All investing is subject to risk, including possible loss of principal. Be aware that fluctuations in the financial markets and other factors may cause declines in the value of your account. There is no guarantee that any particular asset allocation or mix of funds will meet your investment objectives or provide you with a given level of income. Prices of mid- and small-cap stocks often fluctuate more than those of large-company stocks. Investments in stocks or bonds issued by non-U.S. companies are subject to risks including country/regional risk and currency risk. These risks are especially high in emerging markets.

Counterpoint’s investment process incorporates quantitative artificial intelligence models, including machine learning techniques, which are subject to risks inherent in any data-driven approach. The effectiveness of these models depends on the accuracy, quality, relevance, and interpretation of underlying data and assumptions, and there is a risk that models may produce inaccurate assessments, become less effective due to changing market conditions, or fail to perform as expected. Rapidly evolving or unforeseen market environments may reduce the predictive value of model outputs and adversely affect investment decisions and portfolio performance. To help mitigate these risks, Counterpoint maintains rigorous research, testing, monitoring, and oversight processes designed to address potential issues such as algorithmic bias, overfitting, technical errors, and systemic model limitations. Counterpoint’s investment professionals supervise machine learning outputs and continuously evaluate model effectiveness, while monitoring developments in the regulatory landscape to support compliance with applicable laws, regulations, and industry best practices. However, no assurance can be given that the models or investment strategies will be successful under all market conditions.

The Counterpoint Machine Learning Model uses machine learning technology to rank stocks of companies 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.

The Counterpoint Risk & Return-Optimized Model Portfolios are provided for illustrative and educational purposes only. The Counterpoint model portfolios do not constitute research, are not personalized investment advice or an investment recommendation from Counterpoint to any client of a third party financial professional and are intended for use only by a third party financial professional, with other information, as a resource to help build a portfolio or as an input in the development of investment advice for its own clients. Such financial professionals are responsible for making their own independent judgment as to how to use the Counterpoint model portfolios.