Machine Learning Credit Spread ETF Strategy
Utilizing Supervised Machine Learning techniques, categorize and forecast the expected credit spread. ETF's are used to trade the signal generated to create an unlevered strategy with a 1.64 Sharpe and 2.8 Sortino with very low drawdown (2.4%). The benchmark consists of the same two ETF's as the strategy with a static hedge ratio and is always short the credit spread (long the credit ETF short a ratio the treasury ETF).