Strategy. Under normal market conditions, the Fund invests at least 80% of its assets (plus the amount of borrowings, if any) in long and short positions in equity instruments of any market capitalization. Equity instruments include domestic and foreign common stock, preferred stock, depositary receipts, equity swaps (including single-name, index, and basket swaps), options, equity index futures, and other investment companies (such as exchange traded funds (?ETFs?), mutual funds, and closed-end funds) that invest in these types of securities. The Fund may hedge exposure to foreign currencies using foreign currency forwards or futures. The Fund does not focus its investments in any country or geographic location and may be fully invested in equity instruments. In managing the Fund, the Fund?s adviser, … Show more… Under normal market conditions, the Fund invests at least 80% of its assets (plus the amount of borrowings, if any) in long and short positions in equity instruments of any market capitalization. Equity instruments include domestic and foreign common stock, preferred stock, depositary receipts, equity swaps (including single-name, index, and basket swaps), options, equity index futures, and other investment companies (such as exchange traded funds (?ETFs?), mutual funds, and closed-end funds) that invest in these types of securities. The Fund may hedge exposure to foreign currencies using foreign currency forwards or futures. The Fund does not focus its investments in any country or geographic location and may be fully invested in equity instruments. In managing the Fund, the Fund?s adviser, Counterpoint Funds, LLC (the ?Adviser?), employs a strategy that generates returns from two sources: (1) stock selection and (2) tactical market exposure. Stock Selection. The Adviser selects stocks on which to go long and short based on results from the Counterpoint Machine Learning Model . The 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 Fund seeks to target the best performing, recent, and persistent anomalies and may invest in stocks that provide exposure to and capitalize on a wide variety of anomalies at any one time. An investment anomaly refers to a situation when a security or group of securities performs contrary to the notion of efficient markets, which states that security prices reflect all available information at any point in time. Published papers in academic finance journals have identified more than one hundred investment anomalies. The asset growth anomaly, for example, is that companies that aggressively spend capital have worse average stock performance than companies that are more conservative in their capital expenditures. Perfect market efficiency would not yield any market outperformance from investment decisions based on publicly available accounting data such as this. The Adviser may adjust its model to include newer and more effective anomalies and pare down exposure to older underperforming anomalies on a regular basis. The signals from these models indicate which stocks are undervalued and likely to increase in price and which stocks are overvalued and likely to decrease in price. 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 Adviser takes long positions in undervalued securities and short positions in overvalued securities. Tactical Market Exposure. The Adviser varies the Fund?s equity exposure using a tactical, proprietary model of market returns. When the tactical model forecasts lower market returns, the Fund targets a market-neutral (zero beta) allocation to stocks with a gross equity exposure (long positions plus short positions) of at least 80%. Beta is a measure of the volatility, or systematic risk, of a security or a portfolio in comparison to the market as a whole. Beta is assigned a number. A beta of 1 indicates that the security?s price moves with the market. A beta of less than 1 means that the security is theoretically less volatile than the market. A beta of greater than 1 indicates that the security?s price is theoretically more volatile than the market. The remaining 0-20% of the total portfolio assets are invested either directly, or indirectly through ETFs, mutual funds, or derivatives, in U.S. treasury instruments and investment grade debt. When the model forecasts higher market returns, the Adviser selects a blend of equity index futures, equity index ETFs, and/or equity index swaps based on various factors (liquidity, tracking error, and cost) to achieve exposure to the equity markets with a beta between 0.8 and 0.85. The Fund?s adjustments of its holdings may lead to high portfolio turnover. Show less