A Guide to Value ETF DNA

Deutsche Bank Markets Research North America United States Synthetic Equity & Index Strategy Date 17 August 2017 A Guide to Value ETF DNA Making sense of all the different Value ETFs In this report we review all of the Value ETFs with focus on US Large Cap Equities. Overall, we identify 26 different products with about $100bn in assets. Value ETFs are designed to track indices with a focus on cheap stocks, however the path each of these indices takes to get to that goal can differ significantly. We identify three main groups of Value ETFs with similar characteristics: Style Mix, Style Pure, and Factor Tilt. Sebastian Mercado, CFA Strategist +1-212-250-8690 Value ETFs have indeed a Value bias and a clear Financials tilt Unlike other ETFs where the name is not always aligned with the true product exposure, all Value ETFs indeed deliver exposure to Value stocks. The level of exposure, however, can vary among different Value ETF types. For example, Style Pure and Factor Tilt exhibit a higher level of exposure to Value factors relative to Style Mix. The most popular value metrics are those involving Book Value, followed by those involving Earnings, Sales, Dividends, and Cash Flows. Value ETFs usually have below average P/B, P/E, P/Sales, and P/Cash Flows ratios; and above average dividend yield. Moreover, all Value ETF types coincide on Financials being their top sector allocation with a significant overweight relative to a US Equity Large Cap benchmark, while having a clear underweight on Technology. However, there are more sector insights beyond these more obvious observations. Value is in the eye of the beholder Although quantifiable, the right Value exposure depends on how you define Value. Thus, the available Value ETFs provide plenty of alternatives to meet different investors' definitions and preferences. If you want something like the headline index, but with some Value bias given from sector tilts, then one of the Style Mix ETFs may be the answer. Or maybe you want something with a more exclusive basket of Value stocks, then a Style Pure may be what you need. Or maybe you want to keep a similar sector exposure as the headline index, but with a clear Value bias, or a more concentrated Value play, then a Factor Tilt may be what you are looking for. You even have ETFs for those who want pure long/short factor exposure and active management. Furthermore, you may want something more traditional that uses just Book Value-based metrics, or maybe you want a more elaborate Value metric involving a composite of multiple figures. Deutsche Bank Securities Inc. Distributed on: 18/08/2017 00:48:07 GMT 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) 083/04/2017. 0bed7b6cf11c

Table Of Contents Value ETFs... 3 US Equity Value ETFs Overview... 3 Methodologies in-depth... 7 Performance Review... 9 True Exposures... 10 Page 2 Deutsche Bank Securities Inc.

Value ETFs US Equity Value ETFs Overview Value ETFs have existed for a long time, over 17 years to be more specific. However, as ETFs have become more popular among investors, and as strategies have developed beyond the initial indexing guidelines common among plain vanilla indices, we have seen a clear increase in investors' interest and ETF providers for Value ETFs. In fact, as of August 9 th of the current year there were 26 ETFs with Value focus tracking US Large Cap equity indices 1, accounting for almost $100bn in assets. Moreover, in the last 6 years, assets in these Value ETFs have grown about 5 times. Value ETFs are usually designed as a vehicle to access cheap stocks, but thinking that all of them are the same thing would be like thinking that all houses are the same because their common objective is to provide shelter. Last time we checked, houses vary in many different ways, and so do Value ETFs. Most Value ETF construction processes take into consideration popular value factors such as price to book value ratio valuations, and in fact all of the Value ETFs featured in this report exhibit a clear value bias when compared to a traditional US Large Cap Equity benchmark such as the S&P 500 Index 2. Nevertheless, there can be significant differences in terms of the number and combination of factors, and the selection and the weighting of constituents. Fortunately, despite the differences, we can still identify some common types of Value ETFs that allow us to better understand the risk and return profile of these funds. Style Mix: An attempt to define Value The first generation of Value ETFs was based on Style indices with Value focus. These indices were usually variations of popular benchmarks that would employ a value-based selection process to identify companies with some level of Value characteristics while filtering out companies with weak value metrics (usually Growth companies), after which the remaining companies would be weighted by free float market cap or by free float market cap with a value score adjustment. The result was an index similar to the parent index but with a Value bias. In addition, because style mix indices usually cover all the parent index market cap, you could still find companies with partial growth characteristics in these Value indices. This is the largest segment among Value ETFs, representing 89% of the assets. Popular examples of the indices tracked by these ETFs are: the Russell 1000 Value Index, the CRSP US Large Cap Value Index, and the S&P 500 Value index. Style Pure: Distilling Value The second generation of Value indices was built on the back of many of the concepts considered within the Style Mix framework, but dealt specifically with the issue of companies with mixed Value/Growth profiles. Style Pure indices don't necessarily cover all of the constituents of the parent index nor focus on market cap allocations either. In fact, because Style Pure indices focus on companies that only exhibit Value characteristics, they have smaller constituent count relative to Style Mix indices. In addition, because the weighting criteria usually shifts from the free float market cap standard to other criteria based on Value scores or other 1 In this report we focus exclusively on Large Cap ETFs, or ETFs with a 50%+ allocation to Large Caps. 2 The SPDR S&P 500 ETF (SPY) is used as the benchmark proxy for all benchmark comparisons in this report. Deutsche Bank Securities Inc. Page 3

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017* AUM $MM # of ETFs 17 August 2017 alternative weighting methodologies, Style Pure indices can enhanced the Value tilt even further. This is the second-largest segment among Value ETFs with about 8% of the assets. Popular examples of the indices tracked by these ETFs are: the Dow Jones U.S. Large Cap Value Total Stock Market Index, The Dynamic Large Cap Value Intellidex Index, and the NASDAQ AlphaDEX Large Cap Value Index. Factor Tilt: Fine Tuning Value Although traditional Style Mix indices would be what we call the first Smart Beta products and there were other Smart Beta lineups developed during the last decade, it wasn't until earlier on this decade when the Smart Beta concept and Factor Investing began to become more relevant on the ETF agenda. These new ETFs powered by Factor Tilt indices provide a way to access different thoroughly researched and documented market anomalies such as the Value Factor anomaly where you would buy cheap stocks and sell expensive stocks. However because these indices can only take long positions, there are no short positions and that is why we call them "Factor Tilt" as these indices would not offer "pure" factor exposure but rather a combination of market beta and value bias. The selection and the weighting processes among these indices tend to rely even more heavily on value factors, which usually yields a stronger Value bias than in the previous groups. This segment is still small, but growing, accounting for about 3% of the US Equity Large Cap Value ETF assets. The most popular index among these ETFs is the MSCI USA Value Weighted Index. Other: Pure Factor and Active The previous three groups make almost the entirety of the assets in the space, but there are still some interesting ETFs to mention in the group. Pure factor ETFs track indices with both long and short positions in an attempt to deliver a cleaner access to the factor returns while removing market exposure. While Active ETFs employ a Value investing philosophy without following any specific index or written guidelines, they offer more of an alternative for those seeking stock picking skills rather than plain beta exposure. Figure 1: Annual Historical AUM and # of US Eq. Value ETFs growth 120,000 100,000 30 25 Figure 2: AUM Market Share per Value ETF Type Style Pure 8% Factor Tilt 3% Other 0% 80,000 60,000 40,000 20 15 10 Style Mix Style Pure Factor Tilt 20,000 5 Other 0 0 Style Mix 89% Style Mix Style Pure Factor Tilt Other # of Products Source: Deutsche Bank, Bloomberg Finance LP. *2017 as of 9-Aug-17. # of ETFs only includes currently listed products. Source: Deutsche Bank, Bloomberg Finance LP. Data as of 9-Aug-2017. Page 4 Deutsche Bank Securities Inc.

All Value ETF types have indeed a Value bias Regardless of the differences, all types have a clear Value bias. For example, the Value ETF type averages for some common value metrics such as price-to-book, price-to-earnings, price-to-sales, and price-to-cash flow are all lower than those of a US Large Cap Equity benchmark, suggesting that Value ETFs indeed focus on cheaper stocks. In addition, all of these groups also have a higher dividend yield relative to the benchmark, strengthening even further the "cheap stock" argument. From a factor sensitivity perspective, all of these segments also present higher sensitivities to the Value factor 3 relative to the benchmark; in addition to higher sensitivities to the dividend yield factor. Lastly some of these Value ETFs may present a Size bias relative to the benchmark, which is something that investor should also keep in mind when deciding on what Value ETF to use. Figure 3: Aggregate Value Factor & Axioma Factor Metrics per Value ETF types Value ETF Types P / Book Value Common Value Metrics (Avg.) P / Earnings Avg. Div. Yield % Avg. P / Sales Avg. P / Cash Flow Axioma Factor Betas (Avg.) Value Dividend Yield Style Mix 2.13 21.32 2.49 1.57 11.91 0.33 0.04 0.12 Style Pure 1.96 18.31 2.41 1.24 10.07 0.51 0.07 (0.03) Factor Tilt 2.17 16.61 2.18 1.00 9.43 0.57 (0.05) 0.06 S&P 500 ETF 3.19 23.38 1.98 2.12 14.18 0.02 (0.24) 0.16 Source: Deutsche Bank, Bloomberg Finance LP, Axioma. Data as of 9-Aug-2017. Size Value ETFs have a clear Financials sector tilt All Value ETF types coincide on Financials being their top sector allocation with a significant overweight relative to the benchmark; while having a clear underweight on Technology. However, there are more sector insights beyond these more obvious observations. For example, Style Pure and Factor Tilt ETFs have a more similar sector exposure than Style Mix ETFs with any of the other Value ETF groups. In the case of Style Pure and Factor Tilt products, Consumer Discretionary and Technology are among the top 3 sectors, but for Style Mix ETFs these sectors fall to 6 th and 8 th place, respectively. Furthermore, Style Mix ETFs have the highest allocation to Energy, and the lowest allocations to Consumer Discretionary and Technology from among all Value ETF types and the benchmark. Figure 4: Sector Exposure Rankings per Aggregate Value ETF types Rank Style Mix Style Pure Factor Tilt S&P 500 ETF 1 Financials 26.6% Financials 27.0% Financials 23.6% Technology 23.0% 2 Health Care 13.6% Cons. Disc. 12.0% Cons. Disc. 18.9% Financials 14.6% 3 Cons. Staples 10.4% Technology 10.9% Technology 13.7% Health Care 14.2% 4 Energy 9.7% Industrials 9.8% Health Care 12.5% Cons. Disc. 12.2% 5 Industrials 9.4% Health Care 9.4% Cons. Staples 9.3% Industrials 10.1% 6 Technology 8.9% Cons. Staples 8.5% Industrials 8.3% Cons. Staples 8.6% 7 Utilities 6.1% Utilities 8.3% Energy 4.6% Energy 5.9% 8 Cons. Disc. 5.8% Energy 5.7% Utilities 3.6% Utilities 3.2% 9 Telecom 3.8% Telecom 3.7% Materials 2.7% Real Estate 2.9% 10 Materials 3.3% Materials 3.4% Real Estate 1.5% Materials 2.9% 11 Real Estate 2.2% Real Estate 1.5% Telecom 1.3% Telecom 2.2% Source: Deutsche Bank, Bloomberg Finance LP. Data as of 9-Aug-2017. Sector exposures are averages within each group. 3 Factor sensitivities or betas are sourced from Axioma's US Fundamental model. The value factor is defined as a composite of book-to-price, earnings-to-price, and future earnings-to-price. Deutsche Bank Securities Inc. Page 5

Page 6 Deutsche Bank Securities Inc. Figure 5: List and Details of US Equity Value ETFs Ticker ETF Name Listing Date TER Issuer AUM 20D ADV Implied Total Avg. Bid/Ask Spreads $MM $M Liq. $M Liq. $ 5-Day $ 5-Day bps Style Mix IWD ishares Russell 1000 Value ETF 22-May-00 0.20% BlackRock 36,552 189 4,496 4,685 0.01 0.9 VTV Vanguard Value ETF 30-Jan-04 0.06% Vanguard 32,452 90 4,290 4,380 0.01 1.1 IVE ishares S&P 500 Value ETF 26-May-00 0.18% BlackRock 13,592 60 450 510 0.01 1.0 IUSV ishares Core S&P U.S. Value ETF 24-Jul-00 0.05% BlackRock 2,363 17 3,885 3,901 0.04 7.1 MGV Vanguard Mega Cap Value ETF 21-Dec-07 0.07% Vanguard 1,714 5 3,578 3,583 0.05 6.5 VONV Vanguard Russell 1000 Value ETF 22-Sep-10 0.12% Vanguard 1,150 5 4,477 4,482 0.04 3.9 VOOV Vanguard S&P 500 Value ETF 9-Sep-10 0.15% Vanguard 776 2 3,577 3,579 0.14 14.0 SPYV SPDR S&P 500 Value ETF 29-Sep-00 0.15% State Street 351 1 3,580 3,581 0.31 27.0 IWX ishares Russell Top 200 Value ETF 25-Sep-09 0.20% BlackRock 244 0 3,063 3,063 0.05 9.8 NULV NuShares ESG Large-Cap Value ETF 14-Dec-16 0.35% Nuveen 13 0 1,383 1,383 0.17 62.9 Style Pure SCHV Schwab U.S. Large-Cap Value ETF 11-Dec-09 0.04% Charles Schwab 3,580 12 5,561 5,572 0.02 3.6 PWV PowerShares Dynamic Large Cap Value Portfolio 3-Mar-05 0.57% PowerShares 1,325 4 1,340 1,344 0.02 4.2 FTA First Trust Large Cap Value AlphaDEX Fund 10-May-07 0.62% First Trust 1,055 4 1,363 1,366 0.02 4.6 RPV Guggenheim S&P 500 Pure Value ETF 7-Mar-06 0.35% Guggenheim Inv. 884 4 310 4 0.02 2.5 JKF ishares Morningstar Large-Cap Value ETF 28-Jun-04 0.25% BlackRock 884 4 2,188 315 0.02 2.5 FAB First Trust Multi Cap Value AlphaDEX Fund 10-May-07 0.68% First Trust 106 0 346 347 0.15 29.4 PXLV PowerShares Russell Top 200 Pure Value Portfolio 16-Jun-11 0.39% PowerShares 73 0 625 5 0.10 27.7 EZY WisdomTree US LargeCap Value Fund 23-Feb-07 0.38% WisdomTree 45 0 621 11 0.12 16.3 Factor Tilt VLUE ishares Edge MSCI USA Value Factor ETF 18-Apr-13 0.15% BlackRock 2,435 23 1,518 1,541 0.03 3.6 QVAL ValueShares US Quantitative Value ETF 22-Oct-14 0.79% Empowered Funds 68 0 272 273 0.08 30.5 SPVU PowerShares S&P 500 Enhanced Value Portfolio 9-Oct-15 0.25% PowerShares 52 0 2,405 2,406 0.04 12.7 FVAL Fidelity Value Factor ETF 15-Sep-16 0.29% Fidelity Investments 40 0 831 831 0.06 19.5 VLU SPDR S&P 1500 Value Tilt ETF 25-Oct-12 0.12% State Street 9 0 1,679 1,679 0.58 62.0 SPVM PowerShares S&P 500 Value with Momentum Portfolio 6-Apr-17 0.30% PowerShares 3 0 536 536 0.08 30.6 Pure Factor CHEP QuantShares U.S. Market Neutral Value Fund 12-Sep-11 0.75% QuantShares 1 0 58 58 1.05 448.2 Active SYV SPDR MFS Systematic Value Equity ETF 9-Jan-14 0.60% State Street 6 0 438 438 0.18 28.9 Source: Deutsche Bank, Bloomberg Finance LP. Data as of 9-Aug-2017. TERs are net of any waivers, if applicable. 17 August 2017

Comments on liquidity profiles for Value ETFs The majority of these ETFs have liquid underlying baskets with US-listed, large cap, and liquid securities, therefore none of them, with the exception of CHEP, should face problems to trade long institutional size orders under normal market conditions. CHEP's liquidity is not necessarily prohibitive, but has a short leg, and therefore other considerations may apply. Most products have sufficient liquidity to implement strategic asset allocation positions, while a few of them such as IWD, VTV, IVE, VLUE, IUSV, and SCHV could also implement long tactical trades efficiently. None of them is really ideal for shorting Value, nor is expected to function as a price discovery vehicle or pseudo futures under market stress, although IWD would probably be the closest candidate. Bottom line, these Value ETFs are good investment tools, but may not meet the standards of other ETFs also used as liquidity tools such as SPY, QQQ, and IWM. Methodologies in-depth Price to Book Value is the most common value metric among Value ETFs When it comes to methodologies, we first need to understand what are some of the common Value factors defined by the many different index rules. In general, most value factors involve ratios between the price of a stock and a fundamental metric from the income statement or balance sheet. The most popular fundamental metric is Book Value, with all but one of the passive Value ETFs featured in this report taking this metric into consideration. Beyond Book Value, Earnings-based metrics are the second most popular metrics; earnings metrics can take many forms by focusing on past or trailing, and future or projected figures. Next are Sales, followed by Dividend, and cash flow-based metrics. Some indices try to be more unique by exploring other less common value metrics, such as the index underlying QVAL, which employs an enterprise multiple defined as Enterprise Value divided by EBIT (Earnings Before Interest and Taxes). Selection is mostly a process based on Value Scores Filtering or selecting the index constituents is usually a process based on Value Scores. This is particularly the case for Style Mix and Style Pure ETFs, while Factor Tilt ETFs are more likley to add other considerations. In addition, some indices such as those tracked by Style Mix ETFs may have constituents that are present in both Value and Growth indices, while Style Pure ETF indices aim to avoid any index overlap. Factor Tilt ETF index membership can vary from indices that include all the constituents, to indices that focus on a specific number of top-ranked value companies, to indices that may allow overlap. Some methodologies may add sector filters such as that of QVAL's index, which excludes Financials and Real Estate, or NULV's index, which adds an ESG screening on the selection. All indices, with the exception of CHEP, only take long positions. Value score weighting with sector constraints can enhance value tilt while keeping sectors exposures in check Weighting methodologies can vary significantly among Value ETF types. Style Mix Value ETFs usually track indices that employ free float market capitalization very much like their parent index, or that add a proportional adjustment to FF Mkt Cap based on value scores. Style Pure ETF indices make an attempt to deviate from the traditional market cap weighting methodologies by using alternative weighting methodologies based on value scores, or tier-based equal weighting. Finally, Factor Tilt indices employ mostly alternative weighting methodologies which involve value score weighting, optimization, and sector controls. Deutsche Bank Securities Inc. Page 7

Page 8 Deutsche Bank Securities Inc. Figure 6: Methodology Details of US Equity Value ETFs Ticker Selection Stock Membership Weighting Value factors (mostly ratios relative to price) Style Mix IWD FTSE Russell Russell 1000 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value VTV CRSP CRSP US Large Cap Value Value Score Overlap FF Mkt Cap Book Value, Earnings (Fut, Hist), Dividend, Sales IVE S&P Dow Jones S&P 500 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value, Earnings, Sales IUSV S&P Dow Jones S&P 900 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value, Earnings, Sales MGV CRSP CRSP US Mega Cap Value Value Score Overlap FF Mkt Cap Book Value, Earnings (Fut, Hist), Dividend, Sales VONV FTSE Russell Russell 1000 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value VOOV S&P Dow Jones S&P 500 Value Value Score Overlap FF Mkt Cap Book Value, Earnings, Sales SPYV S&P Dow Jones S&P 500 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value, Earnings, Sales IWX FTSE Russell Russell Top 200 Value Value Score Overlap FF Mkt Cap x Value Score Adj. Book Value NULV Style Pure SCHV Index Provider MSCI S&P Dow Jones Index Name TIAA ESG USA Large-Cap Value Dow Jones U.S. Large Cap Value Total Stock Market Value Score, ESG, Carbon Overlap Style Score No Overlap FF Mkt Cap Opt. w/constraints on FF Mkt Cap x Value Score Adj. Book Value, Earnings (Fut), Dividend. Fut. Earnings (ratio, growth), Book Value (cur), Dividend (cur), Revenue (trail), Earnings growth (trail) PWV NYSE Euronext Dynamic Large Cap Value Earnings (Fut 50%); Book Value, Sales, Cash Flow, Value Score No Overlap Equal per Tier (2) Intellidex and Dividend (equal %) FTA NASDAQ NASDAQ AlphaDEX Large Cap Value Value Score No Overlap Equal per Tier (5) Book Value, Cash Flow, Return On Assets RPV S&P Dow Jones S&P 500 Pure Value Value Score No Overlap Value Score Book Value, Earnings, Sales JKF Morningstar Morningstar Large Value Value Score No Overlap FF Mkt Cap Earnings, Revenue, Cash Flow, Dividend, Book Value NASDAQ AlphaDEX Multi Cap Mkt Cap segment allocation + FAB NASDAQ Value Score No Overlap Book Value, Cash Flow, Return On Assets Value Equal per Tier (5) PXLV FTSE Russell Russell Top 200 Pure Value Value Score No Overlap Value score Book Value EZY WisdomTree WisdomTree LargeCap Value Value Score No Overlap Earnings Earnings, Sales, Book Value, 1Y Price chg Factor Tilt VLUE MSCI MSCI USA Value Weighted Mkt Cap/Liquidity Includes all Value Score Book Value, Sales, Earnings, Cash Earnings QVAL Alpha Architect Alpha Architect Quantitative Ex REITs, Fins; Forensic Accounting, Top 60% Quality Value Value Score, Quality Score of Top 10% Value Equal Weight EV/EBIT SPVU S&P Dow Jones S&P 500 Enhanced Value Value Score (Top 100) Top 100 Opt.: Mkt Cap, Value Score, security and sector caps. Book Value, Earnings, Sales FVAL Fidelity Invest. Fidelity U.S. Value Factor Value Score, Size & Sector Adj. No Overlap Mkt Cap + sector o/w adj Free Cash Flow, EBITDA/EV, Tangible Book Value, Earnings (Fut); For Financials only last two. VLU S&P Dow Jones S&P 1500 Low Valuation Tilt Mkt Cap/Liquidity Includes all Value Score Earnings, Cash Flow, Sales, Dividends, Book Value SPVM S&P Dow Jones S&P 500 High Momentum Value Pure Factor CHEP S&P Dow Jones Dow Jones U.S. Thematic Market Neutral Value TR Active SYV Active Active Source: Deutsche Bank, Bloomberg Finance LP. ETF Issuer and Index Provider websites. Value (Top 200) + Momentum (Top 100) Top 100 Methodology Details Opt.: Mkt Cap, Value Score, security and sector caps. Book Value, Earnings, Sales Mkt Cap, Value Score (Top 200) Long/Short Equal, Sector & Market-neutral Book Value, Earnings (Fut), Operating Cash Flow. 17 August 2017

Performance Review Although absolute performance of US Equity Large Cap Value ETFs has been positive for all the periods we reviewed from 1 month to 10 years, the performance of these ETFs relative to the US Equity Large Cap benchmark has varied. Style Mix Value ETFs have underperformed relative to the benchmark during the majority of the periods explored, while also showing the least dispersion of returns among them compared to other Value ETF types. Style Pure Value ETFs have recently underperformed relative to the benchmark, but also outperformed during other periods such as 1Y and 10Y; in addition, these ETFs present larger dispersion of returns compared to Style Mix products. The next group represented by Factor Tilt Value ETFs has shorter history (3 years for the oldest listings) and shows mixed relative performance with some periods of outperformance and others of under or in-line performance; meanwhile dispersion of returns is similar to that of Style Pure ETFs. Finally, the Pure Factor ETF (CHEP) provides an idea of Value factor returns independent of market beta, thus we can see how some periods were more favorable for Value ETFs such as the 1-Year period, while other periods such as YTD have been challenging for the factor. From the performance metrics we can clearly see that Style Pure and Factor Tilt Value ETFs are more likely to provide access to Value returns relative to Style Mix ETFs. Style Pure and Factor Tilt Value ETFs are more likely to provide access to Value returns relative to Style Mix ETFs. Figure 7: Performance Details for US Equity Value ETFs Ticker Style Mix 1M 3M 6M YTD 1Y 3Y Ann. 5Y Ann. 10Y Ann. IWD 1.3 2.8 5.2 5.8 13.6 9.3 18.4 8.1 VTV 1.5 3.4 6.1 6.7 15.1 11.1 19.5 8.9 IVE 1.4 3.0 5.5 6.1 14.2 9.8 18.3 7.4 IUSV 1.4 2.9 5.4 6.1 14.6 9.7 18.6 8.3 MGV 1.6 3.6 6.1 6.3 14.5 11.0 18.9 VONV 1.3 2.9 5.2 5.9 13.6 9.3 18.4 VOOV 1.4 3.0 5.5 6.2 14.2 9.8 18.2 SPYV 1.3 3.0 5.5 6.3 14.2 9.8 18.2 7.9 IWX 1.3 3.2 5.6 6.0 14.2 9.0 17.3 NULV 1.8 4.5 6.6 7.5 Style Pure SCHV 1.3 3.0 6.4 7.1 13.5 10.7 17.7 PWV 1.1 4.3 8.6 9.2 18.1 10.2 19.4 13.4 FTA 1.6 3.2 7.8 9.6 23.4 9.2 19.8 11.2 RPV 2.2 3.9 5.6 6.8 16.4 8.0 26.1 12.0 JKF 1.6 3.2 4.6 4.8 13.2 9.0 15.9 5.8 FAB 1.0 1.9 4.7 5.4 19.4 7.3 18.2 11.9 PXLV 1.8 3.3 5.5 7.2 21.5 11.0 21.5 EZY 2.0 4.1 9.1 10.3 17.7 9.6 16.3 7.8 Factor Tilt VLUE 2.0 3.1 6.8 8.2 19.1 9.5 QVAL 1.0 0.5 4.3 4.8 14.4 SPVU 1.7 5.0 8.5 8.6 26.9 FVAL 2.1 4.4 7.9 9.9 VLU 1.5 3.5 7.0 7.5 17.5 10.7 SPVM 0.9 3.1 Pure Factor (Perf. not compared to S&P 500 ETF due to market neutrality) CHEP (2.4) (1.6) (5.0) (6.9) 7.7 (3.1) 2.2 Active Total Return Performance % as of Jul 31st 2017 SYV 1.7 3.8 7.5 8.2 17.6 12.0 Source: Deutsche Bank, Bloomberg Finance LP. Color fill: Red is for ETFs underperforming the S&P 500 ETF (SPY) in the respective period; Green is for ETFs outperforming; and white is for ETFs in line. Color coding does not apply to CHEP due to its market neutral nature. Deutsche Bank Securities Inc. Page 9

True Exposures Where does the value come from So you have made the decision to own a Value ETF, but which one What value factors are you interested in What is more relevant to you Do you want cheap stocks according to Book Value metrics, or maybe according to Earnings, or maybe a mix of different metrics What if you want Value with a focus on Dividend Yield The following table provides details on the most popular value metrics among US Equity Large Cap Value ETFs, and should serve as a quick guide to help investors match Value preferences with ETF characteristics. Figure 8: Factor Summary for US Equity Value ETFs Ticker Style Mix Book Value Cash P / Book Earnings Sales Dividend Flow Value P / Avg. P / Avg. Div. Earnings Sales Yield % Avg. P / Cash Flow Value Dividend Yield IWD x 2.03 22.03 1.61 2.48 11.87 0.34 0.03 0.04 VTV x x x x 2.32 20.69 1.54 2.50 11.15 0.28 0.07 0.14 IVE x x x 2.07 21.20 1.45 2.44 12.10 0.34 0.02 0.11 IUSV x x x 2.04 21.73 1.38 2.41 11.83 0.35 (0.00) 0.05 MGV x x x x 2.34 19.96 1.61 2.55 11.50 0.30 0.10 0.23 VONV x 2.06 22.82 1.63 2.44 11.09 0.33 0.03 0.04 VOOV x x x 2.08 21.84 1.45 2.41 11.07 SPYV x x x 2.05 21.23 1.47 2.44 12.25 0.34 0.02 0.11 IWX x 2.07 19.85 1.73 2.50 13.20 0.37 0.08 0.24 NULV x x x 2.23 21.89 1.83 2.74 13.02 Style Pure SCHV x x x x x 2.41 21.37 1.90 2.72 12.41 0.21 0.19 0.12 PWV x x x x x 2.20 15.20 1.28 2.23 11.15 0.48 (0.06) 0.19 FTA x x 1.88 16.77 1.02 2.44 8.33 0.52 0.03 (0.18) RPV x x x 1.51 19.24 0.67 2.25 8.15 0.69 (0.08) (0.19) JKF x x x x x 2.10 18.38 1.57 2.82 10.81 0.41 0.27 0.23 FAB x x 1.71 18.02 0.87 2.39 7.85 0.60 (0.05) (0.47) PXLV x 1.59 18.73 1.31 2.66 9.72 0.63 0.16 0.06 EZY x x x 2.24 18.78 1.27 1.78 12.17 Factor Tilt VLUE x x x 1.87 16.94 0.88 2.49 8.17 0.54 0.07 0.07 QVAL x 3.35 12.40 0.77 2.21 7.49 SPVU x x x 1.49 14.57 0.68 2.13 9.18 0.84 (0.14) 0.02 FVAL x x x 2.40 17.77 1.24 2.25 9.49 0.34 (0.07) 0.08 VLU x x x x x 2.27 22.04 1.19 2.21 10.74 SPVM x x x 1.64 15.92 1.25 1.79 11.48 Pure Factor CHEP x x x 1.57 19.63 0.76 2.03 7.35 Active Most Common Value Factors Common Value Metrics (Fund level) SYV 1.99 17.07 1.13 1.99 9.57 Axioma Factor Betas Source: Deutsche Bank, Bloomberg Finance LP, Axioma. Color fill: Red is for ETFs with a lower value than the respective S&P 500 ETF (SPY) value; Green is for ETFs with a higher value; and White is for ETFs with the same value. Data as of 9-Aug-2017 Size Sector biases and concentrations should not be overlooked Most Value ETFs have a clear overweight on Financials, with the exception of a few products such as QVAL, which excludes Financials altogether, and VLUE and FVAL, which control for sector deviations allowing a value tilt while staying more aligned to their parent indices. Similarly, most products have a significant underweight on Technology. Furthermore, we see Style Mix products with significant biases towards the Energy and Consumer Discretionary sectors relative to the other Value ETF types. At an individual product level, some ETFs present significant sector concentrations. For example, QVAL has 55% in Consumer Discretionary, and SPVM and SPVU have 50% and 42% in Financials, respectively. Page 10 Deutsche Bank Securities Inc.

Figure 9: Concentration, Market Cap, and Sector Exposure for US Equity Value ETFs Ticker Style Mix # of Holdings Wgt % in Top 10 Large Cap Mid Cap Small Cap Cons. Disc. Cons. Staples Energy IWD 722 22% 95.7% 4.0% 0.1% 6.9% 9.1% 10.4% 25.8% 13.8% 8.5% 8.1% 2.8% 4.9% 3.2% 6.3% VTV 338 27% 99.8% 0.1% 0.0% 4.8% 9.0% 8.0% 24.7% 13.5% 12.2% 13.1% 3.8% 0.8% 3.9% 6.0% IVE 352 26% 99.5% 0.2% 0.0% 6.9% 11.5% 10.7% 27.7% 12.4% 8.8% 6.6% 3.5% 1.8% 3.7% 6.3% IUSV 640 24% 95.0% 4.4% 0.4% 7.2% 11.0% 10.3% 27.0% 12.0% 9.2% 7.1% 3.9% 2.3% 3.5% 6.5% MGV 150 32% 100.0% 0.0% 0.0% 2.1% 8.9% 8.9% 25.5% 15.7% 12.2% 14.1% 2.4% 0.6% 4.6% 5.2% VONV 721 22% 95.4% 4.0% 0.1% 6.9% 9.1% 10.2% 25.8% 13.8% 8.5% 8.1% 2.8% 4.9% 3.2% 6.3% VOOV 353 26% 99.5% 0.3% 0.0% 6.9% 11.5% 10.7% 27.7% 12.4% 8.9% 6.6% 3.5% 1.8% 3.7% 6.3% SPYV 351 26% 99.7% 0.2% 0.0% 6.9% 11.5% 10.7% 27.7% 12.4% 8.8% 6.6% 3.5% 1.8% 3.7% 6.3% IWX 130 33% 99.7% 0.0% 0.0% 4.5% 11.4% 11.7% 28.5% 17.2% 7.1% 8.9% 1.6% 0.4% 4.3% 4.1% NULV 129 31% 99.7% 0.0% 0.0% 4.5% 11.0% 5.9% 25.7% 12.9% 9.5% 10.2% 5.4% 2.9% 4.2% 7.5% Style Pure SCHV 349 26% 99.1% 0.8% 0.0% 6.3% 12.6% 8.5% 20.5% 11.4% 9.3% 15.3% 3.4% 2.5% 3.9% 6.3% PWV 50 34% 100.0% 0.0% 0.0% 9.1% 6.8% 1.5% 31.7% 15.0% 9.2% 20.6% 3.0% 0.0% 3.2% 0.0% FTA 188 10% 99.9% 0.0% 0.0% 19.5% 6.6% 5.4% 18.9% 7.8% 8.2% 8.6% 5.1% 3.0% 2.1% 14.9% RPV 110 19% 98.6% 1.3% 0.0% 17.6% 7.5% 5.9% 36.4% 10.8% 6.2% 3.3% 2.0% 0.0% 1.9% 8.4% JKF 81 42% 99.8% 0.0% 0.0% 2.1% 13.8% 9.7% 31.4% 9.2% 6.5% 11.2% 1.7% 0.8% 7.5% 5.9% FAB 675 5% 58.9% 25.2% 15.9% 21.1% 5.7% 4.3% 18.2% 5.0% 14.4% 8.2% 5.9% 4.9% 1.8% 10.6% PXLV 70 29% 100.0% 0.0% 0.0% 8.5% 5.6% 10.5% 34.3% 4.8% 5.9% 8.5% 3.4% 0.4% 2.9% 15.4% EZY 295 35% 91.2% 8.1% 0.4% 11.7% 9.1% 0.0% 24.3% 11.0% 18.7% 11.2% 2.6% 0.1% 5.9% 5.1% Factor Tilt VLUE 151 38% 99.0% 0.8% 0.0% 13.0% 8.9% 6.2% 14.4% 13.9% 9.6% 22.5% 3.0% 3.0% 2.1% 3.2% QVAL 40 28% 65.6% 34.4% 0.0% 55.2% 10.2% 0.0% 0.0% 17.4% 4.9% 9.7% 2.7% 0.0% 0.0% 0.0% SPVU 95 37% 99.6% 0.4% 0.0% 13.6% 14.6% 5.9% 41.9% 12.1% 4.1% 3.7% 1.7% 0.0% 0.5% 2.1% FVAL 130 23% 96.2% 3.4% 0.4% 11.9% 8.7% 5.9% 14.7% 13.6% 10.5% 22.5% 3.2% 3.6% 2.1% 3.3% VLU 1363 17% 91.0% 5.7% 3.0% 11.8% 8.8% 8.1% 21.1% 11.6% 10.3% 15.1% 3.3% 2.3% 2.9% 4.4% SPVM 101 16% 100.0% 0.0% 0.0% 7.7% 4.5% 1.3% 49.7% 6.4% 10.5% 8.6% 2.6% 0.0% 0.0% 8.7% Pure Factor CHEP 201 5% Market Neutral Sector Neutral Active Concentration % Wgt. By Market Cap % Wgt. GICS Sectors SYV 56 37% 96.7% 2.1% 0.0% 8.9% 6.8% 9.2% 25.5% 15.7% 9.5% 10.6% 1.9% 3.0% 0.5% 7.1% Source: Deutsche Bank, Bloomberg Finance LP. Color fill: Red is for ETFs with a lower value than the respective S&P 500 ETF (SPY) value; Green is for ETFs with a higher value; and White is for ETFs with the same value. Data as of 9-Aug-2017 Health Care Financials Industrials Technology Materials Real Estate Telecom Utilities Sector or Value biases You be the judge When it came to sector exposure stability, we reviewed some of the largest Value ETF indices per group and we noticed that Style Mix methodologies (IWD, VTV) usually had a more stable sector allocation over time; this was probably due to the high reliance of these methodologies on free float market cap weighting. In fact, a similar sector stability was seen on Style Pure methodologies also using free float market cap weighting (SCHV), while other Style Pure ETFs (PWV) employing alternative weighting methodologies (equal weighting across two tiers) exhibited more sector allocation variations over time. In fact the largest Factor Tilt Value ETF (VLUE), which is also weighted employing an alternative method (value-weighted) displayed notable variations as well. Similarly, another Factor Tilt ETF (QVAL) exhibited significant variations in sector weights over time, but in this case this was most likely due to the selection screening rather than the weighting as this ETF tracks an equally-weighted index. Finally, the only active ETF (SVY) exhibited a surprisingly high degree of sector stability over time. Sector stability is an important behavior to understand the main Value sources of your ETF. For example, ETFs with high sector stability would be more likely to get their Value from simple sector tilts, while ETFs with low sector stability are more likely sourcing their Value from stocks with strong Value characteristics. Deutsche Bank Securities Inc. Page 11

Weight Weight Weight Weight Weight Weight 17 August 2017 Figure 10: Historical Sector Exposure - Style Mix (IWD) Figure 11: Historical Sector Exposure - Style Mix (VTV) IWD VTV 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Figure 12: Historical Sector Exposure - Style Pure (SCHV) Figure 13: Historical Sector Exposure - Style Pure (PWV) SCHV PWV 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Figure 14: Historical Sector Exposure - Factor Tilt (VLUE) VLUE 100% Utilities 90% Telecom 80% Real Estate 70% Materials 60% Technology 50% Industrials 40% Health Care 30% Financials 20% Energy 10% Cons. Staples 0% Cons. Disc. 2014 2015 2016 2017* Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Figure 15: Historical Sector Exposure - Pure Factor (QVAL) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% QVAL 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Page 12 Deutsche Bank Securities Inc.

Weight 17 August 2017 Figure 16: Historical Sector Exposure - Active (SVY) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% SVY 2014 2015 2016 2017* Utilities Telecom Real Estate Materials Technology Industrials Health Care Financials Energy Cons. Staples Cons. Disc. Source: Deutsche Bank, Bloomberg Finance LP. *2017 data as of 9-Aug-2017. Deutsche Bank Securities Inc. Page 13

Appendix 1 Important Disclosures *Other 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 http://gm.db.com/ger/disclosure/disclosuredirectory.eqsr. Aside from within this report, important conflict disclosures can also be found at https://gm/db.com/equities under the "Disclosures Lookup" and "Legal" tabs. Investors are strongly encouraged to review this information before investing. 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 Buy: Based on a current 12- month view of total share-holder 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 share-holder 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. Equity rating dispersion and banking relationships Regulatory Disclosures Page 14 Deutsche Bank Securities Inc.

1.Additional Information 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 1-877-369-4617 or by visiting www.dbxus.com. 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 https://gm.db.com/equities under the "Disclosures Lookup" and "Legal" tabs. Investors are strongly encouraged to review this information before investing. Deutsche Bank Securities Inc. Page 15

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