative models. The quantitative approach uses results from the Counterpoint Machine Learning Model to rank stocks of U.S. domiciled companies and ADRs of any market capitalization. Machine learning is a type of artificial intelligence (?A.I.?) that finds relationships between variables and outcomes, and uncovers interactions between multiple variables. The Fund?s models use over 40 variables as inputs. These variables revolve around themes of value, long-term reversal, stock price momentum, company profitability, investor sentiment toward the company, and stock price stability. If the Adviser?s research indicates that a specific combination of variables would have improved the accuracy of the model?s predictions, then the Adviser will use that combination of variables going forward if supported by economic reasons and/or investor behavioral biases. The models use these variables and identify generalized relationships between historic realized stock returns and the values of those variables. The learned relationship between the input variables and the realized historic returns is updated between portfolio rebalances, allowing the models to adjust to changing market conditions. The models rank the stocks based on their expected future performance. At least every quarter, the Adviser rebalances the portfolio based on the stocks? current rankings. The Adviser adjusts the output from the model to limit the maximum exposure to any one sector to 35% or less of the Fund?s net assets. The Fund will not invest more than 25% of its net assets in any one industry or group of industries within a sector. Show less