ETFs are owned for Investing, traded for Liquidity

Transcription

1 Deutsche Bank Markets Research North America Synthetic Equity & Index Strategy Date ETFs are owned for Investing, traded for Liquidity After 23 years, ETFs are still highly misunderstood. This is why. ETF users are by no means a uniform group. We identify two distinct types: ETF investors and ETF traders. Investors use ETFs as core building blocks in their portfolios mostly for asset allocation purposes. Meanwhile, traders use ETFs as liquidity tools mostly for non-asset allocation purposes. ETF investors buy efficient access to asset class exposure; while ETF traders buy efficient access to asset class liquidity. Investors own the majority of ETF assets and represent a small fraction of ETF trading volumes; while traders own only a fraction of ETF assets, but represent the majority of ETF trading volumes. Sebastian Mercado, CFA Strategist % of ETF assets are held for asset allocation purposes, but only represent 14% of ETF trading... We estimate that institutional and retail investors own 47% and 38% of ETF assets for asset allocation purposes, respectively. Among the major three asset classes, Fixed Income ETFs have the highest asset allocation ETF ownership with 93%; while equity ETFs have the lowest asset allocation ETF ownership with 83%....while the remaining 15% held for non-asset allocation purposes represents 86% of ETF traded volume We estimate that institutions account for the bulk of the non-asset allocation ownership with 12% used for cash management (5%), or pseudo futures-like activities such as risk hedging (7%). On the other hand, we estimate that retail investors account for only 3% of non-asset allocation ETF ownership. Commodity, currency, volatility, leveraged, and inverse products are mainly used as trading tools Based on average holding period analysis, Equity and Fixed Income ETFs are mostly used as asset allocation tools. Commodity and Currency ETPs, on the other hand, clearly reflect a more tactical usage; and Volatility products are almost exclusively being used as trading tools. Furthermore, Smart beta ETFs are mostly being used as strategic asset allocation tools; while Leveraged and Inverse ETPs are mostly being used as trading tools. Average Holding Period (AHP), along with ETF flows provide insight about a product's usage We found that products used mainly for asset allocation have a very distinct pattern with smooth flows and AHP closer to 180 days or beyond; while products mostly used as liquidity tools have volatile flows and AHP closer to 30 days or lower. Distributed on: 08/05/ :58:14GMT Deutsche Bank does and seeks to do business with companies covered in its research reports. Thus, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1.MCI (P) 057/04/2016.

2 Investing vs Trading One of the main criticisms of ETFs has been the fact that their ability to trade can induce excessive trading activity by investors leading to eventual poor results due to transaction costs and failed market timing attempts. This statement is frequently linked to another common belief that ETFs are mainly a retail product. Thus, the combination of these two suppositions has quickly lead some to the conclusion that ETFs are some sort of vehicle of mass destruction of wealth for the less sophisticated retail investor, and therefore should be closely monitored and seen with skepticism. This belief, however, could not be farther from the truth and it is the result of trying to understand this new product utilizing a wrong and outdated framework. In previous reports, we have discussed extensively who the major users of ETFs are and have demonstrated how ETFs have eventually become a product dominated by institutional ownership1. Now we take further steps to understand the differences between investing in ETFs and trading ETFs. More specifically, we use ETF Average Holding Period to obtain a better understanding of each product's trading profile, and fine tuning specific investment usage estimations. When it comes to ETFs, investing is usually driven by asset allocation of strategic or ETFs are owned by those that need to invest, tactical nature where the fund plays a major role in the portfolio construction. On the and are traded by those that need liquidity other hand, trading is usually driven by short-term non-asset allocation purposes where the product plays the role of liquidity enabler to perform tasks such as cash management or risk management. Therefore ETFs are not just investment vehicles like mutual funds. In fact, ETFs are two products in one. On one side, they are investment tools and offer investors access to a desired exposure for a specific fee; while on the other side, they are liquidity tools which offer traders asset class liquidity at a specific cost. Thus, ETFs are owned by those that need to invest, and are traded by those that need liquidity; which most of the time, are not the same individual or entity. Why it is important to understand the differences between ETF investing and ETF trading Understanding these differences is vital to clarify market participant's misconceptions about ETFs. Because only after understanding this they will realize that: 1. ETF investing and ETF trading are not the same 2. Most investors don't trade ETFs excessively, but actually hold them strategically 3. Traders focus on a specific and reduced set of ETFs which concentrate most of the ETF volume activity and meet their liquidity demands 4. Trading activity is dominated by institutional traders 5. Investment activity is dominated by institutional and retail investors For these reasons, ETFs don't only provide an efficient access solution for investors, ETFs don't only provide an efficient access but also provide an efficient access to liquidity for traders in a world where liquidity solution for investors, but also provide an efficient access to liquidity for traders in a has become a scarce resource. world where liquidity has become a scarce resource 1 See "ETF Institutional Ownership nears 60% at the end of 2015" published on Mar 22, Page 2

3 ETF Average Holding Period (AHP) Analysis Please meet the ETF Average Holding Period (AHP), the latest addition to our ETF ETF AHP is the average time an ETF is held research library. We define ETF AHP as the average time an ETF is held by an by an investor/trader in days investor/trader in days. It is obtained by dividing 365 by the ETF turnover. We define ETF turnover as the ratio of ETF value traded to ETF average assets and it is calculated by dividing the ETF Total Value Traded in a specific period by the average level of ETF assets under management during such period. ETF AHP = ( 365 / Turnover ) [days] Turnover = Total Value Traded / Avg. Assets Under Management For our analysis we took a sample including all ETFs, ETVs, and ETNs with over $100 million in assets under management at the end of Our sample included 784 products which although represented only 39% of the listed products, it accounted for more than 98% of the average assets and value traded during 2015 in both cases. We believe this sample to be representative and significant for our analysis because our study is centered around investment (as suggested by assets) and trading (as provided by value traded). We calculated individual AHP for each product in our sample for the year 2015 and we later aggregated and analyzed these data. Longer AHP suggests asset allocation usage; while shorter AHP suggests trading tool usage Longer holding periods are related to investment usage of products for strategic or tactical asset allocation purposes; while shorter holding periods are related to product usage as a trading tool for liquidity purposes. Furthermore, after analyzing the holding period data we have set different levels of AHP for different product profiles. Thus, we see products with an AHP of less than 30 days as trading tools, products with an AHP of over 180 days as strategic asset allocation vehicles; and those products between 30 and 180 days as having a mixed profile between trading and tactical asset allocation tool. Products used as asset allocation tools or with mixed usage make up the majority of listed products (~90%) and assets (~80%) in our sample, but less than 30% of the traded value. This supports our view that: (1) investors holding ETFs, and other similar products, for asset allocation purposes represent the majority of ETF owners, and (2) these investors are very unlikely to engage in excessive trading. On the other hand, traders make up just a small fraction of ETF ownership, but concentrate most of the traded value as a result of their liquidity requirements. Furthermore, our analysis shows that within ETPs (i.e. ETFs and ETVs) excluding leveraged and inverse products, a higher institutional ownership is related to a shorter average holding period. Or in other words, ETPs with a high institutional ownership concentrate most of the ETP trading; while ETPs with a less relevant level of institutional ownership play a less significant role in ETP trading. This strongly suggests that it is institutional investors doing most of the ETP trading, and not retail investors. Actually, retail investors are more likely to hold ETPs strategically for investment purposes. Institutions are behind most short-term ETP trading, while retail investors are more likely to hold ETPs strategically for investment purposes. Page 3

4 Figure 1: Product metrics market share by Average Holding Period bucket Source: Deutsche Bank, Bloomberg Finance LP, FactSet. Figure 2: Average Holding Period and Institutional ETP Ownership Source: Deutsche Bank, Bloomberg Finance LP, FactSet. Excludes Leveraged and Inverse Products, and ETNs. In 2015, ETFs had an average holding period of 143 days; while ETVs and ETNs had an average holding period of 87 and 326 days, respectively. These figures suggest that in general ETNs are mostly used as a strategic asset allocation product2, while ETFs are used for both trading and asset allocation, and ETVs are used mostly for trading and tactical asset allocation. However, we recognize that although there are some general trends in product holding periods and usage, we also see significant differences among individual products. Equity and Fixed Income ETFs are mostly used as asset allocation tools Our average holding period analysis suggests that Equity and Fixed Income ETFs Volatility products are almost exclusively are mostly used as asset allocation tools. Moreover we noticed that Equity ETFs being used as trading tools with an AHP of 137 days had a relatively higher tactical component when compared to Fixed Income ETFs with an AHP of 170 days. Commodity and Currency ETPs, on the other hand, clearly reflected a more tactical usage suggesting that not only traders, but also investors use these products for short term purposes. And as probably expected, Multi Asset ETFs with an AHP of over 200 days displayed a clear strategic asset allocation pattern; while Volatility ETPs and ETNs with an AHP of less than 5 days showed an striking contrast confirming the almost-exclusive usage of these products as trading tools. We also see differences in the average holding period among different ETP issuer offerings. For example among the main ETP providers, ETFs from Vanguard, Schwab, and Guggenheim are mostly being used as strategic asset allocation tools; while ETFs from ProShares and State Street are mostly being used as trading tools. At the same time, other providers such as BlackRock and WisdomTree exhibit a mixed usage according to AHP figures. 2 This is mostly true as many ETNs are the result of customized exposures offered to specific investors and therefore have a very low number of investors. However, there are some notable exceptions such as some Volatility, MLP, and Commodity ETNs. Page 4

5 Figure 3: ETP Average Holding Period by asset class Source: Deutsche Bank, Bloomberg Finance LP, FactSet. ETNs are excluded from all asset classes except Volatility. Figure 4: ETP Average Holding Period by Top 10 ETP Issuer Source: Deutsche Bank, Bloomberg Finance LP, FactSet. ETNs are excluded. Top 10 according to avg. AUM in From a management style perspective, products employing a smart beta approach Smart beta ETFs are mostly being used as are mostly being used as strategic asset allocation tools. Meanwhile actively- strategic asset allocation tools managed products which are also mostly used as asset allocation tools also display some degree of tactical usage. On the other hand, products following beta indices are being used as both trading and asset allocation tools according to AHP readings. Finally, our analysis by product type3 suggests that asset allocation and cash Leveraged and Inverse ETPs are mostly management products are mostly being used as strategic asset allocation tools, being used as trading tools with some degree of tactical asset allocation usage in the case of cash management ETPs. On the other hand, there is a stark contrast with pseudo futures and leveraged and inverse ETPs which are mostly used as trading tools. Figure 5: ETP Average Holding Period by management style Figure 6: ETP Average Holding Period by product type Source: Deutsche Bank, Bloomberg Finance LP, FactSet. ETNs are excluded. Source: Deutsche Bank, Bloomberg Finance LP, FactSet. ETNs are excluded. At an individual level we see that the products with the lowest average holding period are dominated by volatility, leveraged, inverse, or pseudo futures products. 3 See our repot titled "A Stock Pickers Guide to ETFs" published on June 5th, 2015 for additional details and definitions of different product types within ETFs, or Appendix A for a summary of definitions. Page 5

6 Figure 7: Top 100 ETPs & ETNs with the lowest AHP (1-50) Source: Deutsche Bank, Bloomberg Finance LP, FactSet. AHP is for 2015, ADV and AUM are latest available. PF: Pseudo Futures, CM: Cash Management, AA: Asset Allocation, LevInv: Leveraged and Inverse Page 6

7 Figure 8: Top 100 ETPs & ETNs with the lowest AHP (51-100) Source: Deutsche Bank, Bloomberg Finance LP, FactSet. AHP is for 2015, ADV and AUM are latest available. PF: Pseudo Futures, CM: Cash Management, AA: Asset Allocation, LevInv: Leveraged and Inverse Page 7

8 ETFs are mostly owned for asset allocation, and traded for liquidity needs Are ETFs an investment tool, a trading vehicle, or both The debate can go on and on. However, in this report we leverage our previous research in the areas of ETF ownership, product usage, and our new analysis in the average holding period space in an effort to introduce a quantitative framework that would help us to throw some light on the debate. ETF ownership as investment tool for asset allocation estimated at 85% Our quantitative framework for ownership by usage has two legs: an institutional leg and a retail leg. The Institutional calculations involve 3 steps: 1. Institutional Ownership: first we calculate the institutional ownership per institution type for ETFs and other similar products. 2. Product Usage: we, then, group institutions under their most likely ETF usage. For example, assets owned by Hedge Funds and Brokers would be grouped under Pseudo Futures usage; while assets owned by Investment Advisers and Private Banks/Wealth Management would be grouped under Asset Allocation or Investment usage. The Cash Management usage group, on the other hand, would include ETF institutional ownership by Mutual Funds, Pension Funds, and Insurance Companies, among others. We consider Investment usage as being driven by Asset Allocation purposes; while Pseudo Futures and Cash Management usage as being driven by Non-Asset Allocation purposes. 3. Average Holding Period: now, because not all Investment Advisers use ETFs for Asset Allocation, or not all Hedge Funds use ETFs as Pseudo Futures, we also incorporate an adjustment factor based on the ETF's average holding period. Thus, ETFs with an AHP closer to 30 days or lower would have a larger non-asset allocation component, while ETFs with an AHP closer to 180 days or higher would have a larger asset allocation component. The combination of institutional ownership, product usage, and average holding period can give us a more precise estimate of how much of the institutional ownership is driven by asset allocation or by non-asset allocation purposes. On the retail front we consider that most retail ownership is driven by asset allocation purposes, however we also apply an adjustment based on ETF average holding period in order to calculate a level of non-asset allocation usage among retail investors. As of the end of 2015, we estimate that 85% of ETFs were owned for asset allocation purposes; while only 15% were owned for non-asset allocation purposes. This supports our long-standing belief that ETFs are mostly owned as an investment tool for asset allocation purposes. In fact, we estimate that institutional and retail investors own 47% and 38% of ETF assets for asset allocation purposes, respectively. Furthermore, we estimate that institutions account for the bulk of the non-asset allocation ownership with 12% used for cash management (5%), or pseudo futures-like activities such as risk hedging (7%). On the other hand, we estimate that retail investors account for only 3% of non-asset allocation ETF ownership. ETVs, and ETNs have similar ownership breakdowns with 84% and 86% owned for asset allocation purposes, and 16% and 14% owned for non-asset allocation purposes, respectively. However the non-asset allocation component Page 8 As of the end of 2015, we estimate that 85% of ETFs were owned for asset allocation purposes; while only 15% were owned for non-asset allocation purposes

9 among retail investors is relatively higher than the 3% in ETFs with a 7% in both ETVs and ETNs. Figure 9: 2015 Ownership by usage estimates - ETFs, ETVs, ETNs Source: Deutsche Bank, Bloomberg Finance LP, FactSet Among the major three asset classes, Fixed Income ETFs have the highest asset allocation ETF ownership with 93%; while equity ETFs have the highest nonasset allocation ETF ownership with 17%. This suggests that non-asset allocation ownership within fixed income ETFs at a 7% is in its infancy, and if it were to expand like in the case of Equities or Commodities (14%) we could see anywhere between $30bn to $40bn of additional Fixed Income ETF assets driven just by ETF liquidity demand. We could see anywhere between $30bn to $40bn of additional Fixed Income ETF assets driven by liquidity-induced non-asset allocation ownership Figure 10: 2015 Ownership by usage estimates - Equity, Fixed Income, Commodity Source: Deutsche Bank, Bloomberg Finance LP, FactSet Page 9

10 ETF trading as liquidity tool for non-asset allocation estimated at 86% Most people draw wrong conclusions from the ETF market because they forget that there are two parts to the usage equation, or ETF activity. As we have previously mentioned in this report, ETFs can be used as investment tools for asset allocation, or liquidity tools for trading. Most people get the first part of the equation (i.e. the investment) right, but they usually are less precise in their understanding of the second part: the trading aspect of it. Investors that buy ETFs do so mostly for the exposure, and efficient access; however traders that buy ETFs do so for their liquidity. Yes! traders are buying the ETF liquidity, not so much the exposure. Now don't get us wrong, exposure still matters to traders, but it becomes a secondary decision factor within a group of ETF peers. ETF traders buy the ETF liquidity, not so much the exposure which eventually becomes a secondary decision factor among a group of ETF peers. Previously we estimated that about 15% of ETF ownership is driven by non-asset allocation purposes, but how much of the value traded in ETFs is driven by nonasset allocation purposes The answer will probably come as a surprise to many. We utilized our average holding period calculation to estimate the amount of value traded for asset allocation and non-asset allocation purposes. More specifically, we considered that the value traded for ETFs with an AHP below 30 days was 100% driven by non-asset allocation purposes; while for those ETFs with an AHP over 180 days we assumed 100% driven by asset allocation purposes. ETFs with an AHP between 30 and 180 days would have their value traded split into asset allocation and non-asset allocation proportionately. Based on our methodology, we estimated that 86% of all ETF value traded during 2015 was driven by non-asset allocation purposes. In other words, traders using ETFs as liquidity tools for short term objectives accounted for 86% of ETF trading activity, despite only representing 15% of ETF ownership. Again, with the risk of repeating ourselves, we would like to restate that these traders are mostly institutional investors; furthermore this activity is not the result of excessive trading for the sake of it or an attempt to time the market, but in most cases it is the result of the activity required to fullfil the liquidity demands of institutional market participants. For example, Hedge Funds will demand liquidity for risk management, brokers will demand liquidity for market making activities, and mutual funds will demand liquidity for cash management. ETVs and ETNs present similar readings. We estimate that traders using ETFs as liquidity tools for short term objectives accounted for 86% of ETF trading activity in 2015, despite only representing 15% of ETF ownership Figure 11: 2015 Trading by usage estimates - ETFs, ETVs, ETNs Source: Deutsche Bank, Bloomberg Finance LP, FactSet Page 10

11 ETF evolution insights ETF product evolution theory ETF product evolution has been a favorite topic of discussion in our research reports in recent years. Nevertheless, we present a summary of our theory of ETF Product Evolution as a reminder to the new reader. All ETFs are created equal, but some have the potential to progress to a second or third stage of evolution. Each evolution stage carries specific ETF characteristics and usage implications. 1. First Stage/Asset Allocation: this is the default stage in which all ETFs are created equal as investment tools for asset allocation usage. Moreover, most ETFs actually stay in this first evolution stage forever. At this stage, ETFs are highly dependent on the primary ETF liquidity or the liquidity of the underlying constituent basket. 2. Second Stage/Cash Management: as some ETFs begin to develop size and secondary market liquidity they start to expand their usage alternatives to include cash management functions in addition to asset allocation; thus reaching a second stage of evolution. At this second stage of progression, ETFs become slightly less dependent on primary liquidity, and therefore are better equipped to meet some of investors' non-asset allocation liquidity demands. 3. Third Stage/Pseudo Futures: a more reduced number of ETFs takes evolution one step further to reach a third level in which the ETF enjoys extremely abundant liquidity levels, but not only limited to the ETF itself, but also manifested in ETF options and ETF short interest. In fact, it is this combination of liquidity interactions which turns these ETFs into what we call a Pseudo Futures ETF. A Pseudo Futures ETF is an ETF that is able to handle not only asset allocation, or cash management requirements, but also risk management demands. These ETFs develop liquidity of its own, becoming practically independent of their primary market liquidity. In general, this third stage of evolution is limited to only one ETF per asset class or benchmark. Understanding ETF usage evolution through avg. holding period and flow volatility We found that average holding period for ETFs is a fluid metric which can help understand ETF product evolution. In addition, we noticed that ETF flow volatility patterns can also help understand product evolution. As a matter of fact, as we examine product evolution histories for pseudo futures ETFs we notice two distinct patterns, which at this point we will call the earlier and the latter patterns, respectively. During the earlier pattern, the products are relatively new and usually have higher average holding periods, which may present significant oscillations in the first years as the trading activity accommodates to new asset levels. On the flows side, these products tend to present flat or steady inflow trends as a result of product adoption or investment usage. This is what we call a product evolution seasoning period (most ETFs never pass beyond this period). Page 11

12 In the latter pattern, we notice a sustained and consistent decrease in the average holding period until the average holding period settles usually below trading tool levels (i.e. AHP<30 days). On the flows side, we notice that flow volatility increases as a result of increased ETF usage for short term non-asset allocation activities. This is the final evolution state for an ETF, and so far this seems to be a permanent state once reached. SPY and IWM, two of the most prominent Pseudo Futures ETFs, clearly exhibit these patterns. However, as we examine other ETFs with similar exposures such as IVV and IJR we don't see much evidence of final evolution state. In fact IVV and IJR, both of which at some point displayed some flow volatility and low AHP, have seen an increase in AHP in recent years, particularly IJR. We believe that this suggests an increase in investment usage for asset allocation purposes. This would also confirm that ishares' strategy back in 2012 which designated these ETFs as part of the Core product family has apparently been generating the expected results as more investors seem to be using these products for strategic asset allocation purposes in recent years. On the other hand VOO and VB, which also track similar benchmarks, seem to still be mostly in the first evolution stage as activity is mainly dominated by strategic asset allocation usage (VB flow spikes are related to rebalances). Figure 12: The road to becoming a Pseudo Futures ETF: SPY (Eq US Large Cap) Source: Deutsche Bank, Bloomberg Finance LP. Figure 14: Second stage is the limit: IVV (Eq US LC) Source: Deutsche Bank, Bloomberg Finance LP. Page 12 ishares' strategy back in 2012 which designated IVV and IJR as part of the Core product family has apparently been generating the expected results as more investors seem to be using these products for strategic asset allocation purposes in recent years. Figure 13: The road to becoming a Pseudo Futures ETF: IWM (Eq US Small Cap) Source: Deutsche Bank, Bloomberg Finance LP. Figure 15: Second stage is the limit: IJR (Eq US SC) Source: Deutsche Bank, Bloomberg Finance LP.

13 Figure 16: Mostly an Asset Allocation ETF: VOO (Eq US Large Cap) Source: Deutsche Bank, Bloomberg Finance LP. Figure 17: Mostly an Asset Allocation ETF: VB (Eq US Small Cap) Source: Deutsche Bank, Bloomberg Finance LP. Reading the patterns: trading tools versus asset allocation tools We can also observe extreme usage behaviors in some products. For example, VXX, an ETN which tracks Volatility based on VIX futures contracts, shows a clear trading tool pattern where flows exhibit volatility, and AHP not only begins at a low level (9 days) but drops drastically to a stable level around 1 day. This behavior strongly suggests that products like VXX are almost exclusively used as liquidity tools by traders for non-asset allocation purposes. This finding is very reassuring because it confirms that the product is being used by the right group of users for the right purpose. In addition, this also confirms that concerns about wrong usage of this type of products by less sophisticated investors are overstated; and even if these concerns were to materialize, this would be an exception not the norm. On the other hand, SCHB, an ETF which tracks a broad US market equity index, shows a clear investment tool pattern where flows are very steady and consistent, and AHP increases steadily beyond 200 days staying above that level. This behavior strongly suggests that products like SCHB are almost exclusively used as investment tools for asset allocation purposes, mostly of strategic nature. The pattern also suggests that ETF investors owning this type of products are usually buy-and-hold investors using the ETF as a core building block of their portfolio. Figure 18: Extreme behavior: VXX (Volatility), an almostexclusively trading vehicle Source: Deutsche Bank, Bloomberg Finance LP. Figure 19: Extreme Behavior: SCHB (US Broad), an almost-exclusively asset allocation vehicle Source: Deutsche Bank, Bloomberg Finance LP. Page 13

14 A look at other asset classes: Real Estate and HY Credit These patterns can be seen across all products and asset classes. Thus, as a last exercise to help us exemplify the value that this information can provide for understanding ETF usage, we take a look at some US Real Estate and HY Corporate Credit ETFs. VNQ and IYR are two very popular ETFs offering exposure to US Real Estate via US REITs. VNQ with more than $35bn in assets is the largest Real Estate ETF and has very good liquidity; however IYR, despite the fact of being more than 7 times smaller than VNQ in terms of assets, is even more liquid. A fact which could be easily understood after looking at the flow volatility and AHP patterns. Actually, VNQ has a steady stream of flows, and an AHP above 100 days; characteristic of an ETF being used as an asset allocation tool - mostly strategically with some tactical usage. On the other hand, IYR displays a clear pattern of flow volatility with a very low AHP (~10 days) representative of an ETF being used as a trading tool, and very characteristic of Pseudo Futures. Figure 20: The Pseudo Futures ETF for US Real Estate: IYR Source: Deutsche Bank, Bloomberg Finance LP. Figure 21: Despite being the largest US Real Estate ETF, VNQ only has 2nd stage potential Source: Deutsche Bank, Bloomberg Finance LP. Within HY Corporate debt ETFs, the space activity in assets as well as in trading is clearly dominated by two ETFs: HYG and JNK. However, as we have stated before, there is usually room only for one Pseudo Futures ETF per asset class. Then, which of these two ETFs is the Pseudo Futures for the asset class. We usually deem HYG as the Pseudo Futures one, but is this designation confirmed by the flow and AHP patterns We observe that in both cases there is flow volatility and a consistent downward trend in AHP. However, although in both cases the AHP is relatively low, the AHP of HYG is lower at about 20 days compared to JNK's AHP of just under 40 days. Therefore we can confirm that although both products are heavily used as liquidity tools, HYG maintains its Pseudo Futures title. We believe that HYG's edge is probably due to its options activity; for example, in July HYG traded an average daily notional value of $403mn - almost 100 times more than JNK options. Page 14

15 Figure 22: The Pseudo Futures ETF for US HY Corporate Credit: HYG Source: Deutsche Bank, Bloomberg Finance LP. Figure 23: Despite impressive activity, JNK is still one evolution step behind HYG Source: Deutsche Bank, Bloomberg Finance LP. Page 15

16 Appendix A: Definitions ETP Universe Definitions Exchange-Traded Products (ETPs) We define an exchange-traded product (ETP) as a secure (funded or collateralized) open-ended exchange-traded equity with no embedded optionality and marketwide appeal to investors. This includes exchange traded funds (ETF), and exchange-traded vehicles (ETV). The vast majority of instruments are ETFs (~98% in AUM). Exchange-Traded Funds (ETFs) ETFs are open-ended funds which are listed on an exchange and offer intra-day dual liquidity to access diversified investments in a transparent, cheap, and tax efficient way. ETFs indexed to equity and fixed income benchmarks are registered under the investment company act of Only physical index replication techniques are permissible by this legislation while synthetic replication is not allowed. Exchange-Traded Vehicles (ETVs) This terminology typically refers to grantor trusts that exist in the US market. These instruments track primarily commodity benchmarks. They differ from ETFs in that they are registered under the Securities Act of 1933 and not the Investment Company Act of 1940, hence they are not classed as funds. Vehicles that replicate commodity benchmarks, more often known as pools, and funds targeting alternative index returns are formed under the Commodities Exchange Act and are listed under the 33 Securities Act, and report under 34 Corporate Act. Exchange-Traded Notes (ETNs) ETNs are senior, unsecured, unsubordinated debt securities issued by an underwriting bank. As a debt obligation these are not funded, therefore performance delivery depends on the credit worthiness of the issuer. They usually track an index and are listed on an exchange. Like most debt securities, they also have a maturity date. Management Style or Product Strategy Definitions Beta This is the main group with the largest number of products and assets. Within this category we account for all those ETFs that track an index which employs a market capitalization weighting methodology, and a simple selection methodology usually involving screenings such as minimum market cap and liquidity levels, or profitability levels. ETFs in this group are also referred to as plain-vanilla ETFs. Some examples of indices falling within this category are: S&P 500, S&P 400, S&P 600, MSCI EAFE, MSCI EM, Russell 2000, and Russell 1000, to name a few. Beta+ In this group we include every product that offers any level of leverage or inverse implementation. For example, an ETF offering access to twice the daily returns of the S&P 500 on either direction (long or short) would be classified under this category. Page 16

17 Active Classifying products in this group is still easy; basically if the ETF doesn t track any index then we classify the fund as active. Enhanced Beta (aka Smart Beta) This category is reserved for those ETFs that also track an index, but which follow more elaborated strategies. After defining an index universe, there are two main levers that determine most of the risk/return profile of the index: (1) the selection criteria, and (2) the weighting criteria. In their selection process, enhanced beta ETFs usually employ additional screening processes and scoring systems involving multiple factors beyond just minimum market cap and liquidity levels. For example, they could include growth or value scores, dividends paid or dividend yield, earnings, volatility, or momentum screens, to name a few. The weighting methodology of enhanced beta ETFs is usually anything but market cap weighted, it can include simple equal weighting or variations of it, optimized weights, and other metric-specific weights such as those based on dividends paid, inverse volatility, dividend yield, fundamental multi factor scores, earnings, and revenues, to name a few. An enhanced beta ETF will either have a nontraditional selection methodology, a non-traditional weighting methodology, or a combination of both. Product Type Definitions Asset Allocation ETFs This group covers all ETFs with exception of levered and inverse products. These are usually good products for market access strategies, portfolio completion, and core positions. They are also efficient building blocks for multi asset strategies. When selecting these products, major emphasis should be set on the desired exposure, tracking efficiency, primary liquidity (i.e. the liquidity of the underlying basket), and cost. Cash Management ETFs This group covers a more selected group of ETFs which in addition to being good asset allocation tools, also serves a series of cash management portfolio needs. For example, these products are very good for equitizing cash between transitions, around reporting periods (window dressing), and during tax loss harvesting. These ETFs usually have good liquidity, large fund size, and low cost, all of which makes it easier to execute sizeable short-term transactions, therefore secondary market liquidity and fund size tend to be a more relevant factor compared to asset allocation ETFs. The most popular asset allocation usage of these funds is as core building blocks. Pseudo Futures ETFs This group covers an even more selected sample of ETFs which in addition to being good asset allocation and cash management tools can also be used for fulfilling risk management functions such as risk hedging, portable alpha strategies, or tactical shorts. Many times they also trade at a cheaper level than their underlying basket, and offer large amounts of liquidity which can make them attractive for market making activities as well. Secondary and short liquidity (ease to borrow), and fund size tend to be more relevant characteristics at the moment of selecting this type of ETFs. There is usually no more than one pseudo futures ETF per asset class. The most popular asset allocation usage of these funds is among portfolios that require more liquidity given their size or more tactical nature. Page 17

18 Appendix 1 Important Disclosures Additional information available upon request *Prices are current as of the end of the previous trading session unless otherwise indicated and are sourced from local exchanges via Reuters, Bloomberg, and other vendors. Other information is sourced from Deutsche Bank, subject companies, and other sources. For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at Analyst Certification The views expressed in this report accurately reflect the personal views of the undersigned lead analyst(s). In addition, the undersigned lead analyst(s) has not and will not receive any compensation for providing a specific recommendation or view in this report. Sebastian Mercado Hypothetical Disclaimer Backtested, hypothetical or simulated performance results have inherent limitations. Unlike an actual performance record based on trading actual client portfolios, simulated results are achieved by means of the retroactive application of a backtested model itself designed with the benefit of hindsight. Taking into account historical events the backtesting of performance also differs from actual account performance because an actual investment strategy may be adjusted any time, for any reason, including a response to material, economic or market factors. The backtested performance includes hypothetical results that do not reflect the reinvestment of dividends and other earnings or the deduction of advisory fees, brokerage or other commissions, and any other expenses that a client would have paid or actually paid. No representation is made that any trading strategy or account will or is likely to achieve profits or losses similar to those shown. Alternative modeling techniques or assumptions might produce significantly different results and prove to be more appropriate. Past hypothetical backtest results are neither an indicator nor guarantee of future returns. Actual results will vary, perhaps materially, from the analysis. Equity rating key Equity rating dispersion and banking relationships Buy: Based on a current 12- month view of total shareholder return (TSR = percentage change in share price from current price to projected target price plus pro-jected dividend yield ), we recommend that investors buy the stock. Sell: Based on a current 12-month view of total shareholder return, we recommend that investors sell the stock Hold: We take a neutral view on the stock 12-months out and, based on this time horizon, do not recommend either a Buy or Sell. Newly issued research recommendations and target prices supersede previously published research. Regulatory Disclosures 1.Additional Information Page 18

19 Information on ETFs is provided strictly for illustrative purposes and should not be deemed an offer to sell or a solicitation of an offer to buy shares of any fund that is described in this document. Consider carefully any fund's investment objectives, risk factors, and charges and expenses before investing. This and other information can be found in the fund's prospectus. Prospectuses about db X-trackers funds and Powershares DB funds can be obtained by calling or by visiting Read prospectuses carefully before investing. Past performance is not necessarily indicative of future results. Investing involves risk, including possible loss of principal. To better understand the similarities and differences between investments, including investment objectives, risks, fees and expenses, it is important to read the products' prospectuses. Shares of ETFs may be sold throughout the day on an exchange through any brokerage account. However, shares may only be redeemed directly from an ETF by authorized participants, in very large creation/redemption units. Transactions in shares of ETFs will result in brokerage commissions and will generate tax consequences. ETFs are obliged to distribute portfolio gains to shareholders. Deutsche Bank may be an issuer, advisor, manager, distributor or administrator of, or provide other services to, an ETF included in this report, for which it receives compensation. db X-trackers and Powershares DB funds are distributed by ALPS Distributors, Inc. The opinions expressed are those of the authors and do not necessarily reflect the views of DB, ALPS or their affiliates. Aside from within this report, important conflict disclosures can also be found at under the "Disclosures Lookup" and "Legal" tabs. Investors are strongly encouraged to review this information before investing. 2. Short-Term Trade Ideas Deutsche Bank equity research analysts sometimes have shorter-term trade ideas (known as SOLAR ideas) that are consistent or inconsistent with Deutsche Bank's existing longer term ratings. These trade ideas can be found at the SOLAR link at Page 19

20 Additional Information The information and opinions in this report were prepared by Deutsche Bank AG or one of its affiliates (collectively "Deutsche Bank"). Though the information herein is believed to be reliable and has been obtained from public sources believed to be reliable, Deutsche Bank makes no representation as to its accuracy or completeness. If you use the services of Deutsche Bank in connection with a purchase or sale of a security that is discussed in this report, or is included or discussed in another communication (oral or written) from a Deutsche Bank analyst, Deutsche Bank may act as principal for its own account or as agent for another person. Deutsche Bank may consider this report in deciding to trade as principal. It may also engage in transactions, for its own account or with customers, in a manner inconsistent with the views taken in this research report. Others within Deutsche Bank, including strategists, sales staff and other analysts, may take views that are inconsistent with those taken in this research report. Deutsche Bank issues a variety of research products, including fundamental analysis, equity-linked analysis, quantitative analysis and trade ideas. Recommendations contained in one type of communication may differ from recommendations contained in others, whether as a result of differing time horizons, methodologies or otherwise. Deutsche Bank and/or its affiliates may also be holding debt or equity securities of the issuers it writes on. Analysts are paid in part based on the profitability of Deutsche Bank AG and its affiliates, which includes investment banking revenues. Opinions, estimates and projections constitute the current judgment of the author as of the date of this report. They do not necessarily reflect the opinions of Deutsche Bank and are subject to change without notice. Deutsche Bank research analysts sometimes have shorter-term trade ideas that are consistent or inconsistent with Deutsche Bank's existing longer term ratings. These trade ideas for equities can be found at the SOLAR link at A SOLAR idea represents a high conviction belief by an analyst that a stock will outperform or underperform the market and/or sector delineated over a time frame of no less than two weeks. In addition to SOLAR ideas, the analysts named in this report may have from time to time discussed with our clients, including Deutsche Bank salespersons and traders, or may discuss in this report or elsewhere, trading strategies or ideas that reference catalysts or events that may have a near-term or mediumterm impact on the market price of the securities discussed in this report, which impact may be directionally counter to the analysts' current 12-month view of total return as described herein. Deutsche Bank has no obligation to update, modify or amend this report or to otherwise notify a recipient thereof if any opinion, forecast or estimate contained herein changes or subsequently becomes inaccurate. Coverage and the frequency of changes in market conditions and in both general and company specific economic prospects makes it difficult to update research at defined intervals. Updates are at the sole discretion of the coverage analyst concerned or of the Research Department Management and as such the majority of reports are published at irregular intervals. This report is provided for informational purposes only. It is not an offer or a solicitation of an offer to buy or sell any financial instruments or to participate in any particular trading strategy. Target prices are inherently imprecise and a product of the analyst s judgment. The financial instruments discussed in this report may not be suitable for all investors and investors must make their own informed investment decisions. Prices and availability of financial instruments are subject to change without notice and investment transactions can lead to losses as a result of price fluctuations and other factors. If a financial instrument is denominated in a currency other than an investor's currency, a change in exchange rates may adversely affect the investment. Past performance is not necessarily indicative of future results. Unless otherwise indicated, prices are current as of the end of the previous trading session, and are sourced from local exchanges via Reuters, Bloomberg and other vendors. Data is sourced from Deutsche Bank, subject companies, and in some cases, other parties. The Deutsche Bank Research Department is independent of other business areas divisions of the Bank. Details regarding our organizational arrangements and information barriers we have to prevent and avoid conflicts of interest with respect to our research is available on our website under Disclaimer found on the Legal tab. Macroeconomic fluctuations often account for most of the risks associated with exposures to instruments that promise to pay fixed or variable interest rates. For an investor who is long fixed rate instruments (thus receiving these cash flows), increases in interest rates naturally lift the discount factors applied to the expected cash flows and thus cause a loss. The longer the maturity of a certain cash flow and the higher the move in the discount factor, the higher will be the loss. Upside surprises in inflation, fiscal funding needs, and FX depreciation rates are among the most common adverse Page 20

21 macroeconomic shocks to receivers. But counterparty exposure, issuer creditworthiness, client segmentation, regulation (including changes in assets holding limits for different types of investors), changes in tax policies, currency convertibility (which may constrain currency conversion, repatriation of profits and/or the liquidation of positions), and settlement issues related to local clearing houses are also important risk factors to be considered. The sensitivity of fixed income instruments to macroeconomic shocks may be mitigated by indexing the contracted cash flows to inflation, to FX depreciation, or to specified interest rates these are common in emerging markets. It is important to note that the index fixings may -- by construction -- lag or mis-measure the actual move in the underlying variables they are intended to track. The choice of the proper fixing (or metric) is particularly important in swaps markets, where floating coupon rates (i.e., coupons indexed to a typically short-dated interest rate reference index) are exchanged for fixed coupons. It is also important to acknowledge that funding in a currency that differs from the currency in which coupons are denominated carries FX risk. Naturally, options on swaps (swaptions) also bear the risks typical to options in addition to the risks related to rates movements. Derivative transactions involve numerous risks including, among others, market, counterparty default and illiquidity risk. The appropriateness or otherwise of these products for use by investors is dependent on the investors' own circumstances including their tax position, their regulatory environment and the nature of their other assets and liabilities, and as such, investors should take expert legal and financial advice before entering into any transaction similar to or inspired by the contents of this publication. The risk of loss in futures trading and options, foreign or domestic, can be substantial. As a result of the high degree of leverage obtainable in futures and options trading, losses may be incurred that are greater than the amount of funds initially deposited. Trading in options involves risk and is not suitable for all investors. Prior to buying or selling an option investors must review the "Characteristics and Risks of Standardized Options, at If you are unable to access the website please contact your Deutsche Bank representative for a copy of this important document. Participants in foreign exchange transactions may incur risks arising from several factors, including the following: ( i) exchange rates can be volatile and are subject to large fluctuations; ( ii) the value of currencies may be affected by numerous market factors, including world and national economic, political and regulatory events, events in equity and debt markets and changes in interest rates; and (iii) currencies may be subject to devaluation or government imposed exchange controls which could affect the value of the currency. Investors in securities such as ADRs, whose values are affected by the currency of an underlying security, effectively assume currency risk. Unless governing law provides otherwise, all transactions should be executed through the Deutsche Bank entity in the investor's home jurisdiction. United States: Approved and/or distributed by Deutsche Bank Securities Incorporated, a member of FINRA, NFA and SIPC. Analysts employed by non-us affiliates may not be associated persons of Deutsche Bank Securities Incorporated and therefore not subject to FINRA regulations concerning communications with subject companies, public appearances and securities held by analysts. Germany: Approved and/or distributed by Deutsche Bank AG, a joint stock corporation with limited liability incorporated in the Federal Republic of Germany with its principal office in Frankfurt am Main. Deutsche Bank AG is authorized under German Banking Law and is subject to supervision by the European Central Bank and by BaFin, Germany s Federal Financial Supervisory Authority. United Kingdom: Approved and/or distributed by Deutsche Bank AG acting through its London Branch at Winchester House, 1 Great Winchester Street, London EC2N 2DB. Deutsche Bank AG in the United Kingdom is authorised by the Prudential Regulation Authority and is subject to limited regulation by the Prudential Regulation Authority and Financial Conduct Authority. Details about the extent of our authorisation and regulation are available on request. Hong Kong: Distributed by Deutsche Bank AG, Hong Kong Branch. India: Prepared by Deutsche Equities India Pvt Ltd, which is registered by the Securities and Exchange Board of India (SEBI) as a stock broker. Research Analyst SEBI Registration Number is INH DEIPL may have received administrative warnings from the SEBI for breaches of Indian regulations. Page 21