UBC ALGORITHMIC FUNDAMENTALS ETF (UBCB) Exchange: NYSE ARCA

TheFund is actively managed by proprietary artificial intelligence (AI) algorithms. Under normal circumstances, the Fund investsat least 80% of its net assets (including borrowing for investment purposes) in large capitalization (“large cap”)companies listed on U.S. stock exchanges and markets, including common stocks, American Depositary Receipts (“ADRs”)and exchange-traded funds (“ETFs”) that provide exposure to large cap companies. The Adviser defines large cap equitysecurities as companies with market capitalizations of $10 billion or more, measured at the time of purchase. Innormal market conditions, the Adviser anticipates the Fund will hold 40-100 different positions across a broad spectrum ofindustries as dictated by its proprietary investment models. The Fund may take larger positions in certain companies and/orindustries as dictated by its proprietary investment models. The Fund operates as a “non-diversified” fund which meansit can invest in fewer securities at any one time than a diversified fund. The Fund’s systematic investment process is basedon rigorous back testing of proprietary and evolving data-driven strategies and is designed to allow the Fund to achieve attractiverisk-adjusted returns (i.e., returns made relative to the amount of risk taken). The Fund’s use of a systematicinvestment process does not guarantee that such risk-adjusted returns will be achieved. Inmaking investment decisions, the Adviser’s algorithms are trained to invest in profitable companies with predicted expandingfundamentals (i.e., companies demonstrating such things as improved cash flows and earnings per share, reasonable price-to-earningsratio, and improving price-to-earnings growth and dividend yield). In predicting fundamentals, the Adviser uses its proprietarymachine-learnings forecasting algorithms. The proprietary forecasting algorithms generate a wide range of short- to mid-term fundamentalpredictions for economic metrics, industries, and companies’ fundamentals (including financials and operating metrics) acrossmultiple sectors. These fundamental predictions are underpinned by a highly scalable proprietary backend system which processesfactual and market datasets available in the public domain. These datasets include historical financial statements, historicalprice action for companies, investor sentiment, and leading economic indicators, such as gross domestic product, purchasing manager’sindex and consumer purchasing index. The Fund’s portfolio will be actively managed and may have exposure to growth and/orvalue companies. The Adviser believes that by running multiple independent models it serves as a cross-check for the predictionsgenerated by the models. TheAdviser’s AI-driven algorithms actively identify opportunities and automatically invest, divest, and rebalance the Fund’sportfolio allocation, as well as provide real-time performance monitoring and systematic risk management through both rule-basedand machine-learning algorithms to optimize portfolio performance. The risk/performance metrics the Adviser regularly calculates,and uses include Sharpe ratio, Sortino ratio, maximum drawdown, beta, alpha, standard deviation, portfolio turnover, and tradingcosts. In addition, the Adviser utilizes portfolio optimization techniques to determine trading activity, taking into accountanticipated transaction costs associated with trading a particular security. The model parameters the Adviser may optimize includesecurity selection criteria, weighting, diversification, rebalancing frequency, and cash allocation. The Adviser has full discretionto override the machine-learning algorithms at any time, but it is unlikely the Adviser will do so on a regular basis. This wouldgenerally occur when portfolio security weightings and/or the portfolio turnover exceed expected thresholds. TheAdviser may employ various overlay strategies for the Fund that are designed to increase return and/or hedge against market risksand/or generate income. One strategy that may be employed by the Adviser involves writing covered calls on the broad market usingETF(s) based options and/or on stock holdings in the Fund. The Fund’s use of covered calls will provide the Fund with income,but it will limit the Fund’s opportunity to profit from an increase in the market value of the underlying security to theexercise price (plus the premium received). The Adviser may write call options on securities indices when the Adviser believesthe underlying index is going to be flat or down. Both of these overlay strategies are designed to generate income for the Fundduring periods when market conditions are expected to be flat to neutral. Another overlay strategy the Adviser may employ involvesthe use of short selling. Short selling involves investing in such a way that the Fund will benefit from a decline in value ofan asset. The Adviser’s use of short selling will be primarily used to hedge/protect against a perceived risk such as amajor market downturn. It is anticipated that the Fund’s use of short selling will typically involve shorting ETF(s) and/orstock holdings in the Fund. The Adviser may purchase put options on securities indices and/or stock holdings that provide downsideprotection as it relates to the Fund’s exposure to large cap stocks and/or to a market sector that the Adviser has identifiedas a risk for the Fund.