Long Term Performance of Leveraged ETFs

Lü, Lei; Wang, Jun; Zhang, Ge

doi:10.2139/ssrn.1344133

Cited by 58 publications

(54 citation statements)

References 8 publications

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“…Theoretically, given a high enough volatility, almost any long-term multiple is possible with the most likely scenario being a deterioration in the longterm multiple. Both the popular press and academic studies have made substantial note of this fact and generally suggest very short 3 Journal of Financial Studies & Research holding periods for leveraged funds, (Trainor & Baryla, 2008;Carver, 2009;Avellaneda & Zhang, 2010;Lu, Wang, & Zhang, 2009;Justice, 2009;Lauricella, 2009;Spence, 2009Spence, , 2010Zwieg, 2009;Maxey, 2009). …”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting Holding Periods for Leveraged ETFs Using Decay Thresholds: Theory and Applications

Trainor¹,

Carroll²

2013

JFSR

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Due to the interplay between daily rebalancing and volatility, Leveraged Exchange Traded Funds (ETFs) may experience a cumulative return different from the product of their daily leverage ratio and the periodic index return. When the leveraged ETF's return over a particular time frame minus the leverage ratio of the ETF multiplied by the underlying index return is negative, we refer to it as decay. The quantity of this decay is influenced by the daily leverage ratio, time, index return, and volatility. This study quantifies the tradeoffs these variables have on decay, and derives maximum holding periods given an investor's decay threshold under various volatility environments. While the majority of studies suggest short holding periods for leveraged ETFs, this paper asserts that extended holding periods can be justified depending on volatility levels and an investor's willingness to accept a certain level of decay.For decay thresholds of only -2% and low volatility levels, holding periods beyond 6 months can be justified for some leveraged funds. Empirically, forecasted decay over a 3-month period based on the Russell 1000 and using a GARCH (1, 1) volatility estimate rarely underestimates actual decay. Through 2007, the average justified holding period for all but the -3x fund generally exceeded 4 months. During the financial crisis, justified holding periods decreased dramatically.

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Section: Literature Reviewmentioning

confidence: 99%

Forecasting Holding Periods for Leveraged ETFs Using Decay Thresholds: Theory and Applications

Trainor¹,

Carroll²

2013

JFSR

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“…It has been empirically established that if we consider investments over extended periods of time (e.g, three months, one year, or more), there are significant discrepancies between LETF returns and the returns of the corresponding leveraged buy-and-hold portfolios composed of index ETFs and cash [7]. Since early 2008, the quarterly performance of LETFs over any period of 60 business days has been inferior to the performance of the corresponding static leveraged portfolios for many leveraged/unleveraged pairs tracking the same index.…”

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confidence: 99%

Path-Dependence of Leveraged ETF Returns

Avellaneda¹,

Zhang²

2010

SIAM J. Finan. Math.

125

101

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Abstract.It is well known that leveraged exchange-traded funds (LETFs) do not reproduce the corresponding multiple of index returns over extended (quarterly or annual) investment horizons. For instance, in 2008 and early 2009, most LETFs underperformed the corresponding static strategies. In this paper, we study this phenomenon in detail. We give an exact formula linking the return of a leveraged fund with the corresponding multiple of the return of the unleveraged fund and its realized variance. This formula is tested empirically over quarterly horizons for 56 leveraged funds (44 double-leveraged and 12 triple-leveraged) using daily prices since January 2008 or since inception, according to the fund considered. The results indicate excellent agreement between the formula and the empirical data. The study also shows that leveraged funds can be used to replicate the returns of the underlying index, provided we use a dynamic rebalancing strategy. Empirically, we find that rebalancing frequencies required to achieve this goal are moderate-on the order of one week between rebalancings. Nevertheless, this need for dynamic rebalancing leads to the conclusion that LETFs as currently designed may be unsuitable for buy-and-hold investors.

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“…Jarrow [6] and Avellaneda and Zhang [7] were some of the first to do so. The work by both sets of authors is very similar.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Leveraged ETF Volatility Using Nonparametric Density Estimation

Ginley¹,

Scott²,

Ensor³

2015

JMF

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Leveraged Exchange Traded Funds (LETFs) are constructed to provide the indicated leverage multiple of the daily total return on an underlying index. LETFs may perform as expected on a daily basis; however, fund issuers state that there is no guarantee of achieving the multiple of the index return over longer time horizons. LETF returns are extremely volatile and funds frequently underperform their target for horizons greater than one month. In this paper, we contribute two nonparametric simulation methods for analyzing LETF return volatility and how this is related to the underlying index. First, to overcome the limited history of LETF returns data, we propose a method for simulating implied LETF tracking errors while still accounting for their dependence on underlying index returns. This allows for the incorporation of the complete history of index returns in an LETF returns model. Second, to isolate the effects of daily, leveraged compounding on LETF volatility, we propose an innovative method for simulating daily index returns with a chosen constraint on the multi-day period return. By controlling for the performance of the underlying index, the range of volatilities observed in a simulated sample can be attributed to compounding with leverage and the presence of tracking errors. Our nonparametric methods are flexible-easily incorporating any chosen number of days, leverage ratios, or period return constraints, and can be used in combination or separately to model any quantity of interest derived from daily LETF returns.

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Long Term Performance of Leveraged ETFs

Cited by 58 publications

References 8 publications

Forecasting Holding Periods for Leveraged ETFs Using Decay Thresholds: Theory and Applications

Forecasting Holding Periods for Leveraged ETFs Using Decay Thresholds: Theory and Applications

Path-Dependence of Leveraged ETF Returns

Simulation of Leveraged ETF Volatility Using Nonparametric Density Estimation

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