The poor tracking performance of daily-rebalanced leveraged exchange-traded products (LETPs) during the global financial crisis of 2007–2009 led to the perception that these products are prone to detrimental deviations in returns from “naive” expectations (e.g., –2×, –3×). In this study, the authors present findings contrary to this perception and conducive to a more informed understanding of LETP performance.
In previous studies, researchers examined the deviation of the market return on leveraged exchange-traded products (LETPs) from their naive expected return during the 2007–09 global financial crisis, which consequently relied on data constrained by a short history and limited product designs, as well as by the influence of the crisis itself. In this study, the authors use the longest available history of equity market data—that of the DJIA (Dow Jones Industrial Average) from 1896 to 2010—to simulate the return and multiple deviations of LETPs across different rebalancing periods. The authors also construct a comprehensive framework for determining the effective multiple for LETPs.
How Is This Research Useful to Practitioners?
Contrary to widespread perception, the authors find that the deviation of an LETP’s return from its naive expectation (the stated product multiple times the underlying index return) does not, on average, adversely affect investor returns over the holding period of a year or longer.
The authors define the compounding effect of an LETP during a holding period as that LETP’s target return minus its naive expected return. They find that for 3×, 2×, –1×, –2×, and –3× daily-rebalanced LETPs, the compounding effect on fund performance is, overall, neutral when the holding period is a calendar month and beneficial when the holding period is a calendar year.
The authors also examine LETP returns when the purchase date is random and the holding period is allowed to vary between 2 and 2,500 trading days. Consistent with their calendar month and year results, they find that the cumulative return deviation (actual versus naive expected) is positive for all five daily-rebalanced LETPs, and as the number of holding days increases, the positive return deviation also increases.
All monthly observations of daily-rebalanced LETPs are double sorted by index return (cumulative squared) and volatility (variance). Based on the resulting return by volatility matrices, the authors conclude that the compounding effect is beneficial to long-term investors during periods with large return magnitudes and low volatility (including the Great Depression) but not during periods with high volatility and small return magnitudes (e.g., the 2007–09 financial crisis).
Finally, the authors use the concepts of return (both index and LETP) and volatility (index) to present a framework for determining the effective multiple for LETPs under two scenarios: (1) when the holding period is longer than the (e.g., daily) rebalancing period and (2) when the holding period is shorter than (began after the start of) the rebalancing period.
How Did the Authors Conduct This Research?
For the underlying index, the authors use the performance of the DJIA from its inception in May 1896 to December 2010 and obtain daily total return data from Bloomberg. For each LETP, the target daily return is calculated as the stated multiple—that is, 3×, 2×, –1×, –2×, or –3×—multiplied by the underlying index return on a daily basis. Daily LETP target returns are accumulated over the holding period to arrive at the LETP’s cumulative target return.
The authors conduct a return deviation analysis over various holding periods (e.g., calendar month, calendar year) to assess LETP compounding effects, which are determined by differences between cumulative target and naive expected returns for given holding periods.
They also examine multiple deviation—the difference between the effective multiple (the cumulative target return of an LETP divided by the cumulative return on the underlying index during the holding period) and the stated multiple. The authors conduct their multiple deviation analysis by examining the interaction between the effective and stated multiples across different holding periods and rebalancing frequencies.
To test robustness, they conduct additional return deviation analyses in four different ways: (1) using a broader stock market index (S&P 500 Index), (2) using higher-volatility indices (S&P SmallCap 600 and NASDAQ composite), (3) incorporating management fees, and (4) using a Monte Carlo simulation. The authors’ findings are robust in all but the Monte Carlo simulation. They believe this result is largely because the actual DJIA daily return distribution is more peaked and dense around the mean (leptokurtic) than the normal distribution assumed for the Monte Carlo simulation.
The authors provide meaningful observations regarding the historical interaction between LETP volatility and cumulative returns relative to the benefit (or detriment) that arises from the compounding effect. This research serves as an important qualifier for the perception that LETPs have an adverse impact on investor returns over time. I still hesitate to promote the use of LETPs to implement long-term strategies. The financial crisis of 2007–2009 may constitute a unique crisis within the 114+ years examined by this study, but we do not know whether its particular volatility/return profile will or will not turn out to be the model for crises yet to come.