Applying technical analysis to leveraged ETFs : an empirical study using moving averages

Abstract

Leveraged ETFs (LETFs) are exchange traded funds that use derivatives and borrowing to deliver a multiple, typically two or three times, the daily performance of an index. They attract investors because of the potential for magnified gains, but they also come with risks such as volatility drag and path dependency that can decrease long-term performance. This study examines whether a simple, rule-based trading strategy can help overcome some of these issues. The strategy uses a crossover signal between a 12-day exponential moving average (EMA) and a 100-day triangular moving average (TMA). To limit downside risk, it adds a stop-loss that adjusts dynamically using the Average True Range (ATR) The approach was tested on three well-known leveraged ETFs, TQQQ, UPRO, and UDOW , across different market conditions. In some cases the strategy did better than a plain buy-and-hold, especially when markets were volatile. The gains showed up not only in stronger risk-adjusted returns but also in smaller drawdowns compared with the benchmark. Overall, the results suggest that a systematic EMA鈥揟MA strategy with ATR risk controls can offer a steadier way of trading leveraged ETFs. While it does not remove the structural weaknesses of these products entirely, it provides evidence that adaptive, momentum-driven rules may help active traders manage risk and improve consistency where passive exposure often struggles. Furthermore, the findings highlight the value of disciplined, rules-based methods in volatile markets and suggest that this framework could be refined and extended in future studies to test its relevance across different assets and time horizons.