The Fund invests primarily in total return swaps that provide the returns, long or short, of a basket of common stocks. The companies in the swap basket are selected using a third-party, multi-factor quantitative ranking system based on machine learning. The ranking system seeks to identify the factors that are driving both positive and negative returns and classify securities based on forward-looking return expectations. The ranking system considers over 500 fundamental factors. The adviser selects securities based on analyses from the third-party research provider and aims to include the names of over 200 stocks with the best expected returns in the long basket and the names of over 200 stocks with lowest expected returns in the short basket. Machine learning is a form of computer program that analyses raw data and detects patterns and translates those patterns into mathematical formulas that can be used to forecast security prices.