Understanding ETFs

The Dynamics of Leveraged and Inverse Exchange-Traded Funds Minder Cheng and Ananth Madhavan Barclays Global Investors April 8, 2009 Abstract Leveraged and inverse Exchange-Traded Funds (ETFs) have attracted significant assets lately. Unlike traditional ETFs, these funds have “leverage” explicitly embedded as part of their product design and are primarily used by short-term traders, but are gaining popularity with individual investors placing leveraged bets or hedging their portfolios. The structure of these funds, however, creates both intended and unintended character- istics that are not seen in traditional ETFs. This note provides a unified framework to better understand the underlying dynamics of leveraged and inverse ETFs, their im- pact on market volatility and liquidity, unusual features of their product design, and questions of investor suitability. In particular, leveraged funds are not well understood both by investors and industry professionals. The daily re-leveraging of these funds creates profound microstructure effects and exacerbates volatility towards the close. We also show that the gross return of a leveraged or inverse ETF has an embedded path-dependent option that under certain conditions can lead to value destruction for a buy-and-hold investor. The unsuitability of these products for longer-term investors is reinforced by the drag on returns from high transaction costs and tax inefficiency.† 1 Introduction Leveraged and inverse Exchange-Traded Funds (ETFs) provide leveraged long or short exposure to the daily return of various indexes, sectors, and asset classes. These funds have “leverage” explicitly embedded as part of their product design. The category has exploded since the first products were introduced in 2006, especially in volatile sectors such as Financials, Real Estate, and Energy. There are now over 106 leveraged and inverse ETFs in the US with Assets Under Management (AUM) of about $22 billion.1 The space now comprises leveraged, inverse, and leveraged inverse ETFs offering 2× or 3× long exposure or short exposure of −1×, −2×, or −3× the underlying index returns. The †The views expressed here are those of the authors alone and not necessarily those of Barclays Global Investors, its officers or directors. We thank Mark Coppejans, Matt Goff, Allan Lane, Hayne Leland, J. Parsons, Heather Pelant, Ira Shapiro, Mike Sobel, Richard Tsai and an anonymous referee for their helpful comments. c© 2009, Barclays Global Investors. 1Leveraged and inverse equity ETFs constitute about 4% of overall ETF assets, but account for a greater fraction of recent ETF growth and trading activity. 1 Dynamics of Leveraged and Inverse ETFs 2 most recent products authorized by the US Securities and Exchange Commission (SEC) offer the highest leverage factors. However, the bulk of AUM remains in 2× leveraged products. Coverage has also expanded beyond equities and includes commodities, fixed income and foreign exchange. In addition, option contracts on leveraged ETFs have also gained in popularity. There is strong growth in this space outside the US as well.2 Leveraged and inverse mutual funds analogous to ETFs have also grown in popularity. Other than the fact that they offer investors liquidity at only one point in the day, the structure of these products is identical to leveraged and inverse ETFs and hence our analysis is fully applicable to these funds too. Several factors explain the attraction of leveraged and inverse ETFs. First, these funds offer short-term traders and hedge funds a structured product to express their directional views regarding a wide variety of equity indexes and sectors. Second, as investors can obtain levered exposure within the product, they need not rely on increasingly scarce outside capital or the use of derivatives, swaps, options, futures, or trading on margin. Third, individual investors – attracted by convenience and limited liability nature of these products – increasingly use them to place longer-term leveraged bets or to hedge their portfolios. The structure of these funds, however, creates both intended and unintended character- istics. Indeed, despite their popularity, many of the features of these funds are not fully understood, even among professional asset managers and traders. This paper provides a unified framework to better understand some key aspects of these leveraged and inverse ETFs, including their underlying dynamics, unusual features of their product design, their impact on financial market microstructure, and questions of investor suitability. Specifically, leveraged ETFs must re-balance their exposures on a daily basis to produce the promised leveraged returns. What may seem counterintuitive is that irrespective of whether the ETFs are leveraged, inverse or leveraged inverse, their re-balancing activity is always in the same direction as the underlying index’s daily performance. The hedging flows from equivalent long and short leveraged ETFs thus do not “offset” each other. The magnitude of the potential impact is proportional to the amount of assets gathered by these ETFs, the leveraged multiple promised, and the underlying index’s daily returns. The impact is particularly significant for inverse ETFs. For example, a double-inverse ETF promising −2× the index return requires a hedge equal to 6× the day’s change in the fund’s Net Asset Value (NAV), whereas a double-leveraged ETF requires only 2× the day’s change. This daily re-leveraging has profound microstructure effects, exacerbating the volatility of the underlying index and the securities comprising the index. While a leveraged or inverse ETF replicates a multiple of the underlying index’s return on a daily basis, the gross return of these funds over a finite time period can be shown to have an embedded path-dependent option on the underlying index. We show that leveraged and inverse ETFs are not suitable for buy-and-hold investors because under certain circum- stances the long-run returns can be significantly below that of the appropriately levered underlying index. This is particularly true for volatile indexes and for inverse ETFs. The unsuitability of these products for longer-term investors is reinforced by tax inefficiency and the cumulative drag on returns from transaction costs related to daily re-balancing activity. The paper proceeds as follows: Section 2 shows how leveraged and inverse ETF returns 2On February 23, 2009, Deutsche Bank launched the first inverse ETF in Asia. The fund, traded in Singapore, allows investors to target the S&P500 index. Dynamics of Leveraged and Inverse ETFs 3 are related to those of the underlying index and provides an overview of the mechanics of the implied hedging demands resulting from the daily re-leveraging of these products; Section 3 explains the microstructure implications and resulting return drag from trading costs associated with hedging activity; Section 4 analyzes the longer-term return characteristics of these products and the value of the embedded option within; and Section 5 summarizes our results and discusses their implications for public policy. 2 The Mechanics of Leveraged Returns 2.1 Producing Leveraged Returns As leveraged returns cannot be created out of thin air, leveraged and inverse ETFs gen- erally rely on the usage of total return swaps to produce returns that are a multiple of the underlying index returns. Futures contracts can also be used in addition to, or instead of, total return swaps. However, given their exchange-imposed standardized specification (to facilitate exchange-based trading and clearing), futures are not as customizable as total return swaps and are more limited in terms of index representation. In addition, basis risk is more significant with the futures than with total return swaps.3 Leveraged returns also can be produced by trading in physicals on margin. In other words, by borrowing the required capital in excess of its AUM, a leveraged ETF can invest in a properly levered position of the securities comprising the ETF’s index benchmark. A negative implication of such an implementation strategy is that the financing cost will create a drag on the fund’s performance with respect to its promised leveraged return. On the other hand, an inverse or leveraged inverse ETF can short the securities comprising the ETF’s index benchmark and accrue interest income. Interestingly, a new breed of leveraged and inverse ETFs has recently emerged that are managed against customized index benchmarks. These benchmarks explicitly incorporate the financing cost (for leveraged ETFs) or accrued interest (for inverse and leveraged inverse ETFs) in index construction. Consequently, financing cost and accrued interest will not appear as a deviation against the funds’ index benchmark.4 Throughout this paper, we will assume that leveraged and inverse ETFs rely on total return swaps to produce the promised leveraged returns.5 Our findings remain unchanged regardless of how leveraged returns are produced, whether by trading in physicals on margin, equity linked notes, futures or other derivatives besides total return swaps. Unlike traditional ETFs, leveraged and inverse ETFs can be viewed as pre-packaged margin products, albeit without any restrictions on margin eligibility. It is also worth noting that creations and redemptions for leveraged and inverse ETFs are in cash, while for traditional ETFs this is typically an “in-kind” or basket transfer. 3Basis risk refers to the risk associated with imperfect hedging, possibly arising from the differences in price, or a mismatch in sale and expiration dates, between the asset to be hedged and the corresponding derivative. 4See, for example, Dow Jones STOXX Index Guide (2009). 5Most leveraged funds do indeed record a majority of their assets in swaps, with a pool of futures contracts to manage liquidity demands and reduce transaction costs. Dynamics of Leveraged and Inverse ETFs 4 2.2 Conceptual Framework We turn now to the development of a unified conceptual framework to analyze inverse and leveraged ETFs. We will utilize a continuous time framework. All extant leveraged and inverse ETFs promise to deliver a multiple of its underlying benchmark’s daily returns, so we will focus on the dynamics of the index and of the corresponding leveraged and inverse ETFs over a discrete number of trading days indexed by n where n = 0, 1, 2, ..., N . Let tn represent the calendar time of day n, measured as a real number (in years) from day 0. We assume t0 = 0 initially, a convenient normalization. Note the frequency of n does not have to be daily. If there are leveraged or inverse ETFs designed to produce a multiple of the underlying benchmark’s return over a different frequency (e.g., hourly, weekly, monthly, quarterly, etc.), we can redefine n accordingly without any loss of generality. Let St represent the index level which a leveraged or inverse ETF references as its underlying benchmark at calendar time t. Later, in section 4 we will explicitly describe the continuous time process underlying the evolution of the index level, but for now let rtn−1, tn represent the return of the underlying index from tn−1 to tn, where rtn−1, tn = Stn Stn−1 − 1 (1) We will assume there are no dividends throughout to focus on the price and return dynamics without any loss of generality. Let x represent the leveraged multiple of a leveraged or inverse ETF. Therefore x = −2, -1, 2 and 3 correspond to double-inverse, inverse, double-leveraged and triple-leveraged ETFs. 2.3 Return Divergence and Path Dependency It will become clear later that the exposures of total return swaps underpinning leveraged and inverse ETFs need to be re-balanced or re-set daily in order to produce the promised leveraged returns. In effect, these funds are designed to replicate a multiple of the underlying index’s return on a daily basis. The compounding of these daily leveraged moves can result in longer-term returns, as expressed by: ΠNn=1(1 + x rtn−1, tn) (2) that have a very different relationship to the longer-term returns of the underlying index leveraged statically, as given by: (1 + x rt0, tN ) (3) We can use a double-leveraged ETF (x = 2) with an initial NAV of $100 as an example. It tracks an index that starts at 100, falls 10% one day and then goes up 10% the subsequent day. Over the two-day period, the index declines by -1% (down to 90, and then climbing to 99). While an investor might expect the leveraged fund to decline by twice as much, or -2%, over the two-day period, it actually declines further, by -4%. Why? Doubling the index’s 10% fall on the first day pushes the fund’s NAV to $80. The next day, the fund’s NAV climbs to $96 upon doubling the index’s 10% gain. This example illustrates the path dependency of leveraged ETF returns, a topic we return to more formally when we model the continuous time evolution of asset prices in section 4. Dynamics of Leveraged and Inverse ETFs 5 Figure 1: DUG versus DIG (March 2-6, 2009) Figure 2: DUG versus DIG (September 2008 - March 2009) 2.3.1 Example: DUG and DIG Real world examples of the effects noted above – and the confusion they cause among retail investors – are not difficult to find. The relation between short- and long-run performance of leveraged ETFs is well illustrated in the case of the −2× ProShares UltraShort Oil & Gas (DUG) and its 2× long ProShares counterpart (DIG) that track the daily performance of the Dow Jones US Oil & Gas index. As shown in Figure 1, these funds are mirror images of each other over short periods of time, in this case a few trading days in March. Over longer periods, however, the performance is materially different as shown in the six month period in Figure 2. Indeed between September of 2008 and February of 2009, both ETFs were down substantially. These examples illustrate the path-dependency highlighted in the analysis. 2.4 Re-balancing and Hedging Demands The re-balancing of inverse and leveraged funds implies certain hedging demands. Since extant funds promise a multiple of the day’s return, it makes sense to focus on end-of-day hedging demands. One benefit of modeling returns in continuous time, however, is that our analysis generalizes to any arbitrary re-balancing interval. Let Atn represent a leveraged or inverse ETF’s NAV at the close of day n or at time tn. Corresponding to Atn , let Ltn Dynamics of Leveraged and Inverse ETFs 6 represent the notional amount of the total return swaps exposure that is required before the market opens on the next day to replicate the intended leveraged return of the index for the fund from calendar time tn to time tn+1. With the fund’s NAV at Atn at time tn, the notional amount of the total return swaps required is given by: Ltn = xAtn (4) On day n + 1, the underlying index generates a return of rtn, tn+1 and the exposure of the total return swaps, denoted by Etn+1 , becomes: Etn+1 = Ltn (1 + rtn, tn+1) (5) = xAtn (1 + rtn, tn+1) (6) At the same time, reflecting the gain or loss that is x times the index’s performance between tn and tn+1, the leveraged fund’s NAV at the close of day n+ 1 becomes: Atn+1 = Atn (1 + x rtn, tn+1) (7) which suggests that the notional amount of the total return swaps this is required before the market opens next day to maintain constant exposure is: Ltn+1 = xAtn+1 (8) = xAtn (1 + x rtn, tn+1) (9) The difference between (6) and (9), denoted by ∆tn+1 , is the amount by which the exposure of the total return swaps that need to be adjusted or re-hedged at time tn+1, as given by: ∆tn+1 = Ltn+1 − Etn+1 (10) = Atn (x 2 − x) rtn, tn+1 (11) 2.4.1 Example: Daily Hedging Demands We can illustrate the above using an example that is built on the same case already discussed in Section 2.3. With an initial NAV of $100 on day 0 for the double-leveraged ETF, the required notional amount of the total return swaps is $200 (or 2 times $100). As the index falls from 100 to 90 on day 1, the fund’s NAV drops to $80 whereas the exposure of the total return swaps falls to $180, reflecting a 10% drop of its value. Meanwhile the required notional amount for the total return swaps for day 2 is $160 (or 2 times $80), which means the fund will need to reduce its exposure of total return swaps by $20 (or $180 minus $160) at the end of day 1. And note 100× (22 − 2)× 10% = 20. The dynamics of Stn , Atn , Ltn , Etn and ∆tn for n = 0, 1 and 2 are summarized in Table 1 below. Tables 2 and 3 provide examples for an inverse ETF and a double-inverse ETF, re- spectively, with the same assumptions of the index’s performance over two days. These examples highlight the critical role of the hedging term (x2 − x) in (11). This term is non- linear and asymmetric. For example, it takes the value 6 for triple-leveraged (x = 3) and double-inverse (x = −2) ETFs. As (x2− x) is always positive (except for when x = 1 when the funds are not leveraged or inverse), the reset or re-balance flows are always in the same Dynamics of Leveraged and Inverse ETFs 7 Table 1: Dynamics of a double-leveraged ETF (x = 2, rt0, t1 = −10% and rt1, t2 = 10%) Stn Atn Ltn Etn ∆tn n = 0 100 100 200 - - n = 1 90 80 160 180 -20 n = 2 99 96 192 176 +16 Table 2: Dynamics of an inverse ETF (x = −1, rt0, t1 = −10% and rt1, t2 = 10%) Stn Atn Ltn Etn ∆tn n = 0 100 100 -100 - - n = 1 90 110 -110 -90 -20 n = 2 99 99 -99 -121 +22 direction as the underlying index’s performance. In other words, when the underlying index is up, additional exposure of total return swaps needs to be added; When the underlying index is down, the exposure of total return swaps needs to be reduced. This is always true whether the ETFs are leveraged, inverse or leveraged inverse. In other words, there is no offset or “pairing off” of leveraged long and short ETFs on the same index, which is why the re-balance flows are in the same direction between Table 1 for a double-leveraged ETF and Tables 2 and 3 for an inverse and a double-inverse ETF on day 1 and day 2, respectively. Note the need for daily re-hedging is unique to leveraged and inverse ETFs due to their product design. Traditional ETFs that are not leveraged or inverse, whether they are holding physicals, total return swaps or other derivatives, have no need to re-balance daily. We discuss the implications of daily re-balances in the next section. 3 Market Structure Effects 3.1 Liquidity and Volatility near Market Close As leveraged and inverse ETFs gather more assets, the impact of their daily re-leveraging on public equity markets is raising concerns. Many commentators have cited leveraged and inverse ETF re-balancing activity as a factor behind increased volatility at the close.6 Of 6See, e.g., Lauricella, Pulliam, and Gullapalli (2008), who note: “As the market grew more volatile in September, Wall Street proprietary trading desks began piling onto the back of the trade knowing that the end-of-day ETF-related buying or selling was on its way. If the market was falling, they would buy a short Dynamics of Leveraged and Inverse ETFs 8 Table 3: Dynamics of a double-inverse ETF (x = −2, rt0, t1 = −10% and rt1, t2 = 10%) Stn Atn Ltn Etn ∆tn n = 0 100 100 -200 - - n = 1 90 120 -240 -180 -60 n = 2 99 96 -192 -264 +72 course, other factors might also account for heightened volatility at the close. For exam- ple, traders might choose to trade later in the day because there are more macroeconomic announcements earlier in the day or because the price discovery process takes longer. Nev- ertheless, as we show in this section, there are good theoretical and empirical grounds to support the argument that daily re-leveraging by leveraged and inverse ETFs contributes to volatility. In theory, re-balancing activity should be executed as near the market close as possi- ble given the dependence of the re-balancing amount on the close-to-close return of the underl