This ETF, HRAA, implements a dynamic asset allocation framework across major asset classes. It integrates three sophisticated investment methodologies: a risk parity approach, a systematic long/short global macro strategy, and a mechanism for dynamic tail protection. The fund gains its exposure to global securities predominantly through futures and forward contracts. Its sub-advisor deploys an algorithmic global macro strategy that utilizes machine learning. This machine learning-driven approach constructs a portfolio by identifying and leveraging factors such as total return momentum, seasonal patterns, carry measures, and mean reversion, while simultaneously optimizing for diversification through careful consideration of volatility and correlations. The integrated risk parity strategy is designed to ensure that each asset class contributes an equivalent amount of risk to the overall portfolio. Furthermore, a dynamic tail risk protection component, executed through long and short volatility futures, aims to mitigate the impact of significant and rapid market selloffs. HRAA seeks to achieve low correlation with conventional equity and fixed income markets and targets an average annualized volatility level of 12% or lower. The fund also has the capacity to utilize financial leverage, potentially up to 300%.