Spotlight Web Seminar Active and Passive Investing: Why Are ETF Fees So Low? Morningstar Advisor February/March 2011

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Spotlight Web Seminar Active and Passive Investing: Why Are ETF Fees So Low? Morningstar Advisor February/March 2011

Total Cost Analysis of ETFs Paul Justice, CFA Director of ETF Research North America Bradley Kay Director of Quantitative Analysis February 28, 2011 2010 Morningstar, Inc. All rights reserved. <#>

What We Definitely Know: ETFs Are Growing in Popularity 1,000 1,200 800 1,000 800 600 600 400 400 200 200 0 2003 2004 2005 2006 2007 2008 2009 2010 0 Source: Morningstar. Net Assets ($Bil)# of ETF

We Know: They Are Opening Up New Asset Classes for Investors 1,000 800 In $ Bil 600 400 Commodities Alternative Municipal Bond Taxable Bond International Stock U.S. Stock 200 0 2003 2004 2005 2006 2007 2008 2009 2010 Source: Morningstar.

We Know: They Are Inexpensive Expense ratios for ETF index funds are significantly cheaper than equivalent mutual fund expense ratios 0.6 Asset-weighted expens 0.4 0.2 ETFs Mutual fun 0 Large-Mid-CapLarge-Mid-Cap Cap Growth Cap Value Growth Blend Source: Morningstar.

We Know: They Are Inexpensive Especially in sector funds Expense ratio 1.6 1.2 0.8 0.4 0 Industrials Technology Utilities Health Care Financials Cons Discretionary Sector ET Source: Morningstar.

We Know: ETFs Are Affecting Mutual Fund Pricing ETF Assets vs. Asset-weighted MF Expe 0.95 700 Expense ratio (%) 0.9 0.85 0.8 0.75 600 500 400 300 200 Assets (bn) Mutual Fund ETF Assets (b 0.7 100 0.65 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0 Source: Morningstar.

How a Mutual Fund Works

ETF Creation / Redemption

Are Fees a Fare Comparison? Mutual Funds are full-service providing entities ETF Expense ratios lower due to outsourcing capital market activities How can we say ETFs are less expensive without measuring the impact of bypassed services? In what asset classes are those services over- or underpriced?

10 Most Tracking Error Calculations Are Useless

Sources of Tracking Difference: Long-Term Trend The long-term trend captures persistent factors that boost or detract from portfolio performance over time Management and service fees Rebalancing trade costs Share lending and repo revenue Swap agreements and other derivative contract costs Point-to-point measurements tend to be very poor estimates This is the ONLY type of tracking difference that predicts future performance for the portfolio relative to its benchmark 11

Sources of Tracking Difference: Technical/Timing Issues Also referred to as mean-reverting noise Stems from purely technical issues in index and portfolio pricing Stale securities prices used in the index calculation Different timing for price cutoff and currency conversion Fair value pricing used in fund NAV Can easily cause a deviation of 100+ basis points between an index and a portfolio without any real difference in value This is often the largest source of tracking error in fixed-income, precious metals, and foreign equity funds 12

Sources of Tracking Difference: True Random Deviations Random price movements that persist in the NAV; true deviations in fundamental value Portfolio optimization and index sampling Delays in investing or hedging cash flows These deviations have an average of zero effect on long-term trend versus the index, but can throw off trend estimation for a sub-period This is an estimate of true tracking error Not predictive of future fund performance Predicts the size of ERRORS in our future performance estimate 13

14 Sources of Tracking Difference: An Example Hypothetical ETF: Japanese equities hedged into U.S. dollars Estimated Holding Cost Management, custodial, administrator, etc. fees: 50 bps Annual swap costs for JPY/USD hedge: 20 bps Trading costs during rebalance: 10 bps Tracking Error Big flows one day get invested immediately in Nikkei 225 futures Delay in adding the currency swap for new 10% of assets JPY appreciates 0.5% versus USD: 5 bps gain relative to benchmark Technical/timing issues Index prices for Nikkei 225 set using end-of-day prices in Tokyo NAV prices set using adjustments for ADR and futures pricing in New York, as well as NY close prices for JPY/USD

What s Wrong with Most Tracking Error Calculations? Point-to-point return difference Long-term trend captured in the return difference No way to estimate volatility of portfolio tracking For most time periods used in this estimation (< 3 years), daily technical deviations likely to be similar size to trend difference Standard deviation of return differences Confounds illusory technical pricing differences with true deviations in fundamental value For many categories of ETF, 70-90% of this tracking error calculation could purely be due to mean-reverting noise Does not provide a good prediction for expected deviations over longer time periods 15

Morningstar s New Data Points Estimated Holding Cost Isolates the long-term trend, avoiding point-to-point problem Predictive of future performance difference between fund NAV and index Presented as an annualized return difference Tracking Error Isolates true, persisting deviations in portfolio value Predictive of how widely future performance might differ from (index return + estimated holding cost) Presented as an annualized standard deviation of expected performance relative to the index 16

17 How Liquid Is Your ETF?

Two Extremes of Liquidity Measurement Precise analysis of liquidity in underlying securities Requires extensive computation and intraday order book data Misses hidden liquidity in the ETF itself Mostly relevant to very large orders reliant on market makers Rough heuristics based on widely available data Assets in the ETF ETF trading volume Price volatility Premium/Discount volatility 18

A Better Estimate for Moderate Trade Sizes Of all the rough heuristics used, two provide the best information Daily dollar trading volume Volatility of the premium/discount Market Impact Cost combines these into a single statistical model for how far a given dollar trade will move ETF prices Standardized to an estimate for how much a $100k trade will move the price from bid-ask midpoint or fair value Accounts for both visible order book liquidity and hidden liquidity in the ETF itself 19

Market Impact Cost: Some Caveats Intended for moderate trade sizes that do not require market makers Trades of $1-5 million or more will price dependent on current liquidity in available hedging vehicles (futures, underlyings, etc.) Market makers will provide more accurate prices on demand Assumes reasonable execution, including use of limit orders Measures more liquidity than just what s available on the order books Very infrequently traded ETFs will have extremely high Market Impact Cost estimates If there s not enough trading volume to analyze, we scale up observed market price volatility to match $100k trade size 20

21 Total Cost Analysis

What We Have Found Thus Far The U.S. ETF market is even more liquid than we thought Market impact costs form a tiny fraction of total costs for larger ETFs, even at trade sizes up to $1 million Total cost of ETFs varies much more than expense ratios Precious-metal ETFs seem to have the fewest frictions outside of disclosed prospectus expenses U.S. equity ETFs often have 0-30 basis points of hidden costs beyond the expense ratio Foreign equity and bond ETFs see much larger range of hidden costs 22

Data Point Calculation Examples SPDR S&P 500 (SPY) NER: -0.09% EHC: -0.23% MIC: 0.0002 TE: 0.02% PwrShrs RAFI 1000 (PRF) NER: -0.39% EHC: -0.40% MIC: 0.0143 TE: 0.12% ishares S&P 500 (IVV) NER: -0.09% EHC: -0.16% MIC: 0.0013 TE: 0.06% Rydex EqWt S&P 500 (RSP) NER: -0.40% EHC: -0.56% MIC: 0.0029 TE: 0.04% 23

Estimating an All-In Cost for ETF Investing Relies solely on Est. Holding Cost, Market Impact, & Tracking Error Simple Inputs Expected length of holding Expected size of trade in dollars Commission costs Simple Outputs Total cost from purchase to sale Expressible as dollar amount or as an annualized percent loss 95% error bounds for the estimate are calculable 24

Total Cost Analysis Examples Trade size: $1 million Duration of holding: 3 years Commission: $10 flat fee Total Cost Estimate Dollar Amount Annual % TER 95% Bound 95% Bound SPDR S&P 500 $ (6,996.50) -0.23% 0.0% $ (6,996.50) $ (6,996.49) ishares S&P 500 $ (5,118.27) -0.17% 0.0% $ (5,118.28) $ (5,118.26) PowerShares RAFI US 1000 $ (16,520.92) -0.55% 0.3% $ (16,520.94) $ (16,520.90) Rydex S&P 500 Equal Weight $ (17,801.54) -0.59% 0.4% $ (17,801.55) $ (17,801.54) SPDR S&P Dividend $ (10,156.28) -0.34% 0.3% $ (10,156.30) $ (10,156.26) Vanguard Emerging Markets $ 1,123.01 0.04% 0.2% $ 1,121.59 $ 1,124.43 ishares MSCI Emerging Markets $ (34,457.63) -1.15% 0.6% $ (34,458.18) $ (34,457.08) SPDR Gold Shares $ (13,689.54) -0.46% 0.4% $ (13,689.97) $ (13,689.10) ishares COMEX Gold $ (13,081.40) -0.44% 0.2% $ (13,083.08) $ (13,079.72) 25

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Spotlight Web Seminar Active and Passive Investing: Why Are ETF Fees So Low? Q&A