betasofetfsonfinancialwebsites-fma2010

8/13/2019 BetasofETFsonFinancialWebsites-FMA2010

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ETF Betas on Financial Websites: A Confusing Mess

By

Doug WaggleAssociate Professor of Finance

University of West Florida11000 University ParkwayPensacola, FL 32514-5750

(850) [email protected]

Pankaj Agrrawal

Assistant Professor of FinanceUniversity of Maine305 DPC Business Building

Orono, ME 04469(207) 581-1983

[email protected]

January 2010


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Abstract

We calculate betas of a sample of 232 ETFs and compare them against the betas reported by four

top financial websites. We find that a large number of the website betas related to international,

global, bonds, commodities, and currency ETFs are markedly different from our estimates. The

primary reason for differences in the beta estimates was the selection of the market indexes used

in the regression calculations, which many websites do not even reveal. We also looked at six

additional financial websites and examined their market index selections along with their

supporting information regarding the use and calculation of beta. Most financial websites do not

provide adequate information on their beta calculations to allow for appropriate interpretations.


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Exchange Traded Funds (ETFs) have evolved to the point where both individual and

institutional investors are employing them as core components of their portfolios. In a recent

Wall Street Journalarticle, Burton (2008) notes that many financial advisors now depend on

ETFs when building client portfolios. ETFs now occupy prominent positions in investor

portfolios because they offer the benefits of mutual funds and the convenience of stocks. ETFs

provide easy diversification, low fees, and significant tax advantages, while at the same time

allowing real-time trading and short selling. With over 700 possibilities to choose from, ETFs

can offer something for almost everyone. But how do investors choose a subset of ETFs that

meets their goals from the wide selection that is available to them? To make such informed

portfolio decisions, investors need timely and accurate financial data on the ETFs. Often they

turn to enormously popular websites such as Yahoo! Finance, MSN Money, Google Finance or

Morningstar to obtain key investment information, such as beta and other measures. With

various estimates putting the traffic to such sites in the millions, the quality and validity of the

information provided by these sites is obviously a concern. It is also the topic of research for this

paper.

This paper focuses on betas because they give a quick estimation of exposure to market

risk. For a well-diversified portfolio the nondiversifiable systematic risk is best indicated by beta.

The recent market turmoil has heightened the need to understand portfolio volatility and the


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a lack of transparency, and just plain misinformation. Despite beta being defined as a measure of

systematic, or market risk, many websites report betas that do not reflect the market risk faced

by U.S. investors; at best they reflect sector risk. In addition, most of the websites do not provide

sufficient information to allow investors to appropriately interpret and utilize the available betas.

ETF Background

The S&P 500 SPDR, which surfaced on the scene in 1993, was the first ETF. It was not

until 1995 that a second ETF, based on the S&P 400 Midcap Index, was offered, but by the end

of 2000 there were 80 ETFs including the well-known Diamonds on the Dow and the Qs on the

NASDAQ. As of November 2008, there were over 700 ETFs with about $480 billion in total

assets. (Investment Company Institute, 2009). Leaders in the ETF industry include Barclays1,

which issues iShares, State Street Global Advisors, sponsors of SPDRs, Merrill Lynch, known

for HOLDRS, and Vanguard, which is well-known for index mutual funds and decided to have a

presence in the ETF arena as well.With such a large selection of ETFs it is easier than ever to find one that matches a

particular investment objective. There are ETFs that hold stocks, bonds, commodities,

currencies, and real estate. Investors can use ETFs to invest domestically or internationally, or to

capture individual sectors or industries within the market. While ETFs themselves can be

shorted, there are also those that actually make short bets against the market. Some ETFs also

have a component of active management built into the process.


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Beta Calculation and Potential Issues

The Sharpe-Lintner-Black CAPM Beta is a measure of the systematic risk of individual

securities or portfolios and is based on historical returns of the asset relative to the market. The

usefulness of beta continues to be widely discussed and challenged, but Graham and Harvey

(2001) find that 70% of practitioners still use the traditional CAPM beta as a measure of their

exposure to market risk. Higher betas mean greater co-movement with the market and higher

expected returns relative to the market. Investors also use betas to select the level of market risk

that they are comfortable with. With well-diversified portfolios, company-specific, or

unsystematic risk, is diversified away, thus making beta an even better tool for evaluating the

relevant investment risk. ETFs are, of course, portfolios of securities so their betas are

conceivably even more meaningful and useful than those of individual securities.

Beta is calculated using the Ordinary Least Squares regression of the historical returns of

the security or portfolio against the overall market. The standard model for calculating beta

employs excess returns relative to the risk-free rate:

ifMiifi errrr ++= )()( (1)

where riis the return on security i, rMis the return on the market, rfis the risk-free rate of return,

iis the calculated beta coefficient, is the intercept term, and eiis the residual term.

In practice, the beta calculation is often simplified by ignoring the risk-free rate and

regressing the security returns against the returns of the market. Since the periodic risk-free rate

is fairly close to zero and subtracted from both sides of the equation this simplification makes


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ETF betas were calculated using both Equations (1) and (2), but only the results for the latter

case are presented here. The differences in the two sets of estimates are trivial. The returns on the

S&P 500 index and the 3-month U.S. Treasury bill rate were used to represent the market and the

risk-free rate, respectively. The betas were estimated using a minimum of 24 months and a

maximum of 36 months of return data. ETFs with less than 24 months of data were excluded

from the data set, to maintain estimation stability.

While the calculation of beta might initially sound straight forward, it leaves a lot of

room for interpretation and differences. First, although the S&P 500 index has been widely used

as a market measure for U.S. equity securities, many potential questions remain. Should this

market portfolio be expanded to include a broader index, such as the Russell 3000? Should the

market portfolio include additional tradable assets, such as bonds, commodities, real estate, or

currencies? Given that U.S. investors are encouraged to invest internationally, should the market

portfolio be expanded to include the entire globe? If a global market portfolio is used, should it

include just equity or other asset classes as well?

There is likewise no agreed upon estimation interval for the calculation of beta, but

estimation windows of one to five years are common. Does a five-year estimation window give

too much weight to the distant past? Is a one-year estimation window more appropriate or does

this focus too much weight on the current market environment? Works such as Smith (1980) and

Hawawini (1980) have observed the effects of the estimation window. Groenewold and Fraser

(2000) argue that the typical five-year estimation window has the best explanatory value.


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understate the true volatility of less liquid securities. The use of monthly returns can also be

problematic since it requires a longer estimation interval to provide a suitable number of

observations. These issues are examined by works such as Hawawini and Vora (1980), Corhay

(1992), Levy, Guttman and Tkatch (2001), Ho and Tsay (2001), and Agrrawal and Clark (2007).

Differences in beta estimates from various information providers are to be expected, and

this has been true for as long as betas have been calculated. Reilly and Wright (1988), for

example, noted that the published betas of Value Line and Merrill Lynch differed significantly.

They concluded that the differences were due to the use of weekly returns by Value Line and

monthly returns by Merrill Lynch.

ETF Beta Sample

Over half of the 700 plus ETFs in existence today were introduced after 2006, giving

them limited windows for the calculation of beta, and many have relatively small market

capitalizations that may result in liquidity issues such as wide bid-ask spreads. Accordingly, we

consider only ETFs with at least $100 million in market capitalization and 24 months of return

history as of September 20082. This resulted in a final sample of 232 ETFs. Our sample includes

155 U.S. equity ETFs, 59 international or global ETFs, 6 commodity ETFs, 6 foreign currency

ETFs, and 6 bond ETFs. The U.S. equity group is obviously the biggest category by far. All

available betas for our selected ETFs were retrieved in September of 2008, from four of the most

visited financial websites: Yahoo! Finance, MSN Money, Morningstar, and Google Finance.

Yahoo! Finance reported betas for 154 of our sample of 232 ETFs, with most omissions


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ETFs with longer histories, Yahoo! Finance presents betas for 3 Years, 5 Years, and even

10 Years.3

Only on the Yahoo!s 3-year betas were examined. Yahoo! Finance actually

obtains their beta and other risk measures from Morningstar, but the figures lag the numbers

shown at Morningstar. As expected the Morningstar sample is somewhat larger with 157

observations. Morningstar presents only 3-year betas. MSN Money had betas for all 232 ETFs

in the sample4. Google Finance presented betas for 226 of the sample, and there does not seem to

be explanation for the six exclusions since all of them had ample financial history.

In addition to examining the full sample of betas for the four noted websites, these sites

and six other popular financial sites were examined to locate publicly available information on

their calculations of beta and to determine which indexes they use as a basis for their

calculations. For sites lacking descriptive information, a much smaller subset of ETFs was

examined to see if any inferences could be drawn about their beta calculations. The six additional

sites examined were: AOL Money & Finance, Bloomberg, CNN Money, Reuters, Smart Money,

and TheStreet.com.

Some Unexpected ETF Betas on Popular Websites

First, the published financial betas as found on the Yahoo! Finance, MSN Money,

Morningstar, and Google Finance websites were examined and then compared them against beta

calculations with the S&P 500 index as the market proxy. The results of these comparisons are

illustrated in the XY scatter plots shown in Figures 1 through 4.


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Figure 1 shows that the bulk of the 3-year betas presented by Yahoo! Finance match up

fairly well with the calculations discussed here, but that there is a noticeable group of outliers

that skew the results to a -0.23 correlation coefficient. As can be seen in Figure 2, the majority of

the MSN betas generally pair up fairly well with our calculations, but the set of outliers is even

larger here. As is the case with Yahoo! Finance, the outliers change the overall positive

relationship for the majority of observations to a correlation -0.32. Figure 3 reveals that most of

Morningstars betas also line up with our S&P 500 based calculations, but that there are again a

sizeable number of outliers leading to a correlation of -0.22 that is not representative of the

overall picture.

It is obvious that outliers are driving the negative correlations noted in Figures 1, 2, and

3. It is these numerous outliers and the reasons for them, which are of particular interest. As has

already noted, some differences in beta estimations are to be expected, but not of the magnitude

revealed by the scatter plots. which are clearly beyond the norm. Removing the outliers for

Yahoo! Finance, MSN, and Morningstar results in expectedly high correlation coefficients of

0.90 or higher for the betas of these sites relative to our calculated betas. 5

The XY scatter plot of Googles ETF betas versus our S&P 500-based betas is shown in

Figure 4, and makes a particularly interesting picture. It is not so much that there are outliers, but

rather that Google reports so many betas exactly equal to 1.0, all of which plot on a straight line

(Figure 4), that is perplexing. In fact, of the 226 betas in our Google sample, fully 75 of those are

exactly equal to 1. This was not something that was expected. The Google sample includes 152


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high of 2.78. MSN Moneys estimates for the same group of ETFs likewise range from a low of

0.35 to a high of 3.10. This information is presented in Table 1. Unfortunately, Googles website

does not provide its visitors with any explanation regarding their beta calculations. Our first

impression with the Google betas was that they are applying separate best-fit indexes and using

those as their market measures. Morningstar, for example, presents separate beta calculations

with a standard index and a best-fit index. Google could be calculating betas for

pharmaceutical ETFs, for example, using a pharmaceutical index as the assumed market. The

Google assigned beta for the iShares Pharmaceutical ETF is exactly 1.0, indicating that a sector

index was used instead of the broader market. The calculated beta was 0.77 for the same ETF,

with the S&P 500 as the market index. There are problems of inconsistency here, as well. Google

estimates a beta of 0.64 for the Merrill Lynch Pharmaceutical HOLDRS (ticker: PPH, not shown

on the table), which is much more in line with the S&P 500 based figure of 0.72; and most likely

employs the broad market index for the beta calculation.

In the paragraphs that follow, it is shown that the anomalies associated with Yahoo!

Finance, MSN, and Morningstar betas are almost exclusively in ETF categories other than U.S.

equity -- bonds, international or global equities, commodities, and currencies. Table 2 presents

the betas for the 6 bond ETFs in the sample. The low betas calculated for bond ETFs are

consistent with general expectations, implying little or negative correlation with the broad equity

market. Other than Google, however, the S&P 500-based calculations are not comparable with

the published betas as found on these finance websites. For the iShares Lehman Aggregate Bond


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imply that the bond ETF has higher market risk than that of the S&P 500 an obvious

mischaracterization.

Table 3 presents the betas of the 59 international and global equity ETFs in the sample.

Again, about a third of Googles betas are exactly equal to 1.0. Once again, a first impression

might be that Google was using best-fit indexes, such as country-based indexes as their market

measure, but this remains unclear. Googles iShares Switzerland ETF, for example, has a beta of

1.00 compared to our calculation of 0.79. Looking further, however, shows that Googles iShares

Sweden ETF has a beta of 1.69, which is in line with the S&P 500-based calculation of 1.60.

Setting Google aside, there are still numerous differences between the S&P 500-based

calculations and those presented by the other financial websites. With the iShares Mexico ETF,

for example, S&P 500 beta estimate of 1.25 is a good bit different than the 0.54 and 0.93 figures

provided by MSN and Yahoo! Finance, respectively.

In Table 4, the betas of the six commodity ETFs in the sample are shown. Betas close to

zero for ETFs such as the SPDR Gold ETF were expected, and that exactly how the S&P 500-

based calculations turned out to be. The calculated beta estimate of -0.06 for SPDR Gold,

however, differed dramatically from the 12.85 beta figure obtained from Yahoo! Finance and the

27.79 beta provided by MSN Money. Table 5 shows betas of the sample of six currency ETFs

and reveals additional oversized differences. Google is consistent in assigning 1.0s across the

board, while Yahoo! Finance and Morningstar do not present betas for any of these ETFs. The

S&P 500-based figures differ dramatically down the line compared to MSN. The average beta


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Differences in Market Indexes Used and Inadequate Explanations

The wide range of values observed for the betas of categories other than U.S. equity

make it clear that there are notable differences in the underlying assumptions of the various

website beta calculations. It was determined that the primary reason for the differences in betas is

the selection of the index used to proxy the market portfolio. While this paper uses the S&P 500

index as the market proxy for all calculations, this is not the case for all of the sites that were

examined. Table 6 shows ten top financial websites and details the conclusions about the market

index used for the various categories of ETFs. CNN Money has apparently adopted the premise

that beta is dead because this is the only site in the group that does not provide any beta figures

for the ETFs whatsoever. Accordingly, CNN Money is not included in the following discussion.

As noted before, Google provides beta estimates, but offers no insights into their calculations.

For the remaining eight websites examined, the market index employed for the U.S equity ETFs

is consistent with the S&P 500 index. The consistent with disclaimer is included because while

the presented betas examined are comparable to the S&P 500-based calculations, three of the

eight websites offered no insights at all into their beta calculations. On Morningstar, MSN

Money, and Bloomberg, the market index employed was clearly noted, while it was identified

with some digging at Smart Money and Yahoo! Finance.

Extrapolating from the information in Table 6, there appears to be a general consensus of

opinion regarding which market index to use for U.S. equity ETFs, however, differences of

opinion were the norm for the other categories. For the fixed income (bond) ETFs, Morningstar,


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five sites, including Google, use the S&P 500, or something comparable, as the market index,

although this is clearly stated only at Bloomberg. The Smart Money site states that the Lehman

Aggregate Bond Index is used as the market measure for bonds, but observations actually

suggest that they use an index comparable to the S&P 500.

Table 6 also reveals differences in market indexes used for calculating the betas of

international ETFs. It appears that four sites use the MSCI EAFE6

index while three others use

the S&P 500 index. Bloomberg uses a variety of different indexes, which are all noted with their

beta figures. With global funds, there are additional differences to contend with. Smart Money

and TheStreet.com both report betas comparable to our S&P 500-based figures. The remaining

websites use different indexes for different global funds. For example, both MSN and

Morningstar measure the iShares Global Utilities ETF against the S&P 500 index; and both sites

measure the iShares Global Industrials ETF against the MSCI EAFE index.

Differences are also noted in the market indexes employed for computing the betas of

commodity and currency ETFs. Two of the sites base their betas solely on the S&P 500 index,

and two others use the three-month LIBOR rate index. MSN uses the MSCI EAFE equity index

for gold and silver commodity ETFs, but it uses the S&P 500 equity index for the iShares

Commodity ETF and the iShares U.S. Oil ETF. Morningstar uses the three-month LIBOR or the

S&P 500 equity index for the commodities. MSN, which clearly identifies the index used for

every other ETF category, inexplicably does not do so for currency ETFs.

Purpose of Beta


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calculations. The reason that Morningstar, for example, uses more focused indexes to calculate

betas is that their ultimate goal is notto determine a measure of systematic risk. Instead, they

want to determine alphas as measures of portfolio performance. If one is gauging the

performance of a bond investment, the S&P 500 Index is not an appropriate benchmark, but the

Lehman Aggregate Bond index may be. Using equations 1 or 2, if the returns of a benchmark

portfolio are used in place of the broad market returns, measures excess returns on the part of

the investment. Funds generating positive alphas are sought after, and sites such as Morningstar

specialize in providing this information to the marketplace.

So the issue relates to the true purpose of the betas in the calculations. Morningstar and

some other sites present betas that are actually generated as a byproduct of the calculation of

performance-measuring alphas. If the benchmark used for performance evaluation purposes is

something other than a broad market index that encompasses U.S. equities, the betas that are

calculated in the process will obviously not be appropriate measures of overall systematic risk

for U.S. investors. For U.S. equities, the S&P 500 index is a widely recognized benchmark

portfolio, so the betas calculated during the alpha-generating process also do a good job

measuring systematic risk. Not surprisingly, the problem of the divergent goals of the

calculations only manifests itself for categories other than U.S. equity.

While this alpha-beta issue may be obvious to sophisticated investors, some financial

websites exacerbate the problem and end up inadvertently misleading investors by providing the

traditional market risk definition of beta in conjunction with betas that do not actually measure


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What should a typical investor who reads Morningstars beta definition and then examines their

Gold ETF beta conclude?

Betas can also be used to measure the systematic risk of a portfolio. A portfolio beta is

simply the weighted average of the betas of the securities that comprise the portfolio, with the

weights being the percentage of the portfolio invested in each asset. Unfortunately, this portfolio

beta calculation is rendered meaningless if the individual betas are calculated differently. An

investor who uses the Morningstar site, for example, to determine the overall beta for a portfolio

of U.S., international, global, commodity, and currency ETFs would generate a completely

useless number. The use of different market indexes used in the derivation of betas means that

they cannot be used for calculating meaningful portfolio betas.

Conclusions

Transparency of financial information is essential to its usefulness. This is one of the key

tenets of standardized financial reporting. If there is no understanding of how data is developed,

then it has no value. Financial websites exist because they can make reliable financial

information more accessible to investors, but it does not appear that these websites understand

the importance of the transparency of their own data. Based on our examination of ETF betas

and reporting, none of the websites we reviewed deserves an A in this regard, although

Morningstar would merit a B, in opinion of the authors. As noted earlier, there are numerous

alternatives regarding the calculation of beta, and a user of this information should be able to

readily determine how it was developed. Providing this information would not be a monumental


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There are significant differences in the beta estimates of ETFs on financial websites,

which are primarily attributed to the selection of the market index used in the calculations.

Yahoo! Finance, one of the leaders amongst the various finance portals, puts the notation

against standard index along with its beta figures. Unfortunately, the Yahoo! Finance site

keeps its users in the dark regarding many of these standard indexes. For seven of the nine

financial websites examined, it was not possible to locate information about the market index

utilized for some or all of the ETF betas that were available. Given that this review of financial

websites suggests that the market indices used for ETF betas are anything but standard, this is

not acceptable. As noted earlier, the Smart Money site actually reported incorrect information on

the index used for bond ETFs. In a similar vein, Yahoo! Finance and Morningstar provide short

discussions of beta and mention gold funds as an example of an investment that would be

expected to have a low beta relative to the S&P 500 index. This sounds perfectly reasonable,

except that the betas they actually present for two gold ETFs average about 12.0, because of their

use of alternative indexes. Google Finance adds to the confusion with its perplexing set of betas

that are exactly equal to 1.0. Since they also do not provide any insight regarding the market

index used or how their beta calculations are carried out, avoiding this site for ETF beta

information is advised.

The financial websites examined use a variety of market indexes for beta calculations of

ETF categories other than U.S. equity. This not only means that there are different beta figures

for bond, international, global, commodity, and currency ETFs, but that the interpretation of the


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beta measure provides an estimate of the risk level associated with adding the particular security

to a well-diversified portfolio of U.S. stocks. If the market proxy is something like the MSCI

EAFE index, then this changes the interpretation. A U.S. investor who primarily holds U.S.

equity can no longer look at beta and see whether or not the security in question has above or

below-average market risk relative to their current portfolio. The correct interpretation of this

alternative beta is now that it shows risk relative to a well-diversified portfolio of international

equity. Above (below) average market risk relative to international equity may or may not

translate to above (below) average market risk relative to the U.S. investors stock portfolio.

Another issue with the use of different indexes for calculating security betas relates to the

overall portfolio beta. A portfolios beta is calculated as the weighted average of the betas of the

securities that make up the portfolio. Unfortunately, this does not hold true if the betas

themselves are calculated differently, as can happen in a U.S. based portfolio comprised of U.S.

and international ETFs. The differences in betas due to the different market indexes are even

more pronounced for bond, commodity, and currency ETFs. Financial websites that continue to

use alternative market proxies should clearly explain the implications for interpreting the

resulting non-standard betas.

In summary, the ETF betas provided by the leading financial websites are a confusing

mess. Most websites provide little or no useful explanation of their beta calculations, and may

actually have information that could be misleading to the retail investor, who is not well versed

with the various nuances of modern portfolio theory. There are currently no standards in place


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highlighting that this is being done, as is the case with many financial websites, is even worse.

Users of these websites should demand more transparency regarding the financial information

provided and ensure that they are correctly interpreting the information provided.


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References

Agrrawal, Pankaj, and John Clark. 2007. ETF Betas: A Study of their Estimation Sensitivity to

Varying Time Intervals.Institutional Investor,Exchange-Traded Funds & Indexing

Innovations Issue, Vol. 41, 10 (Fall): 96-103.

Burton, Jonathon. 2008. MarketWatch: Financial Advisors Shift to ETFs. Wall Street Journal.

(September 7): 3.

Corhay, Albert, 1992. The Intervalling Effect Bias in Beta: A Note. Journal of Banking and

Finance.16, 1 (February): 61-73.

Groenewold, Nicolaas, and Patricia Fraser. 2000. Forecasting Beta: How well does the 'Five-

Year Rule of Thumb' do?Journal of Business Finance & Accounting. 27, 7/8 (Sep/Oct):

953-982.

Graham, John R. and Harvey Campbell. 2001. The Theory and Practice of Corporate Finance:

Evidence from the Field.Journal of Financial Economics. 60, 2 (May/June): 187-243.

Hawawini, Gabriel A. 1980. An Analytical Examination of the Intervalling Effect on Skewness

and Other Moments.Journal of Financial and Quantitative Analysis. 15, 5 (December):

1121-1127.

Hawawini, Gabriel A., and Ashok Vora. 1980. Evidence of Intertemporal Systematic Risks in

the Daily Price Movements of NYSE and AMEX Common Stocks.Journal of Financial

and Quantitative Analysis. 15, 2 (June): 331-339.

Ho, Li-Chin Jennifer and Jeffrey J Tsay. 2001. Option Trading and the Intervalling Effect Bias


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Levy, Haim, Ilan Guttman, and Isabel Tkatch. 2001. Regression, Correlation, and the Time

Interval: Additive-Multiplicative Framework.Management Science. 47, 8 (August):

1150-1159.

Reilly, Frank K., David J. Wright. 1988. A Comparison Of Published Betas.Journal of

Portfolio Management. 14, 3 (Spring): 64-69.

Smith, Keith V. 1980. The Effect of Intervalling on Estimating Parameters of the Capital Asset

Pricing Model.Journal of Financial and Quantitative Analysis. 13, 2 (June) 313-332.


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Figure 1: Yahoo! Finance Betas vs. S&P 500 Calculated Betas

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

-0.5 0.0 0.5 1.0 1.5 2.0 2.5

S&P 500 Calculated Beta

Correlation coefficient = -0.2313p = 0.0039

20


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Figure 2: MSN Money Betas vs. Calculated S&P 500 Betas

-5.00

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

-1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50 3.00

Calculated S&P 500 Betas


21


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Figure 3: Morningstar Betas vs. S&P 500 Calculated Betas

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

-0.50 0.00 0.50 1.00 1.50 2.00 2.50



22


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Figure 4: Google Finance Betas vs. S&P 500 Calculated Betas

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0


23

Correlation coefficient = 0.6416p = 0.0000


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Table 1: Comparative Betas of U.S. Equity ETFs where Google Assigned a Beta of 1

Beta Source

Ticker ETF NameYahoo!Finance

MSNMoney

GoogleFinance

Morningstar

VS S&P500

XRO Claymore/Zacks Sector Rotation --- 1.17 1.00 --- 1.14

DIA DIAMONDS 0.98 0.97 1.00 0.97 0.97

ITA iShares Dow Jones U.S. Aerospace & Defense --- 1.62 1.00 --- 1.39

IAI iShares Dow Jones U.S. Broker-Dealers --- 1.71 1.00 --- 1.77

IHF iShares Dow Jones U.S. Health Care Providers --- 1.04 1.00 --- 0.94

ITB iShares Dow Jones U.S. Home Construction --- 0.35 1.00 --- 0.67

IHI iShares Dow Jones U.S. Medical Devices --- 0.57 1.00 --- 0.56

IEO iShares Dow Jones U.S. Oil & Gas Exploration& Production

--- 0.76 1.00 --- 0.74

IEZ iShares Dow Jones U.S. Oil Equipment &Services

--- 0.75 1.00 --- 0.74

IHE iShares Dow Jones U.S. Pharmaceutical --- 0.56 1.00 --- 0.77

IAT iShares Dow Jones U.S. Regional Banks --- 0.95 1.00 --- 0.83

NYC iShares NYSE 100 1.01 1.00 1.00 1.00 1.06

IWC iShares Russell Microcap --- 1.08 1.00 1.17 1.16

SLX Market Vectors Steel --- 1.24 1.00 --- 1.46

PPA PowerShares Aerospace & Defense --- 1.44 1.00 --- 1.23

PZD PowerShares Cleantech --- 1.53 1.00 --- 1.29

PJB PowerShares Dynamic Banking --- 0.82 1.00 --- 0.64

PXE PowerShares Dynamic Energy E&P --- 0.74 1.00 --- 0.88

PTH PowerShares Dynamic Heathcare --- 0.77 1.00 --- 0.82

PXJ PowerShares Dynamic Oil Services --- 0.82 1.00 --- 1.04PRF Powershares FTSE RAFI US 1000 --- 1.05 1.00 --- 1.06

PSP PowerShares Listed Private Equity --- 1.44 1.00 --- 1.45

PIV PowerShares Value Line Timeliness --- 1.17 1.00 --- 1.19

PHO PowerShares Water Resource Port --- 1.24 1.00 --- 1.24

PWC PowerShares XTF: Dynamic Market 0.92 0.90 1.00 0.93 0.95

DDM ProShares Ultra Dow30 --- 1.91 1.00 --- 1.97

MVV ProShares Ultra MidCap400 --- 2.15 1.00 --- 2.04QLD ProShares Ultra QQQ --- 3.10 1.00 --- 2.78

SSO ProShares Ultra S&P500 --- 1.97 1.00 --- 1.99

ELG SPDR DJ Wilshire Lg Cap Growth 0.98 1.04 1.00 0.98 0.98

XHB SPDR Homebuilders --- 0.49 1.00 --- 0.91


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XOP SPDR S&P Oil & Gas Explor & Product --- 0.76 1.00 --- 0.77

XRT SPDR S&P Retail --- 0.89 1.00 --- 0.95

XLI SPDR Select Sector - Industrial 0.96 1.04 1.00 0.96 0.98

VIG Vanguard Div Appreciation --- 0.77 1.00 --- 0.80

VOT Vanguard Mid-Cap Growth --- 1.09 1.00 --- 1.12

VTV Vanguard Value 1.01 0.95 1.00 1.01 1.01

DTN WisdomTree Dividend Top 100 --- 1.00 1.00 --- 1.00

DHS WisdomTree High-Yielding Equity --- 1.05 1.00 --- 1.07

DLN WisdomTree LargeCap Dividend --- 0.94 1.00 --- 0.98

Average 0.98 1.09 1.00 1.00 1.10

Note: Google provides no explanation of their beta calculations.All betas as of Sept 12, 2008


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Table 2: Comparative Betas of Bond ETFs

Beta Source

Ticker ETF Name

Yahoo!

Finance

MSN

Money

Google

Finance

Morning

star

VS S&P

500LQD iShares GS $ InvesTopTM Corporate Bond 1.20 0.80 -0.07 1.19 0.08

SHY iShares Lehman 1-3 Year Treasury Bond 0.49 0.79 -0.04 0.49 -0.06

TLT iShares Lehman 20 Year Treasury Bond 2.72 2.53 -0.26 2.73 -0.25

IEF iShares Lehman 7-10 Year Treasury Bond 1.69 2.07 -0.20 1.70 -0.20

AGG iShares Lehman Aggregate 1.01 1.04 --- 1.01 -0.02

TIP iShares Lehman TIPS Bond 1.53 1.79 -0.15 1.49 -0.19

Average 1.44 1.50 -0.14 1.44 -0.11


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Table 3: Comparative Betas of International and Global ETFs

Beta Source

Ticker ETF NameYahoo!Finance

MSNMoney

GoogleFinance Morningstar

Calculated

vs S&P500

EEB Claymore/BNY BRIC --- 2.17 1.00 --- 2.00

FXI iShares FTSE/Xinhua China 25 1.91 2.54 1.62 1.94 2.09

ILF iShares Latin America 40 1.49 1.46 1.54 1.52 1.55

EWA iShares MSCI Australia 1.35 1.43 0.96 1.35 1.40

EWO iShares MSCI Austria 1.36 1.36 0.73 1.35 1.44

EWK iShares MSCI Belgium 1.14 1.08 1.22 1.10 1.41

EWZ iShares MSCI Brazil 1.96 2.14 1.63 1.99 1.93

EWC iShares MSCI Canada 1.14 1.20 - 1.11 1.22

EFA iShares MSCI EAFE 0.99 0.99 1.00 0.99 1.10

EEM iShares MSCI Emerging 1.52 1.57 1.75 1.55 1.60

EZU iShares MSCI EMU 1.08 1.12 1.30 1.09 1.34

EWQ iShares MSCI France 1.06 1.08 1.24 1.06 1.29

EWG iShares MSCI Germany 1.12 1.15 - 1.15 1.38

EFG iShares MSCI Growth --- 0.99 1.00 0.98 1.05

EWH iShares MSCI Hong Kong 1.18 1.53 0.98 1.20 1.44

EWI iShares MSCI Italy 1.01 1.02 0.99 1.02 1.22

EWJ iShares MSCI Japan 0.82 0.69 0.54 0.81 0.67

EWM iShares MSCI Malaysia 0.73 0.77 0.82 0.82 0.91

EWW iShares MSCI Mexico 0.93 0.54 1.36 0.97 1.25

EWN iShares MSCI Netherlands 1.10 1.14 1.34 1.06 1.37

EPP iShares MSCI Pacific Ex-Japan 1.29 1.43 0.97 1.30 1.40

EWS iShares MSCI Singapore 1.19 1.36 1.10 1.26 1.47

EZA iShares MSCI South Africa 1.88 1.64 1.48 1.85 1.80

EWY iShares MSCI South Korea 1.44 1.58 1.73 1.54 1.39

EWP iShares MSCI Spain 0.99 1.18 1.09 1.03 1.12

EWD iShares MSCI Sweden 1.38 1.26 1.69 1.37 1.60

EWL iShares MSCI Switzerland 0.68 0.56 1.00 0.69 0.79

EWT iShares MSCI Taiwan 1.15 1.31 1.13 1.15 1.26EWU iShares MSCI United Kingdom 0.94 0.95 1.00 0.92 1.05

EFV iShares MSCI Value --- 0.99 1.00 1.02 1.16

IEV iShares S&P Europe 350 0.99 1.01 1.13 1.00 1.08

IOO iShares S&P Global 100 0.79 0.82 0.96 0.77 1.00


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IXP iShares S&P Global Telecommunications 1.07 1.14 1.07 1.06 1.08

JXI iShares S&P Global Utilities Sector --- 0.68 1.00 --- 0.82

ITF iShares S&P/TOPIX 150 0.84 0.70 0.53 0.82 0.69

ADRD PowerShares BLDRS Developed Markets 100ADR

1.00 1.01 1.15 0.99 1.09

ADRE PowerShares BLDRS Emerging Markets 50ADR

1.56 1.64 1.74 1.56 1.68

PGJ PowerShares Golden Dragon Halter USXChina

1.86 1.41 2.11 1.85 2.26

PID PowerShares Intl Dividend Achievers --- 0.94 1.00 --- 1.11

FEZ SPDR DJ EURO STOXX 50 1.02 1.11 1.36 1.05 1.28

DGT SPDR DJ Global Titans 0.66 0.68 0.87 0.65 0.91

FEU SPDR DJ STOXX 50 0.94 1.00 1.11 0.95 1.11

VWO Vanguard Emerging Markets 1.52 1.61 1.44 1.55 1.51

VGK Vanguard European 0.99 1.00 1.01 0.99 1.08

VPL Vanguard Pacific 0.94 0.90 0.82 0.94 0.89

DWM WisdomTree DEFA --- 1.06 1.00 --- 1.12

DTH WisdomTree DEFA High-Yielding Equity --- 1.06 1.00 --- 1.16

DOO WisdomTree International Dividend Top 100 --- 1.07 1.00 --- 1.22

DOL WisdomTree International LargeCap Dividend --- 1.07 1.00 --- 1.11

DIM WisdomTree International MidCap Dividend --- 0.93 1.00 --- 1.07

DLS WisdomTree International SmallCap --- 0.94 1.00 --- 1.06

DND WisdomTree Pacific ex-Japan Total Dividend --- 1.46 1.00 --- 1.33

Average 1.16 1.15 1.13 1.16 1.25


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Table 4: Comparative Betas of Commodity ETFs

Beta Source

Ticker ETF Name

Yahoo!

Finance

MSN

Money

Google

Finance

Morning

star

VS S&P

500IAU iShares COMEX Gold 11.85 27.34 -0.18 11.42 -0.07

GSG iShares GSCI Commodity --- 0.23 1.00 --- -0.32

SLV iShares Silver --- 30.83 1.00 --- -0.14

GDX Market Vectors TR Gold Miners --- 32.14 1.00 --- -0.01

GLD SPDR Gold 12.85 27.79 0.41 12.43 -0.06

USO United States Oil --- 0.69 1.00 --- -0.24

Average 12.35 19.84 0.71 11.93 -0.14


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Table 5: Comparative Betas of Currency ETFs

Beta Source

Ticker ETF Name

Yahoo!

Finance

MSN

Money

Google

Finance

Morning

star

VS S&P

500DBV PowerShares DB G10 Currency Harvest --- 1.05 1.00 --- 0.38

FXA Rydex CurrencyShares Australian Dollar --- 8.22 1.00 --- 0.21

FXB Rydex CurrencyShares British Pound Sterling --- 3.10 1.00 --- 0.05

FXC Rydex CurrencyShares Canadian Dollar --- 2.88 1.00 --- 0.42

FXE Rydex CurrencyShares Euro Currency --- 5.80 1.00 --- -0.04

FXF Rydex CurrencyShares Swiss Franc --- 10.56 1.00 --- -0.34

Average --- 5.27 1.00 --- 0.11


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Table 6: Financial Websites Market Indices Used for Different ETF Beta Calculations

Site US Equity

US Fixed

Income International Global Commodity Currency

AOL Money &Financemoney.aol.com

S&P 500? N/A MSCI EAFE

? Not disclosed Not disclosed N/A

Bloombergwww.bloomberg.com

S&P 500+ S&P 500

+ Varies by fund

+ Varies by fund

+ Varies by fund

+ Varies by fund

+

CNNMoney.commoney.cnn.com

N/A N/A N/A N/A N/A N/A

Google Financefinance.google.com

Varies by fund? S&P 500

? Varies by fund

? Varies by fund

? Varies by fund

? Varies by fund

?

Morningstar1

www.morningstar.comS&P 500

+ Lehman

Aggregate Bond+

MSCI EAFE+ Varies by fund

+ ML USD

LIBOR 3M+

ML USD

LIBOR 3M3

MSN MoneyMoney.msn.com

S&P 500+ Lehman

Aggregate Bond+

MSCI EAFE+ Varies by fund

+ Varies by fund

+ Not disclosed

Reuterswww.reuters.com

S&P 500? S&P 500

? S&P 500

? Not disclosed Not disclosed Not disclosed

SmartMoney.comwww.smartmoney.com

S&P 500* S&P 500?2 S&P 500? S&P 500? S&P 500? S&P 500?

TheStreet.comwww.thestreet.com

S&P 500? S&P 500

? S&P 500

? S&P 500

? S&P 500

? S&P 500

?

Yahoo! Financefinance.yahoo.com

S&P 500* LehmanAggregate Bond*

MSCI EAFE? Varies by fund

? ML USD

LIBOR 3M?

N/A

+

Market index used is clearly identified along with the beta estimate.* Market index used can be found on the financial website with some searching.

? No indication of market index used was found on the financial website itself. This is what we believe the market index to bebased upon comparisons of betas of other sites or our calculations, or by searching information from other sites.

1 Morningstar also presents betas based on best fit indices.2 SmartMoneys glossary definition of beta states that their fixed income betas are calculated using the Lehman Aggregate Bond

Index, but as far as we can tell, this is not the case.3

No Morningstar betas were shown for currency ETFs in our sample, but an index was noted.N/A Not available. Betas were not supplied for our sample ETFs in this category.

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