标题： 杠杆ETF中的复合效应：超越波动性拖累范式 显示英文标题

标题： Compounding Effects in Leveraged ETFs: Beyond the Volatility Drag Paradigm

摘要： 一种普遍的观点认为，杠杆ETF（LETFs）由于\emph{波动率拖拽}而长期表现衰减。 我们表明这种观点是不全面的：LETF的表现从根本上取决于回报自相关性和回报动态。 在回报独立的市场中，LETFs对其目标倍数表现出正的预期复合效应。 在序列相关的市场中，趋势增强收益，而均值回归导致表现不佳。 通过一个统一框架，该框架结合了AR(1)和AR-GARCH模型、连续时间的制度转换以及灵活的再平衡频率，我们证明了回报动态——包括回报自相关性、波动率聚类和制度持久性——决定了LETFs是超越还是落后于其目标。 实证分析中，使用大约20年的SPDR S\&P~500 ETF和Nasdaq-100 ETF数据，我们验证了这些理论预测。 每日再平衡的LETFs在动量驱动的市场中提升收益，而较少频次的再平衡则在均值回复的环境中减轻损失。 显示英文摘要

摘要： A common belief is that leveraged ETFs (LETFs) suffer long-term performance decay due to \emph{volatility drag}. We show that this view is incomplete: LETF performance depends fundamentally on return autocorrelation and return dynamics. In markets with independent returns, LETFs exhibit positive expected compounding effects on their target multiples. In serially correlated markets, trends enhance returns, while mean reversion induces underperformance. With a unified framework incorporating AR(1) and AR-GARCH models, continuous-time regime switching, and flexible rebalancing frequencies, we demonstrate that return dynamics -- including return autocorrelation, volatility clustering, and regime persistence -- determine whether LETFs outperform or underperform their targets. Empirically, using about 20 years of SPDR S\&P~500 ETF and Nasdaq-100 ETF data, we confirm these theoretical predictions. Daily-rebalanced LETFs enhance returns in momentum-driven markets, whereas infrequent rebalancing mitigates losses in mean-reverting regimes.