Smart leverage? Rethinking the role of Leveraged Exchange Traded Funds in constructing portfolios to beat a benchmark

Leveraged Exchange Traded Funds (LETFs), while controversial, remain popular with both institutional and retail investors. We argue that the potential of LETFs has been underestimated due to the use of very simple investment strategies. We investigate the potential of including a broad stock market index LETF in long-term, dynamically-optimal investment strategies. Our objective function is designed to maximize the outperformance over standard investment benchmarks (i.e. the information ratio (IR)). Our results exploit the observation that positions in a LETF deliver call-like payoffs. The addition of a LETF to a portfolio can be a way to add inexpensive leverage while providing downside protection. Under stylized assumptions, we analyze closed-form IR-optimal investment strategies using either a LETF or standard/vanilla ETF (VETF). In more realistic settings, we use a neural network-based approach to determine the IR-optimal strategies, trained on bootstrapped historical data. We find that IR-optimal strategies with a broad stock market LETF are more likely to outperform the benchmark than IR-optimal strategies with the corresponding VETF. The IR-optimal portfolio containing the LETF is also able to achieve partial stochastic dominance over the benchmark and VETF-based strategies. Our results help to explain the empirical appeal of LETFs to investors.