Redefining Credit Risk - IndexUniverse.com

Redefining Credit Risk
William Mast
Credit Derivatives Indexes
Gavan Nolan and Tobias Sproehnle
A Fixed-Income Roundtable
Ken Volpert, Jason Hsu, Waqas Samad, Larry Swedroe and more
The Impact of Bond Fund Flows
David Blanchett
Plus David Blitzer on bubbles, Jeremy Schwartz on dividends and buybacks, Francis Gupta on country
classifications and a biography on Bogle

www.journalofindexes.com
Vol. 14 No. 4
features
Redefining Credit Risk
By William Mast ....................................10
Are CDS better than ratings when measuring bond risk?
Credit Derivatives Indexes: Methodology And Use
By Gavan Nolan and Tobias Sproehnle . . . . . . . . . . . . . . . 14
How to build a credit derivatives index.
A Fixed-Income Roundtable
Waqas Samad, Larry Swedroe, Ken Volpert and more . . . 20
Our panel of experts digs into the bond market.
The Impact Of Fund Flows On Fixed-Income
Mutual Fund Performance
By David Blanchett .................................28
Are bond fund inflows costing mutual fund investors?
Bubble Bubble, Toil And Trouble
By David Blitzer ....................................32
Bubbles aren’t as aberrant as you’d think.
The Importance Of Dividends And Buybacks
Ratios For Gauging Equity Values
By Jeremy Schwartz.................................34
Two measures speak volumes about the market.
Developed, Emerging Or Frontier Markets?
By Francis Gupta ...................................38
A new perspective on classifying markets.
‘The Devil’s Invention’
By Lewis Braham ...................................44
How the index fund industry began.
A History Of Money . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
How much do you think you know?
news
Russell Launches First In-House ETFs . . . . . . . . . . . . . . . . 52
Nasdaq-100 Rebalance Shakes Up Q’s . . . . . . . . . . . . . . . . 52
Case-Shiller Indexes Suggest Housing Slump . . . . . . . . . . 52
ProShares Expands Bond Lineup . . . . . . . . . . . . . . . . . . . . . 53
Indexing Developments ............................. 53
Around The World Of ETFs .......................... 55
Back To The Futures ................................ 57
Know Your Options ................................ 57
From The Exchanges ............................... 57
data
Selected Major Indexes .............................59
Returns Of Largest U.S. Index Mutual Funds . . . . . . . . . . 60
U.S. Market Overview In Style . . . . . . . . . . . . . . . . . . . . . . . 61
U.S. Industry Review ................................62
Exchange-Traded Funds Corner . . . . . . . . . . . . . . . . . . . . . 63
10
28
44
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July / August 2011
1

Contributors
David Blanchett
David Blanchett, CFA, is the director of Consulting and Investment
Research for the Retirement Plan Consulting Group at Unified Trust
Company in Lexington, Ky. He is primarily responsible for helping 401(k)
advisors with fiduciary, compliance, operational and investment issues
relating to Unified Trust’s retirement plan services. Blanchett has published
over 30 papers in various industry journals. He recently completed his MBA
at the University of Chicago Booth School of Business.
David Blitzer
David Blitzer is managing director and chairman of the Standard &
Poor’s Index Committee. He has overall responsibility for security selection
for S&P’s indexes and index analysis and management. Blitzer previously
served as chief economist for S&P and corporate economist at The
McGraw-Hill Companies, S&P’s parent corporation. A graduate of Cornell
University with a B.S. in engineering, he received his M.A. in economics
from George Washington University and his Ph.D. in economics from
Columbia University.
Lewis Braham
Lewis Braham is a writer who has covered investing and the mutual fund
industry since 1996. His work has appeared in BusinessWeek, SmartMoney,
Bloomberg Markets, Fortune and Financial Planning, in addition to a range
of investment newsletters. Braham has an MFA in creative writing from
CUNY’s Brooklyn College. He lives in Pittsburgh with his wife and his dog.
“The House That Bogle Built” is Braham’s first book.
William Mast
William Mast is director of fixed-income indexes for Morningstar’s Index
business, responsible for Morningstar’s bond-index efforts, including business
strategy, research and new product and business development.
Previously, he spent more than 20 years at top-tier investment banks in
a variety of fixed-income disciplines. Mast holds a bachelor’s degree in
economics from St. Bonaventure University and an MBA from New York
University’s Stern School of Business.
Gavan Nolan
Gavan Nolan is a director of credit research at Markit and a CDS market
specialist. Having joined Markit in 2001, he has written about the credit
markets from the accounting scandals of the last decade right through to
the current European sovereign debt crisis. Previously, Nolan worked at J.P.
Morgan in interest rate markets. He holds a B.Sc Economics degree from
Queen Mary College, University of London.
Jeremy Schwartz
Jeremy Schwartz, CFA, is director of research at WisdomTree Investments
Inc., responsible for the WisdomTree equity index construction process and
overseeing research coverage across the WisdomTree equity family. Prior
to joining the company, he was Professor Jeremy Siegel’s head research
assistant and helped with the research and writing of “Stocks for the Long
Run” and “The Future for Investors.” Schwartz is a graduate of The Wharton
School of the University of Pennsylvania.
Tobias Sproehnle
Tobias Sproehnle, CFA, is a director of credit data and indexes at Markit,
having joined the company in 2006 to manage its iTraxx series of credit
default swap indexes in Europe and Asia. Prior to Markit, he was responsible
for product development and strategy for fixed income and credit
derivatives at Eurex. Sproehnle holds a diploma in economics and information
management from the University of Würzburg, Germany.
2 July / August 2011

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Cliff Weber: NYSE Euronext
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Bernstein, Herb Blank, Srikant Dash, Fred
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4 July / August 2011
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What’s really in your ETF index?
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Editor’s Note
Risky Business
Jim Wiandt
Editor
With the global economy’s condition currently best described as “precarious”
in the aftermath of the last few years of financial turmoil, it’s not surprising
that risk is at the forefront of investors’ minds. Similarly, it’s not surprising
that the past few years have seen renewed attention paid to fixed-income markets, with
an emphasis on “fixed” at a time when not much else seemed to be. All of this makes
it apt that the current issue of the Journal of Indexes takes an up-close look at credit
default swaps and the broader fixed-income asset class of which they are a part.
Morningstar’s Bill Mast opens the issue with a commentary—backed by hard data—
on the usefulness of the information provided by credit default swaps. Mast presents
evidence that suggests the CDS market may provide better insight into a company’s
creditworthiness than the major ratings agencies, and argues that fixed-income indexes
should make use of that information.
Markit’s Gavan Nolan and Tobias Sproehnle follow with an explanation of how their
company constructs its CDS indexes and how they can be used. David Blanchett steers
the conversation towards what the huge influx of investor dollars into fixed-income
mutual funds means for fund holders, and provides some compelling data.
This issue’s roundtable discussion includes a broad cast of fixed-income experts—
Barclays Capital’s Waqas Samad, Research Affiliates’ Jason Hsu, Vanguard’s Ken
Volpert and more—opining on everything from the value of ratings to the validity of
active management in fixed income to the best way to construct a bond index.
David Blitzer weighs in with an interesting column that points out that bubbles
are natural and regularly occurring market phenomena rather than random lightning
strikes. WisdomTree’s Jeremy Schwartz explores what stock buybacks and dividends
tell us about the markets, and Francis Gupta of Dow Jones Indexes wraps up the issue
by laying out a new blueprint for sorting countries into the developed, emerging and
frontier buckets.
Finally, if you still haven’t had your fill, test your knowledge of the history of money
with our back-page crossword puzzle.
Wishing you sound investing in these risky times,
Jim Wiandt
Editor
8
July / August 2011

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prospectus and its summary prospectus (if available) contain this and other information about the fund. Please read the prospectus and summary
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Redefining Credit Risk
Are credit default swaps a viable alternative to credit ratings?
By William Mast
10 July / August 2011

For more than a century, the big three bond rating
agencies—Moody’s, Standard & Poor’s (S&P) and
Fitch—have been the unchallenged arbiters of corporate
creditworthiness. Rating references are embedded
in hundreds of guidelines, laws and private contracts that
affect a broad range of financial concerns.
The recent financial crisis, however, laid bare a material
weakness in the traditional agencies’ models: Their
ratings are backward-looking because they are predicated
on historical data that is observed at a discrete point in
time. Given this constraint, these agencies have not been
favorably positioned to react quickly to rapid changes in a
creditor’s financial health. Hence, evidence of accounting
fraud in a company’s financial statements may elude their
scrutiny. Additionally, the legacy credit rating agencies
have demonstrated that they remain ill-equipped to assess
the risks of some complex, structured products.
There is now considerable momentum in the markets
and on legislative agendas to explore and evaluate alternative
ways to assess the credit ratings of public companies.
Independent credit research efforts—some housed under
the same roof as the big three—have already broken the
issuer-paid model and are using real-time market factors in
their evaluations. In fact, there’s a body of recent research
that points to the credit default swap (CDS) market as a
source for a more fluid, market-driven metric to gauge the
creditworthiness of an issuer.
The Big Three: A Brief History
Today Moody’s, S&P and Fitch are a colossal force in the
capital markets. Their predominance can be traced back
to 1909, when John Moody first assigned a letter grade to
railroad bonds with the intention of giving investors an easy
way to evaluate creditworthiness. Poor’s Publishing, which
was the predecessor to S&P, began rating bonds in 1916, and
Fitch followed in 1924. All three charged investors for their
research. Regulators started using the rating agencies in the
1930s to evaluate the health of bank balance sheets, and in
the process raised the agencies’ profiles and profitability.
The economic stability of the post-World War II years
diminished their profiles until the 1970s. In 1975, the
Securities and Exchange Commission (SEC) recognized
certain firms as nationally recognized statistical rating
organizations (NRSRO), which indirectly made it a requirement
for bond issuers to attain a rating. Around this time,
the business model changed from investor-pay to issuerpay.
Subsequently, and to this day, regulators have increasingly
relied on the agencies to police debt investing.
That model is now facing challenges. In 2006, the
agencies got a hint of what may lie ahead. On the
heels of well-publicized corporate skulduggery—Enron
and WorldCom come to mind—Congress passed the
Credit Rating Agency Reform Act, which gave the SEC
legal authority to require rating agencies operating
with NRSRO status to register and comply with certain
requirements. The core of the requirements involved
periodic reporting and disclosure, but fell short of giving
the SEC regulatory authority over the credit rating process;
namely, procedures and methodologies.
There is a widely perceived notion that the agencies
and their flawed models contributed to the global financial
crisis in 2008, from which we still haven’t completely
recovered. Talk of additional regulation in the wake of the
crisis has focused on eliminating conflicts of interest associated
with the issuer-paid model, improving the quality
and timeliness of the agencies’ ratings, increasing transparency
and replacing self-regulation with more stringent
government oversight.
Market Indexes And Ratings
The potential for disconnect between the ratings agencies
and the market’s risk perception can be illustrated
in a yield-spread premium-dispersion graphic. Figure
1 is a plot of individual bond-yield spread premiums—
from the Morningstar Corporate Bond Index in early
2010—against a composite rating of Moody’s, S&P and
Fitch. If we assume any given rating is a uniform measure
regardless of the industry or issuer, one would logically
expect to see a much tighter range of yield spreads
for any given rating. Where this is not the case, we can
assume the market’s perception of credit risk is, to some
degree, at odds with the current rating.
If we conclude there are viable alternatives to the rating
agencies, we should also consider other options to
the current offering of bond market indexes. The mainstream
fixed-income indexes have always been defined
by the rating agencies—including Morningstar’s current
indexes. This is most evident where the clear demarcation
between investment grade and below investment grade
(commonly referred to as “high yield” or “junk”) has not
faded over time. New index methodologies have always
evolved with the markets. For example, as average issue
sizes grew over time, the index providers increased the
amount outstanding required for inclusion. And as smaller
sectors matured and proved to have sufficient liquidity,
those sectors were added to aggregate indexes. To the
degree that alternatives to the ratings agencies emerge,
these new options should help define new indexes.
Figure 1
Spread (%)
7
6
5
4
3
2
1
0
Source: Morningstar
US Corporate Bond Yield Spread Vs. Ratings
10
2 3 4 5 6 7
Composite Rating
8 9 10 11 12
www.journalofindexes.com July / August 2011
11

Credit Default Swaps
Origins
Developed in the late 1990s, a credit default swap,
or CDS, was originally designed to reduce the risk
that commercial bank loans posed to financial institutions.
A CDS is a contract between parties that is
meant to insure a buyer against credit deterioration
or full-blown default. The buyer pays a premium to
the seller in return for credit protection. CDS prices
are a fairly pure indicator of credit risk because the
structure separates the credit risk component from
the other asset risks, such as interest-rate risk and
currency risk.
Growth
Growth of the CDS market since the start of the
last decade has been exponential, only slowing in
the wake of the financial crisis. At its peak of over
$65 trillion in 2007, the CDS market was more than
$20 trillion larger than the estimated market for
bonds and structured products.
Credit default swaps are not traded on an
exchange. While this lack of transparency initially
concerned regulators, it was the credit crisis and
the illustrated systematic risk that led to corrective
action. In 2009 the global industry agreed upon
standards administered by the International Swaps
and Derivatives Association that created central
clearing operations—thereby reducing counterparty
risk—and implemented international standards
for contract terms.
Credit Default Swaps: A Worthy Market Measure?
As stated earlier, one main criticism levied at the rating
agencies is the historical, point-in-time nature of their ratings.
A better model for determining an issuer’s creditworthiness
could be derived from real-time information.
For starters, a security’s market price reflects the
expected performance of the entity, the potential for performance
to exceed or fall short of expectations, sector
outlooks, geographic performances, the potential for surprises
and the security’s liquidity. Market activity (including
trading volumes, historical trends, correlations and
volatility) adds to the picture.
A credit default swap, or CDS, is a contract between
parties that is meant to insure a buyer against credit
deterioration or outright default. The buyer pays a
premium to the seller, and in return, receives credit
protection. If a negative credit event occurs, the buyer
is compensated for losses incurred. The contracts are
an easy way to trade credit risk, and CDS prices are a
fairly pure indicator of credit risk, because the structure
separates the credit risk component from the other
embedded risks, such as interest-rate risk and currency
risk. Dominated by a handful of major financial institutions,
the CDS market today can exhibit technical spread
movements and reversals that are not always reflective
of actual market sentiment.
Despite some technical pressures and, at times, lack of
liquidity, the CDS market nevertheless provides the purest
independent measure of how the market perceives the
prospects of a given entity.
This raises a question: If appropriately harnessed and
interpreted, can the signals provided by the CDS market
improve investors’ ability to anticipate changes in an
issuer’s creditworthiness?
Research Support For Credit Default Swaps
As An Appropriate Measure Of Credit Risk
There’s a fairly large body of evidence that suggests
the answer to this question may be yes. In the late 1970s,
Weinstein (1977) and Pinches and Singleton (1978) presented
evidence that bond and stock price changes occur
well before the announcement of changes to a rating, and
in fact found there was little or no price response on the
announcement date.
Perraudin and Taylor (2004) presented evidence that
up to a quarter of some high-credit quality bond categories
carry ratings that are not consistent with their
market prices. A large fraction of the bonds that market
prices suggest are rated incorrectly experience ratings
changes within six months, consistent with the idea that
ratings changes lag market prices.
Blanco, Brennan and Marsh (2004) found that the CDS
market leads the bond market in determining the price of
credit risk. They argued that the price discovery in the CDS
market occurs because structural factors make it the most
convenient location for the trading of credit risk.
Also in 2004, Hull, Predescu and White found that the
credit default market anticipated rating agency reviews for
downgrades, actual downgrades and negative outlooks.
They also saw evidence of some predictive powers not specific
to the entity in question.
Fitch Solutions (2008) used CDS pricing to build market-implied
ratings and concluded there is a clear ability
Figure 2
($B)
80,000
60,000
40,000
20,000
Credit Default Swap
Notional Amount Outstanding
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: ISDA Market Survey
12 July / August 2011

to forecast future rating actions by examining CDS premiums.
And in 2009, Neziri showed that a one-month change
in a sovereign’s CDS premium tended to increase ahead of
a crisis in the stock market.
Examining distressed names, Batterman and Sonola
found in 2009 that, even though CDS and cash market
instruments were not always consistent with underlying
fundamentals, they did provide an independent view
of a company’s prospects. They went on to advise that
this market perception reflected in prices should not be
ignored, particularly when an instrument is trading at
extremely distressed levels.
Of course, the CDS market as it is today can’t provide
all of the answers. Concern over a perceived lack
of transparency and regulation in the CDS markets
was heightened during the financial crisis. In particular,
manipulators allegedly created heightened credit
concerns with purchases of credit default swaps on the
target, and then took a simultaneous short position in
the company’s stock in order to profit. As Preece (2009)
points out, however, this could only have happened if
CDS spreads were a leading indicator of equity prices.
The author concluded that the data revealed otherwise.
A comparison of the share price of financial companies
with their CDS spread indicates that the two measures
were moving in tandem, making it more difficult to
manipulate the market in this fashion.
Over time, measures of efficiency, transparency and
standardization in the CDS market will only improve,
thereby making it an even better gauge of an issuer’s creditworthiness.
No credit rating model is perfect, but when
appropriately harnessed and interpreted, the signals provided
by the CDS market can improve an investor’s ability
to anticipate events among issuers.
Conclusion
The rapid growth in the size of the CDS market, as well
as increasing transparency and standardization, make
it a useful gauge for price and risk discovery for bonds.
Such a CDS market may provide a viable alternative to
the current credit rating agency model. The pace of any
such transition is a valid concern. Agencies will push back
when they perceive a threat to their livelihoods; portfolio
mandates can’t change overnight, and the degree to
which the agencies are hardwired into the total market
infrastructure can’t be underestimated. Whatever the
pace, the bond market’s utilization of the rating agencies
is transitioning—and so should its indexes.
Sources
Batterman, James, CFA and Olu Sonola, CFA, “Credit Spreads and the Point of No Return: Highly distressed trading levels, anticipating default, and potential implications
for recognizing impairment,” CFA Magazine (March–April 2009), pp. 6-8, 28.
Blanco, Roberto, Simon Brennan and Ian W. Marsh, “An empirical analysis of the dynamic relationship between investment-grade bonds and credit default swaps,”
Bancode España, Madrid (2004).
Fitch Risk Performance Monitor—Fitch Solutions (December 2008), p. 8.
Hull, John, Mirela Predescu and Alan White, “The Relationship Between Credit Default Swap Spreads, Bond Yields, and Credit Rating Announcements,” Joseph L. Rotman
School of Management (January 2004).
Perraudin, William and Alex Taylor, “On the Consistency of Rating and Bond Market Yields,” Journal of Banking and Finance (2004), pp. 269-278.
Pinches, George and J. Clay Singleton, “The Adjustment of Stock Prices to Bond Ratings Changes,” Journal of Finance (1978), pp. 29-44.
Neziri, Hekuran, “Can Credit Default Swaps Predict Financial Crises? Empirical Study On Emerging Markets,” Journal of Applied Economic Sciences, Spiru Haret University,
Faculty of Financial Management and Accounting Craiova, vol. 4, issue 1(7) (Spring 2009)
Preece, Rhodri, “A Transparent Agenda: Investors Should Welcome Efforts to Improve Transparency in CDS Markets,” CFA Magazine (March–April 2009), pp. 16-17.
Stulz, René M., “Credit Default Swaps and the Credit Crisis,” Journal of Economic Perspectives, vol. 24, No. 1 (Winter 2010), pp. 73-92.
Weinstein, Mark, “The Effect of a Rating Change Announcement on Bond Prices,” Journal of Financial Economics 5 (1977), pp. 329-350.
Why advertise in the Journal of Indexes?
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www.journalofindexes.com July / August 2011
13

Credit Derivatives Indexes:
Methodology And Use
Innovation in CDS indexes
By Gavan Nolan and Tobias Sproehnle
14
July / August 2011

Credit default swap (“CDS”) indexes are now a fixture
of the credit markets. Their benefits have seen them
gain in popularity since their inception in 2001, and
index providers continue to innovate and create products
that reflect the changing economic landscape. In this
article, we dissect the world of CDS indexes through the
spectrum of the widely referenced Markit CDX and Markit
iTraxx family of CDS indexes.
Credit Indexes: An Overview
Synthetic credit indexes have not been around for
long, when compared with equities, bonds and commodities
indexes. They originated in 2001, when J.P. Morgan
launched the JECI and HYDI indexes. Morgan Stanley followed
suit with the launch of Synthetic TRACERS. The two
banks subsequently merged their indexes under the Trac-X
name in 2003. In parallel, iBoxx launched the iBoxx CDS
indexes. In 2004, Trac-X and iBoxx merged to form CDX in
North America and iTraxx in Europe and Asia.
After administering the CDX family of indexes and
acting as the calculation agent for the iTraxx indexes,
Markit acquired both families of indexes in November
2007, and now owns and manages the Markit iTraxx,
Markit CDX, Markit iTraxx SovX, Markit iTraxx LevX
and Markit LCDX families of CDS indexes as well as the
Markit iBoxx cash bond indexes. (See Figure 1.)
Credit indexes have expanded dramatically since their
humble beginnings: Markit iTraxx and Markit CDX index
trade volumes now exceed $70 billion a day and have
a net notional outstanding over $1.2 trillion. Together
they make up almost 50 percent of the market, when
compared with the notional outstanding in single-name
credit derivatives. Rules, constituents, coupons and
daily prices for the credit indexes are available publicly.
Investors have also been attracted by the fact that these
indexes can be priced more easily than a basket of cash
bond indexes or single-name CDS. Other advantages
include the fact that they are highly liquid and are also
efficient to trade due to a standardization of terms and
legal documentation. They are seen as a cost-efficient
way to trade portions of the market and are supported by
all major dealer banks, buy-side firms and third parties.
Markit’s CDS indexes are made up of the most liquid
part of the relevant single-name CDS market. The
Markit CDX North American Investment Grade Index,
for example, consists of 125 North American investmentgrade
names, selected according to a number of criteria,
including liquidity, ratings and underlying asset availability.
With this index, an investor interested in taking a
broad exposure to U.S. corporate investment-grade risk
Figure 1
Global Tradable Credit Indexes
Structured
Finance
Loans
US
US
Europe
Markit ABX, CMBX, TABX
Markit LCDX
Markit iTraxx LevX
LCDX
Tranches
Senior
Sovereigns
Markit iTraxx SovX
Western Europe
CEEMEA
Asia Pacific
Latin America
Global Liquid Investment Grade
G7
Fixed
Income
Synthetic
Fixed Income
Corporate
Bonds
Emerging
Markets
North America
Europe
Markit CDX EM
Markit CDX NA
Markit iTraxx Europe
Emerging Markets
EM Diversified
Investment Grade (IG, HiVol)
Crossover
High Yield (HY, HY.B, HY.BB)
Sectors
Europe (Europe, HiVol)
Non-Financials
Financials (Senior, Sub)
Crossover
Cash
Fixed Income
Municipal
Bonds
Bonds
Asia
US
Europe
Asia
US
Emerging Markets
Markit iTraxx Asia
Markit MCDX
iBoxx
Japan (Main, HiVol)
Asia ex-Japan (IG, HY)
Australia
Source: Markit
www.journalofindexes.com July / August 2011
15

can execute this strategy with a single CDS trade rather
than by purchasing 125 contracts simultaneously to
make up a diverse portfolio.
Credit Indexes: Structure
The indexes are “rolled” every six months—in March
and September—a process that includes reconsidering
the current constituents of the indexes and issuing new
indexes with revised constituents. Liquidity is the driving
factor when index constituents are considered for
inclusion. By using the most liquid entities traded in the
single-name CDS markets over the previous six months,
Markit ensures that these indexes are an accurate reflection
of the credit markets as well as a liquid tool for all
market participants.
The second major change during this “roll period”
is the extension of the time to maturity by six months.
The old contract—which in credit lingo is the “off-therun”
contract—remains in place until maturity, though
liquidity usually tends to decrease as the majority of
investors roll their exposure into the new contract (also
called the “on-the-run” contract). (See Figure 2.)
Trading Overview
Markit’s CDS indexes can be traded, with licensed
dealers providing liquidity on various platforms. Buying
and selling the indexes can be compared with buying
and selling portfolios of loans or bonds. A buyer takes
on the credit exposure to the loans or bonds, and is
exposed to defaults in the same way as a buyer of a bond
portfolio (buying the CDS index is equivalent to selling
credit protection on the underlying index constituents).
When an investor sells the index, credit exposure is passed
on to another party.
The indexes trade at a fixed coupon, which is paid quarterly
(except for the Markit CDX Emerging Markets Index,
which is semiannual) by the seller of the index (buyer of
protection), and upfront payments are made at initiation
and close of the trade to reflect the change in price.
Correspondingly, the protection seller, or buyer of the
index, receives the coupon. The indexes are quoted on a
clean (of coupon) basis. (See Figure 3.)
Spread Vs. Price Indexes
CDS indexes are traded either in spread or in price
terms (see Figure 4). This convention mimics the bond
Figure 2
Credit Index Construction
CDS trading
volumes
observed
from DTCC TIW
Rules
applied
Provisional
membership
Entities and
reference
obligations
Final
Provisional
membership
membership
list
Provisional
Coupon
membership
levels
Provisional
Trading
membership
begins
Rules-based
construction based
on CDS volumes
from DTCC TIW
Index rules
applied to each
index family
Published on
website
Agreed by
participating
dealers
Published on
website
Agreed by
participating
dealers
On
March/September
20
Source: Markit
Figure 3
Trading Example
'$(,#$620 #$#(,.0("$(,2'(1$6 +.*$
* 3,"'$15(2' .0("$-%-,September 20,
,# 6$#"-3.-,-%,4$12-0!371
,-2(-, *.0-2$"2(-,-,2'$(,#$6-,
-4$+!$0 5'$,2'$1.0$ #' 1+-4$#2-
,#"-00$1.-,#(,&.0("$(12'$.0("$(1. 0
+(,312'$.0$1$,24 *3$-%2'$1.0$ ##($0$,"$1
,4$12-0+ )$1 ,3.%0-,2. 7+$,22- ""-3,2
%-02'$+-4$+$,2(,2'$1.0$ #1
7+$,2
, ##(2(-, '$5(**0$"$(4$2'$
""03$#(,2$0$123.2-20 #$# 2$
1'$5(**' 4$2-+ )$2'$%3**
"-3.-,-,"-3.-,. 7+$,2# 2$
82'(11(+.*($1-.$0 2(-,1 1 **
.0-2$"2(-,!37$01+ )$2'$1 +$
. 7+$,2-,2'$ same date
$2-32-5
December 208,4$12-0
. 712'$6$#"-3.-,
1'-32-5
March 13 8,4$12-0"*-1$1
2'$20 #$5'$,2'$1.0$ #(1
,#2'$$/3(4 *$,2.0("$(1
,4$12-0. 712'$
""03$#(,2$0$123.2-20 #$
# 2$ ,#0$"$(4$1. 7+$,2
,-5
8
Source: 0)(2
16
July / August 2011

Figure 4
Spread
Price
Trading Parameters
CDX (IG, XO, HVOL), iTraxx (Europe, Japan,
Asia ex-Japan, Australia), SovX, MCDX
CDX (HY, EM, EM.Div), LCDX, LevX
risky duration of the credit is multiplied by the difference
between the current spread of the credit and the coupon
PGUIFJOEFY5IJTHJWFTUIF17POFBDIDPNQPOFOU'PS
example, if a credit is trading at 200 bps with a risky duration
of 3.75 years, and the index coupon is 150 bps, then
UIF17PGUIFDPOTUJUVFOUJT
markets, where some bonds trade on a yield basis and
others on price.
Prices can be converted into spreads, and vice versa,
using standardized models. Intuitively, if an index has
a fixed coupon of 60 and the current coupon is 90, it is
positive for the protection buyer (they are paying 60 for
something that is currently worth 90). The price is inversely
related to spread, so the price of the index at 90 is lower
than the price at 60, and as the protection buyer is short the
credit, a drop in price is positive.
Markit calculates the official levels for the Markit iTraxx
and CDX suite of indexes based on their regional market
close times. In addition, theoretical index spreads and prices
are calculated based on the contributions received for the
Total Return Credit Indexes
Another way of displaying Markit’s CDS indexes is to use
its total return versions. In contrast to the price and spread
indexes, total return index levels mimic the position of an
investor in the credit index market who “rolls” his position
into the relevant on-the-run contract in case of a regular
roll in March and September.
At a given point in time, only the most recently available
index CDS return is included in any one index. The
return of the index therefore reflects the value of exiting
the long risk position in the old Markit iTraxx contract and
simultaneously entering the new contract at mid at the
end of the first day of trading of the new contract (transacting
at mid means transaction costs are not included).
By mimicking an investor position, total return indexes are the only
CDS indexes that are linked over time. Credit total return indexes are
available as long and short versions of the European credit indexes.
underlying index components. These theoretical index levels
are calculated using the following methodology:
r5IFTVSWJWBMQSPCBCJMJUZPGFBDIDPOTUJUVFOUBUFBDI
coupon payment date is calculated using the Markit
composite credit curve and recovery rate for each of the
index constituents.
r5IFQSFTFOUWBMVF 17PGFBDIJOEFYDPOTUJUVFOUJT
then calculated using the trade details of the index (as
described below).
r5IF17PGUIFJOEFY XFJHIUFEBWFSBHFPGUIF17TPG
the constituents) and the accrued interest on the index
(weighted average of the accrued interest of the index
constituents) are calculated.
r 5IFPSFUJDBM QSJDF PG UIF JOEFY JT DBMDVMBUFE BT
17BDDSVFE
r 5IF JOEFY UIFPSFUJDBM TQSFBE JT TPMWFE BT UIF GMBU
DVSWFUIBUHJWFTUIFJOEFY17VTJOHUIFJOEFYSFDPWFSZ
rate assumption.
5IF 17 PG FBDI JOEFY DPOTUJUVFOU DBO CF DBMDVMBUFE
using one of two methods: either a simplified model
using risky duration only for each credit in the index
that generates a decent approximation, or the hazard
rate model for each underlying component of the index.
This will generate a more accurate value, as it allows for
curvature in the credit spread curve.
For small differences in fixed and current coupons, the
two valuation methods will have similar results. The hazard
rate model will give better results for large movements
in the spread. In the simple valuation methodology, the
Therefore the roll transaction costs are 1 percent of the
respective “old” series coupon plus 1 percent of the
respective “new” series coupon.
By mimicking an investor position, total return indexes
are the only CDS indexes that are linked over time. Credit
total return indexes are available as long and short versions
of the European credit indexes.
Markit iTraxx SovX: A Case Study
If an index provider had tried to launch a product
based on western European sovereign CDS in 2007, the
reactions from dealers and investors would probably
have ranged from apathetic to incredulous. But everything
changed when the global economy subsequently
went through the worst recession since the 1930s. A
combination of automatic stabilizers, additional fiscal
stimuli and bailouts for ailing banks left many governments
with enormous budget deficits. Despite previously
being considered risk free, many European sovereigns
are now perceived by credit investors as some of the
riskiest names in the world.
How do we know this? Because the sovereign CDS
market has developed in tandem with the deterioration in
government credit over the last three to four years. CDS on
sovereign issuers such as the U.K. were rarely traded prior
to 2007; the U.K.’s five-year spread of 1 bp denoted the
risk-free standing of the government. Now the U.K. has the
sixth-highest amount of net notional outstanding of any
name—corporate, financial or sovereign (according to sta-
www.journalofindexes.com July / August 2011
17

Figure 5
Deterioration In Western European Sovereign Credit
230
210
190
170
150
130
110
90
70
20.04.2010
04.05.2010
18.05.2010
01.06.2010
15.06.2010
29.06.2010
13.07.2010
27.07.2010
10.08.2010
24.08.2010
07.09.2010
21.09.2010
05.10.2010
19.10.2010
02.11.2010
16.11.2010
30.11.2010
14.12.2010
28.12.2010
11.01.2011
25.01.2011
08.02.2011
22.02.2011
08.03.2011
22.03.2011
05.04.2011
19.04.2011
Markit iTraxx SovX Western Europe Markit iTraxx Europe Senior Financials Markit iTraxx Europe
Source: Markit
tistics from the Depository Trust & Clearing Corporation).
Even Italy, which tops the volumes table, was trading as
tight as 5 bp in the summer of 2007.
By 2009, investors were alert to the slide in sovereign
credit quality in Europe. Single-name trading had
picked up rapidly, and the next logical step was to create
an index: The Markit iTraxx SovX Western Europe (SovX
WE) was born. An index comprising the 15 most liquid
sovereign CDS contracts, the SovX WE allowed market
participants to macro-hedge positions on European
government debt, as well as take positions on the asset
funds, which use the indexes for both hedging and
speculation. The dealer community is obviously very
active in providing liquidity.
The Markit iTraxx SovX indexes have been used in
a variety of trading strategies since their inception. In
January 2010, news that the SovX WE was trading wider
than its corporate equivalent, the Markit iTraxx Europe,
captured the headlines. There are caveats to the comparison.
Four of the SovX WE’s 15 equally weighted constituents
are “peripheral” eurozone countries: Greece,
Ireland, Portugal and Spain. In contrast, just eight of the
By 2009, investors were alert to the slide in sovereign credit
quality in Europe. Single-name trading had picked up rapidly,
and the next logical step was to create an index.
class as a whole. As was witnessed after the introduction
of the Markit iTraxx Europe Index, as well as sectoral
indexes such as the Markit iTraxx Europe Senior
Financials, liquidity tends to get concentrated in indexrelated
trading and this, in turn, drives bid/ask spreads
tighter. Following its launch in September 2009, SovX
WE is now one of the most widely traded CDS indexes,
typically with a bid/ask spread of about 2 bp. The Markit
iTraxx SovX CEEMEA Index (CEEMEA), representing
sovereigns in the emerging markets of central and eastern
Europe, as well as the Middle East and Africa, followed
in January 2010.
So who uses the Markit iTraxx SovX family of indexes?
Market participants from across the board use the
indexes to manage their risk. The bid/ask spread and
liquidity of an index, when compared with the underlying
CDS contracts, also play a role: Entering or exiting
a position cheaply and quickly is an important concern
for real-money investors. The same applies to hedge
Markit iTraxx Europe’s 125 constituents are based in these
countries. The peripherals have seen a marked deterioration
in their credit profiles over the last few years, and
their spreads have widened sharply as result. The large
weighting of peripherals in the SovX WE has played a large
part in its underperformance.
Nonetheless, a comparison of the two indexes over
the last year shows that the trend has accelerated (see
Figure 5). The SovX WE is now trading about 100 bp
wider than its corporate counterpart, a difference that
can’t be explained by weighting variations alone. Some
market participants will have profited from buying the
SovX WE and selling the Markit iTraxx Europe, i.e.,
shorting sovereign credit risk and going long corporate
risk. The latter index has been relatively stable since
last summer, while the SovX WE has widened significantly.
The increasing differential will have delivered
profits on this strategy.
continued on page 49
18
July / August 2011

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A Fixed-Income Roundtable
Looking at an asset class that isn’t always as it seems
20
July / August 2011

In an effort to get a handle on what’s going on in the fixedincome
area, the Journal of Indexes assembled a broad
panel of experts and presented them with some wideranging
questions.
Ken Volpert, Principal and Head of the
Taxable Bond Group, Vanguard
JOI: Are bond ratings accurate? Or is there a
better way to measure a bond’s risk level?
Volpert: I think for the most part they’re
pretty accurate. It’s a static measure of risk. The ratings
agencies themselves say it’s a static measure of risk with
regard to timely payment of principal and interest. They’re
not predictive in the sense of where ratios might potentially
go, and I think that’s maybe part of the problem.
I do think also in the structured finance area, they have
had poorly designed models that led to some bad results
in some wholesale downgrading of sectors given the crisis
that we had. But I think in the corporate market, the ratings
have been pretty good as a static measure of timely payment
of principal and interest.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
Volpert: I wouldn’t call them a substitute for ratings,
because ratings, as I mentioned, are really a static measure
of the risk of timely payment of principal and interest. But
CDS spreads actually are more forward-looking. They’re
really asking, what are the risks going forward? They could
widen because some company is becoming aggressive or
acquisitive. And so while the current ratings are X, the perspective
risk is Y, because they may lever up and buy some
other company. CDS reflects that forward view.
CDS is giving a little bit of a future look on the potential
trends or path of the ratings, given the information that the
market has available to it.
JOI: Does active management make sense in fixed income,
or some of its subsets?
Volpert: Yes, active management makes sense. At
Vanguard we have active and index funds. We believe
both make sense provided the costs are low. If active
management has a high cost, it doesn’t make sense,
because you have this high hurdle that you need to
overcome—and it’s very difficult to do that in the bond
market without taking excessive risk.
Bond index funds make a lot of sense. I look at our oneto
five-year government credit, five- to 10-year government
credit and 10-plus-year government credit against their
Lipper Groups, and over the last three years, it’s ranged
between outperforming 65 to 77 percent of the competition
over five years, to 74 to 82 percent ratings over 10 years. It’s
very compelling on the index side.
If you can be pretty close to an indexlike expense ratio
and be an active fund and do things that can actually outperform
the index through issue selection or subsector
allocation, that makes a lot of sense.
JOI: Do you believe there are any bubbles in the fixed
income area right now?
Volpert: We don’t really think there are bubbles right now.
Clearly, yields are really low on the short end of the market,
but that’s really driven by a forward view of what the
economic growth is going to be for the future. It seems like
there are a lot of head winds against rapid growth going
forward. You’ve got large budget deficits that need to be
addressed, and that’s likely to result in a slower-growing
economy than what we’ve seen in the past. That probably
also means lower interest rates.
Now, where maybe rates are lower than they should be
on a forward view is if an investor has the view that the Fed is
basically going to inflate its way out of our debt problems. If
we don’t do the difficult thing and cut the deficits, that would
lead to a slower economy, which I would argue would lead
toward lower longer-term interest rates. If instead the Fed
inflates its way out of debt problems, creates more money
and is doing things to devalue the dollar to basically make
our economy grow on a notional basis so it’s growing rapidly
because of inflation—the debt actually becomes less and
less significant in terms of its percentage of the economy.
There is a way of inflating your way out of the debt problem,
but it’s not a good outcome. It certainly wouldn’t be
a good outcome for interest rates. And it would result in a
much slower-growing economy.
JOI: Should bond indexes be weighted by market cap? Is
there a better way?
Volpert: If you add up all the active managers, you’re
basically getting the market, because you’re buying all
the assets that exist in the marketplace. But then you’re
doing that with high costs and turnover commissions and
transactions costs, etc. It’s a considerably lower return than
what you would get if you were able to buy that same market
but with a low expense ratio, and very low turnover.
A primary argument of indexing presupposes marketcap
weighting. If you take away the market-cap weighting,
you’ll lose the predictability of the relative performance.
What you’re doing then is embedding active bets into the
benchmark construction. We don’t think that’s really what
indexing historically was developed to do. We also don’t
think it’s going to yield the results that historically index
investors have experienced.
JOI: Is fixed income still a low-risk asset class?
Volpert: I would say the risk doesn’t really change. In other
words, the durations are what they are. They do change
some as rate levels vary or as issuance patterns change.
For example, right now, the Barclays Aggregate index has a
duration of five years, and over the past 20 years it has averaged
4.6 years with a standard deviation of about 0.3 years ...
so the risk is pretty much well within the historical range.
I would say the yield is less, so you can say, if you’re buying
the same risk, but you’re getting less yield, that maybe is
a little bit riskier in terms of expected return for level of risk. I
think it’s the same risk levels/duration. It’s just that you’re not
getting paid as much for that risk as you have historically.
www.journalofindexes.com July / August 2011 21

JOI: Is the municipal bond market headed for a collapse?
Volpert: The head of our muni group thinks that risk in
the muni market is way overblown. First-quarter state
revenues are up about 9 percent year-over-year. That’s a
huge increase. They dropped a lot for sure in 2009 after the
decline of 2008, but they’ve bounced back now.
And the state and local governments are making tough
decisions. You hear about it every day in the papers: school
districts that are cutting back; services that are being
reduced; taxes that are going up. There are actions being
taken to get the deficits in line.
We think that over this year and next year you’re going
to see large reductions in the deficits at the state and
local level, which is a very good thing. There’s also a lot of
projects and things that a lot of these local governments
have done historically that issued a lot of debt and took on
leverage—they’re not doing those projects. There’s not a
lot of issuance going forward, and not a lot of prospective
increased leverage in the state and local government.
Then, finally, the muni market is still very cheap.
In general, in munis, there are good fundamental trends
compared to where we’ve been in the last year or two.
Jason Hsu, CIO, Research Affiliates LLC
JOI: Are bond ratings accurate? Or is
there a better way to measure a bond’s
risk level?
Hsu: There is a lot of anecdotal and empirical
evidence suggesting that bond ratings tend to be more
reactive than proactive. That is, you see downgrades following
a sequence of negative shocks to either the corporation
or to the country. We have seen this with the ratings for subprime
mortgages. More recently, ratings for the PIIGs countries
were revised down only after they started to experience
problems refinancing their debt.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
Hsu: Often market-based information—information that
one extracts from, say, the credit default swap—may contain
more information than analyst reports. We know this
to be the case for stocks, where prices seem to actually lead
sell-side investment bank recommendations. This may
also be true with regard to extracting rating or creditworthiness
information from a credit default swap, versus getting
that information from bond rating agencies.
I would support the use of CDS as a potentially more
informative and timely source of information.
JOI: Does active management make sense in fixed income,
or in some of its subsets?
Hsu: Absolutely. Fixed-income indexes are very difficult to
replicate and track passively. The way they’re constructed,
they often contain thousands of debt issues. Many of them
are illiquid. Making a passive portfolio, especially one that
tries to fully replicate the indexes, can be costly and unmanageable,
and often you experience high tracking error.
From that perspective, actively managing the fixedincome
exposure rather than passively replicating the full
index could make sense. Certainly we have seen providers in
the marketplace do this, and then many are familiar with the
track record produced by Pimco’s Bill Gross. There is evidence
that may lead us to believe that there are stellar bond
managers who can add alpha against a passive index.
JOI: Do you believe there are any bubbles in the fixedincome
area right now?
Hsu: Many people are talking about the bubble in the
U.S. Treasury market. Whenever a lot of people suggest a
particular asset might be over- or undervalued, it makes
you wonder if that could really be the case, if so many
people think it’s so obvious. There are people who say
U.S. Treasurys are poised to experience a price decline
because rates are at historical lows. With the amount of
liquidity that has been pumped into the marketplace,
the scenario is higher inflation in the future and therefore
higher interest rates.
However, the viewpoint of expecting a price decline has
been in the marketplace for quite a while. To date, we continue
to see fairly low rates on the front end of the yield curve.
What the market information is telling us is that perhaps it’s
not as obvious that Treasurys are in a bubble as one might
expect. Having said that, the long-run prognosis is for higher
rates and higher inflation—but when? Until the Fed is willing
to allow that to happen, we may be in a period of low interest
rates for a number of quarters, if not a few more years.
JOI: Is the municipal bond market headed for a collapse?
Hsu: There’s been a lot of discussion about municipal bonds
being overvalued or just a dangerous place to be. Clearly
they’re providing very high yield. There are stories of taxadvantaged
investors buying muni bonds for the attractive
yields. That’s not to say that they’re not pricing in the significant
likelihood of municipality default, so it’s dangerous to
simply correlate the high likelihood of municipality default
with a municipal bond bubble. They’re offering attractive
yields. Is that yield big enough to compensate investors for
the risk? There’s a camp that would argue there will be some
sort of bailout if municipality default becomes a systemic
risk that may topple the economy. If you believe in that possibility,
then the yield is quite attractive, rather than a bubble
in the municipal bond arena.
JOI: Should bond indexes be weighted by market cap? Is
there a better way?
Hsu: There are so many ways to improve upon traditional
bond indexes. Cap-weighting a bond index, whether it’s
sovereign or corporate, means you will own more of the
issuers that are more in debt. You will buy more of the
sovereign debt from PIIGs than, say, Australia, because
the Aussie government arguably has been more fiscally
responsible and has managed its spending and debt-to-
GDP ratio more than the PIIGs economies. But why would
you want to buy more from those who are less fiscally
responsible, while running a large debt-to-GDP ratio?
22
July / August 2011

Consider whether you are being properly compensated
when you choose to own more of the debt issued by the more
indebted companies and countries. Empirical evidence shows
that the investor is inadequately compensated for the higher
default risk that they take on in their fixed-income portfolio
when they buy issues from distressed economies. Why that is
the case is a puzzle in fixed-income research. But if you use a
cap-weighted fixed-income index, you will own too much of
these distressed companies and countries.
For those two reasons, I think cap-weighting is a horrible
idea: 1) you end up just holding a lower-quality, more distressed
basket of debt, lending too much to companies and
countries that are less likely to pay you back; and 2) for that
increased risk, you’re not even appropriately compensated.
Ric Edelman, CEO,
Edelman Financial Services
JOI: Does active management make sense
in fixed income, or in some of its subsets?
Edelman: No. I don’t believe in actively
managing portfolios. Trying to actively manage a bond
portfolio is as fruitless as actively managing a stock portfolio.
I’ve seen no evidence that anyone has systematically
succeeded, on an after-tax basis, in outperforming market
averages enough to convince me that opportunistic efforts
are worth the risk or the money—or the effort.
JOI: Do you believe there are any bubbles in the fixedincome
area right now?
Edelman: I don’t know if it’s a bubble. We are concerned
that there is excessive risk in two broad areas. First are
long-term bonds because of the threat of rising interest
rates, although the threat is not imminent. The general
consensus is that rates will inevitably rise. And when they
finally do, long-term bonds will suffer a decline in value.
And if rates rise significantly, then the decline in value
could be dramatic. It would not be surprising to see 20 or 30
percent losses due to a rapidly rising rate environment.
The second concern we have is muni bonds. It’s not that
we think there will be massive defaults such as those that
have been suggested by others. But there will be a likelihood
of cut credit ratings—and credit declines have as bad
an impact on bond values as rising rates do.
As the state and local governments find themselves
increasingly challenged fiscally, muni bond investors may
discover a loss of market value. If they hold to maturity,
they will be made whole in the overwhelming majority of
cases, but that could require an investor to wait years, even
decades, for return of capital.
JOI: How should a bond’s price be determined for index
inclusion when markets are often illiquid and everything
is traded off exchange?
Edelman: At first blush, it would seem that the only fair
way is to mark-to-market, so that investors are seeing the
current value at all times. The problem with that concept
is that with thinly traded securities, mark-to-market could
mean marking to the last trade, which may not be a valid
way to evaluate a bond’s current value. It could inadvertently
create volatility that is more extreme than justified.
I’m hesitant to say that mark-to-market is the answer, but
the alternative, which is marking to duration or maturity or
simply basing it on par value, is equally problematic.
I’m not sure that I would want to offer a definitive recommendation.
But investors need to be aware of these issues.
My concern is that too many investors are not aware that this
question is an important one and how it colors the pricing of
their portfolios. It could cause some investors to be lulled into
a false sense of confidence as to the value of their accounts.
Kathy Jones, Vice President and Fixed
Income Strategist, Schwab Center for
Financial Research
JOI: Are bond ratings accurate? Or is there a
better way to measure a bond’s risk level?
Jones: The question I think is really, does the opinion match
up with the outcome? And I think the answer to that is in
most cases, yes. The rating agencies for most bonds do a
pretty good job, though it’s not meant to be, in most cases,
a leading indicator. In other words, a lot of times there will
be a downgrade after someone has already seen the bond
decline in value, or you’ll see the bond go up first, and then
there will be an upgrade by the rating agency.
Is there a better way to measure bonds’ risk level? I
think ratings and opinions need to be tailored to whatever
universe or subset that you’re looking at. Say you’re talking
about taxable corporate bonds: There are a number of different
metrics that would apply to different industries. And
those metrics would be different from the kind of metrics you
might apply to emerging market bonds or sovereign debt.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
Jones: Well, credit default swaps will give you a picture,
a snapshot, of what the market’s assessment is right now.
It’s something to take a look at. And certainly if you have
access to the information, and you see that it’s going
somewhere—up or down—it’s something to pay attention
to. But keep in mind this is an over-the-counter market
between institutional investors, and it may not necessarily
reflect a large number of people making that assessment at
any given point in time. It’s interesting and useful, but like
anything else, you have to be a little careful.
JOI: Does active management make sense in fixed income,
or some of its subsets?
Jones: Yes, I think it does. And I think it’s particularly useful
in credit-sensitive sectors. This would be my personal point
of view. It can be very difficult for an average investor to do
the in-depth credit work that’s needed to assess individual
issuers, whether they’re in the muni world or in the corporate
world. Because an index will sort of track the larger issues—
good, bad or otherwise—with an active manager, you might
be able to really get a bit more in-depth credit analysis done.
www.journalofindexes.com July / August 2011 23

JOI: Do you believe there are any bubbles in the fixedincome
area right now?
Jones: No. I dislike using the word “bubbles” unless I
really feel very strongly, because that’s more than saying
something might be a little bit overvalued or might be due
for a correction. “Bubble,” to me, implies many standard
deviations away from fair value. Often markets that are in
bubbles are heavily leveraged, and I don’t see that in the
fixed-income market right now.
That’s not to say that rates can’t go up and bonds can’t
go down at some point. But I think if you look at where
markets are trading, even Treasurys—which a lot of people
are very nervous about—if you look at it from a term-structure
point of view, as in, what’s the term premium, it’s not
out of whack with some of the underlying drivers such as
core inflation, growth metrics, etc. Again, maybe a little bit
overdone, but I wouldn’t call it a bubble.
JOI: Is the municipal bond market headed for a collapse?
Jones: No—that’s a simple answer to that one. Are there
some muni issues that might default? Sure, there may be
some, but we don’t expect this sort of widespread collapse
that people are talking about.
Mario DeRose, CFA, Fixed Income
Strategist, Edward Jones & Co.
JOI: Are bond ratings accurate? Or is
there a better way to measure a bond’s
risk level?
DeRose: I think ratings do a reasonable job, in most cases, of
measuring credit risk. Obviously, the rating agencies have gotten
a black eye from their missteps in structured finance and
rating mortgage-backed bonds, and subprime backings. They
clearly didn’t do a very good job there. But when you’re looking
at the more plain-vanilla corporate and municipal bonds,
I think the ratings are reasonably accurate, in most cases. I
don’t think you can rely on them, but I don’t think they should
be ignored either. I think for credit risk purposes, they provide
a reasonable idea of what the credit risk of a bond might be.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
DeRose: I don’t think they’re an alternative, but I think
that’s another thing you should consider. I think people
who ignored the credit default swap market back in ’08
learned that they were, in some cases, a better indicator
than what the actual rating was.
JOI: Does active management make sense in fixed income,
or in some of its subsets?
DeRose: I think it can, but you know there are always tradeoffs.
I think it’s going to depend on the individual investor
and what works best for them. You’ve got to make sure that
the goals of the active manager align with the goals of the
investor and so forth. Sometimes I think to the degree that
you can help limit the downside by use of active management,
that’s certainly a positive.
JOI: Do you believe that there are any bubbles in the
fixed-income area?
DeRose: No, I really don’t. Certainly there’s some good values;
there’s some not-so-good values if you look at various
investments. But I’m not seeing any irrational behavior out
there. I think fixed income produces cash flow, so there’s
real inherent value in the investments.
JOI: Is the municipal market headed for a collapse?
DeRose: No; I don’t see the municipal bond market ever collapsing.
There’s been a lot of misunderstanding regarding
bonds and the markets, and that’s kind of led to some outrageous
claims by some regarding defaults that may occur in
the market down the road. Certainly there’s budget challenges
out there due to the severity of the recession, but I
don’t see budget challenges meaning the same as defaults.
You see a lot of municipalities having problems balancing
their budgets, but that doesn’t mean most of them are
going to default. I think interest and principal payments
just make up a small part of a muni budget, and so I don’t
see widespread defaults, at least not on the investmentgrade
muni bonds. You could see an increase of defaults
for lower-quality bonds, but I don’t see anything that’s
going to turn the market upside down.
In fact, we see municipal bonds as the best buying
opportunity in the fixed-income space right now.
JOI: How should a bond’s price be determined for index
inclusion when markets are often illiquid and everything
is traded off exchange?
DeRose: That’s pretty difficult. We went through a pretty
bad period back in 2008, 2009 where there wasn’t a lot of
liquidity in the market at times. And prices were very fluid,
always changing in that type of environment. And, of course,
the markets around the world are sort of like that today.
Clearly, an index is a lot less meaningful in that type of
market. Things just change too much. It’s hard to put a
handle on exactly where you are at any particular time. I
think you need to look at bonds that have actually traded,
more than just valuation bids that may give kind of an artificial
level to the markets. I think you need to look at actual
trades, although that may cause greater volatility in the
index, at least in the short run.
The index has got to be something that’s investable.
If you can’t trade a particular bond, I can’t see that it has
much value in terms of measuring the market.
JOI: Is fixed income still a low-risk asset class?
DeRose: Well, I think it should be, but it seems to be moving
away from that. Fixed income should be the foundation
of most portfolios, where you don’t take a lot of risk; the
risk should be taken in the equity portion, where there’s
just greater upside. But the desire to reach for yields over
time has really pushed the market more and more towards
the riskier fringe part of the asset class. We’re seeing a lot
more attention to the high-yield, emerging-market and
various derivative-type bonds—mortgage-type bonds and
so forth—and those are a lot riskier. The trade-off of that
24
July / August 2011

greater risk sometimes isn’t fully appreciated by a lot of
investors. They’re looking for the higher yield, and don’t
really appreciate sometimes the greater risk and potential
volatility that some of those investments have.
J.R. Rieger, Vice President of Fixed
Income Indices, Standard & Poor’s
JOI: Do you think bond ratings are accurate?
Or is there a better way to measure
a bond’s risk level?
Rieger: I can’t comment on bond ratings themselves.
However, ratings are very important in determining
whether groups of bonds or individual bonds are investment
grade or not. I’m looking at it from a benchmarking
or measuring-the-market perspective. When we’re identifying
bonds as investment grade or not, the criteria to
do that has historically been how the rating services have
rated the individual bonds.
Looking at the bond market from an indexing perspective,
we don’t depend on one rating agency. We look at
multiple rating agencies to determine whether a bond is
investment grade or not, but we still depend on those ratings.
There are ways to look at the bond market that are
not necessarily based on the first dollar of default, as rating
agencies do. And S&P does have various ways to look
at a bond’s risk level, including its risk-to-price product
line. Risk-to-price looks at a bond from the perspective
of its volatility, its duration, its risk characteristics, and
grades the bonds into four categories, with the highest
quartile being bonds where the investors—at the current
yield levels—are getting rewarded or compensated for the
level of risk that they’re taking.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
Rieger: I think that the CDS market provides data to the
marketplace that can be used in conjunction with a lot of
other data, and they help investors make decisions. The
CDS market is a very efficient market when it’s working
well. When it’s not working well, when there are only a few
participants interested in certain credit default swaps and
willing to take one side or the other on that swap, then the
market becomes a little thinner, and the market participants
and investors need to be aware of that. Just because
the spread is 100 bps or 200 bps doesn’t necessarily mean
that there’s a robust market behind that number that
represents the spreads. But it can help in understanding
what’s going on; it can be, in some cases, an early indicator
of whether the market is perceiving more or less risk for
that credit. Not necessarily default risk, but maybe risk in
regards to where yields are going relative to that credit or
to other types of investments.
JOI: Do you believe there are any bubbles in the fixedincome
area right now?
Rieger: In my role as vice president of fixed-income indices
at S&P, I’m not making forecasting statements. But we
can look at the various sectors of the bond market and see
where yields have come way down and prices have risen
sharply as a result. When you look at the U.S. Treasury
bond market and the investment-grade corporate bond
market, and perhaps even the corporate high-yield market,
yields have come way down, or narrowed significantly
in those asset classes. There’s only so much more upside.
If yields began to rise and credit spreads begin to widen,
those bonds are going to see their prices decline precipitously
based on whatever their term structure is.
In other areas of the market—for example, in the
investment-grade municipal asset class—we’ve seen taxexempt
yields equate to taxable equivalent yields that
are substantially cheaper than investment-grade corporates,
or even high-yield corporates. There seems to be
a richness, if you will, to the corporate bond market and
a cheapness to the municipal market. The U.S. Treasury
market will depend on world global events, and in particular,
global events that drive flights to quality. [Currently]
it’s Greece. There’s a lot going on here, so you have the
flight-to-quality events that are keeping yields down in
the U.S. Treasury markets. But in the U.S. corporate market,
we’ve seen yields come way down and prices have
been rising accordingly, so they have only so much more
upside potential mathematically.
JOI: Should bond indexes be weighted by market cap? Is
there a better way?
Rieger: Bond indexes that use a market-weighting schema
have been in place for a long time, and they serve a very
important purpose of reporting about how that asset class, or
a subsector of the asset class that they’re measuring, is doing.
That’s what was issued, and that was the performance.
When we start looking at fixed-income markets in other
ways—such as equally weighted or fundamentally weighted
or GDP-weighted—those indices also serve important
purposes, but are reporting back on a strategy of investing
within those fixed-income asset classes as opposed to
measuring how those fixed-income asset classes actually
perform. S&P does produce indices that are not market
weighted, but the majority of our indices are market
weighted. We have explored looking at alternative weightings
further, and do have some views on how to leverage
different perspectives on weighting schemes. But at the
end of the day, whenever we launch an index like that, it
really is an investment strategy.
JOI: How should a bond’s price be determined for index
inclusion when markets are often illiquid and everything
is traded off exchange?
Rieger: If we put the liquid Treasury market aside, the
fixed-income markets are OTC, and I’m referring to the
U.S. markets in particular. At one point we had over 3 million
bonds outstanding in U.S. markets alone, and very
few—percentagewise—were actually trading on any given
day, and very few had two-sided markets.
The pricing question is a very valid one. Indices need to
be very selective as to how they’re pricing the constituents,
www.journalofindexes.com July / August 2011 25

and the pricing process has to be very transparent. S&P takes
the perspective that transparency is critical for the index.
The fixed-income indices typically have large numbers
of bonds in them, so benchmark indices used for
performance measurement and performance attribution
leverage those bonds in an index to help them understand
whether they are weighted properly by sector and structural
characteristics—short duration, long duration—and quality
characteristics. We do have a lot of bonds in the index
for that purpose. The pricing we use depends on the asset
class and the purpose of the index. For a broad benchmark
index, we have used end-of-day bond pricing services. But
for more investable indices, we have actually used trading
desk prices for some asset classes because it’s a better fit
for the purpose that the investor is looking to use the index
for. However, most of our indices are priced through an
end-of-day bond pricing service, and that seems to suit the
needs of the clients who use the index.
Waqas Samad, Managing Director and
Head of Index, Portfolio & Risk
Solutions, Barclays Capital
JOI: Does active management make sense
in fixed income, or in some of its subsets?
Samad: I think it depends on what you define by “making
sense.” Clearly there is a broad set of active managers,
and there are supposedly as many active managers
as passive managers in the fixed-income space. They’re
certainly trying to achieve outperformance … and usually
in the fixed-income space that boils down to taking
views on interest rate risk, credit and sovereign risk, and
FX risk, for global portfolios.
Sometimes that’s going to work in favor of an asset manager
just like it would in the equity space, and sometimes it’s
not going to work. From a stats point of view, taking a look
at some historical periods, the evidence of course points to
periods when it works and periods when it doesn’t.
To give you an example, in 2008, approximately 65 percent
of the fixed-income active managers that are out there
underperformed the Barclays Capital Aggregate index. But
then in 2009 and 2010, you had a situation where a lot of
managers were able to outperform the index. To a degree,
it depends on what’s going on in the market.
JOI: Should bond indexes be weighted by market cap, or
is there a better way?
Samad: Even though we recognize that no single index
design or index methodology is universally applicable to
all shapes and sizes of manager or asset owner or portfolio,
the fact is that in the fixed-income space, and obviously in
the equity space as well, right now the standard is marketcap
weighting. And it’s very difficult to see the market moving
wholesale very rapidly away from such a standard—in
this kind of environment especially.
Thinking back to the question about active management,
even when managers are taking active bets, they
have to keep an eye on the risk/return profile. They have
to make their bets wisely. As a result, if you’re thinking
about alternative weighting schemes for index benchmarks,
you’re very often making an active management
choice right there.
We’ve done a lot of work in alternative weighting schemes,
and whenever you’re doing all of that, you must bear in
mind that the indices have got to be rules based and transparent
and so on—everything that you would expect from a
good quality benchmark index. But also, crucially, they have
to be tradable. By that I mean they have to be useful to the
end-user to the extent that they’re trying to build or replicate
a portfolio around those rules. If the choice of methodology
results in a strategy that just isn’t implementable in the market—because,
for example, illiquid parts of the debt universe
are weighted much more highly than the liquid parts—then
those indexes are not going to be useful.
JOI: How should a bond’s price be determined for index
inclusion when markets are often illiquid and everything
is traded off exchange?
Samad: Clearly there’s an option to aggregate prices from a
number of different sources, and then come up with some
sort of an average price using an algorithmic approach
or a methodology. Another way is to take the prices that
one has gathered, and then apply a purely mathematical
method of imputing the price of other securities that might
bear some relation to the ones that you can get prices on—
the matrix pricing approach.
And the third way is to take pricing from a single market
participant and use those prices in constructing an index
of bonds. When it comes to illiquid markets, it’s clear to us
that the third example, where you take the price information
from a source that is very close to the markets, has the best
chance of being able to get a price that is viewed as indicative
of where the market is trading on a particular bond.
When you use the averaging-of-multiple-prices
approach, that may lead to some sort of distortion of the
true price by coming up with an average across a wide dispersion
of the component prices available to you.
We feel, especially when it comes to illiquid securities,
that the best way to deal with the pricing of the bonds is to
get the best information that you can from traders that are
active in the market, and to have a very strong quality control
process and price evaluation routines that thoroughly
validate pricing inputs.
JOI: Is fixed income still a low-risk asset class?
Samad: I think the perception from the investor base is
that on a relative basis compared to equity and other asset
classes, it has been a low-risk asset class.
Obviously when you look at other areas of fixed income—
such as emerging markets and high yield—that’s where
investors are looking to take a little more risk in order to
get to higher yield and an increased return. But I think
when we do a comparative analysis versus equity and other
asset classes like commodities, we come to the conclusion
that fixed income in general could be broadly described as
being a relatively low-risk asset class.
26
July / August 2011

Larry Swedroe, Director of Research,
Buckingham Asset Management
JOI: Are bond ratings accurate? Or is there a
better way to measure a bond’s risk level?
Swedroe: I think it’s important to distinguish
between the types of bonds we’re talking about.
Moody’s and S&P have very good, long track records
in the municipal bond market, and I think you can rely
on them pretty well in those markets. And there you
don’t have the kind of conflicts of interest that you have
in other markets, like the ABS market. In other words,
municipalities don’t go out and issue more debt because
they get a good rating. They need money to build a hospital
or a road. The ABS market was allowed to grow
because they got good ratings, so there was a conflict.
The ratings agencies knew if they gave a good rating
they’d get more business, and you’ve got this vicious
circle, causing them—in my opinion—to sell their souls
to the devil, if you will. You don’t have those conflicts in
the muni market, and even in the corporate bond market
you don’t have it so much.
The second thing—and maybe this is the more important
one—we have never relied solely on a credit rating.
We have parameters, for example, in the municipal bond
market, where we’re a fairly big presence; we’re a manager
for our clients of over $14 billion in assets. We’re
buying on the order of $3 billion or $4 billion a year in
fixed-income securities. On the municipal bond side, we
have always restricted our holdings to AAA, AA and even
A if it’s three years or less. If we’re going more than three
years, we would want AA or AAA.
We trust the market more than we trust Moody’s or
S&P. If something is rated AA but is trading like a BBB, a
lot of people will buy it because they think they’re getting
a bargain. We say, no; you’re really owning a BBB, and
Moody’s and S&P are just late recognizing the risk. The
market has just reacted much faster. We will only buy
things that trade like their rating.
On top of that, even if something is AA or AAA, but is
not the type of bond we buy, we won’t buy it. We won’t buy
a AAA municipal bond if it is one of the sectors that have
poor credit history.
We also stay away from corporate bonds and we certainly
don’t buy any individual corporate bonds—we think
the credit risks are not worth it. You should take that kind
of risk on the equity side of your portfolio, where you can
diversify the risks more effectively and you earn the risk
premium in a more tax-efficient way.
JOI: Are credit default swaps a good alternative or substitute
for ratings?
Swedroe: I think that may be of value, but I don’t think
you really need them because all you have to do is look at
where a bond is trading in the market and that will tell you
where the market thinks that bond should be rated. We’ve
been doing this for 15 years; we did it before there were
CDS and we didn’t need them to do it.
JOI: Does active management make sense with fixed
income, or some of its subsets?
Swedroe: The evidence is very clear that while it’s possible to
beat the market with active management on the equity side,
the odds are so low, you shouldn’t even try.
The odds are much worse on the bond side. It’s simple
logic: If you stick with high investment grade, most of the risk
is systematic risk of interest rates and guessing them right.
There are very few default losses with AAA or AA bonds. We
know the evidence on guessing interest rates is terrible, so
that’s a problem. The second problem is even when there is
credit risk, like with AA or A bonds, what are the odds that
the stock of two companies will perform dramatically differently?
Quite likely. If they’re both AAA-rated bonds, what are
the odds the bonds are going to perform differently? They
are much lower. That’s why there’s much more opportunity
to add value on the equity side than on the bond side.
JOI: Do you believe there are any bubbles in the fixedincome
area right now?
Swedroe: Bubbles certainly can happen, but they tend to
happen in asset classes that have lotterylike payoffs—like
small-caps stock or IPOs or emerging markets. Anything
that promises this super-great return. When things get to
be “safe,” everyone starts to pile in, and they forget that risk
shows up—it’s only a question of when, not if. Spreads often
get to too-thin levels and people start taking too much risk.
I think you should try to minimize—and even eliminate—credit
risk, because you don’t need to take it. I
believe the main purpose of the fixed-income portion of
the portfolio is to dampen the overall portfolio risk to an
acceptable level, so I don’t want to take credit risk because
it tends to show up at exactly the same time as equity risk.
When my equities are getting killed, I want the bonds to be
my safety net. And that doesn’t happen if I’m taking credit
risk in emerging market bonds or junk bonds or convertibles.
If you want risk, take it on the equity side.
JOI: Are municipal bonds headed for a collapse?
Swedroe: I think Meredith Whitney’s forecast will go
down as the second-worst ever, after the BusinessWeek
“The Death of Equities” article [Aug. 13, 1979]. What
people forget is that municipalities by law, unlike the federal
government, cannot run budget deficits in all but one
state. As a result, they must act, and they do act. They cut
spending; they raise revenues. In 2009 and 2010, roughly
$100 billion was cut each year to close the gap, and in
2011 and 2012 it’s going to be much more than that.
Now I think the political environment is empowering the
politicians to stand up to the unions and negotiate better
transactions. Bankruptcy isn’t even legal in 26 states, so
they can’t declare it, and they need access to the public
markets, so those that can declare it will do everything
they can to avoid it. Even in the Great Depression, there
were virtually no losses; while there were defaults of 6 or
7 percent, ultimately they got paid back. When New York
City defaulted in the 1970s, every penny got paid back.
The same happened with Orange County in the 1990s.
www.journalofindexes.com July / August 2011 27

The Impact Of Fund Flows
On Fixed-Income Mutual Fund
Performance
What every bond investor should know
By David Blanchett
28
July / August 2011

Recent market returns and events have led to
record inflows into fixed-income mutual funds,
which received $246 billion in net inflows in the
year 2010, according to the Investment Company Institute,
versus outflows of $29 billion for equity mutual funds.
Certain mutual fund families, such as Pimco, and in particular
the Pimco Total Return Fund, received a seemingly
disproportionate amount of these flows. While past
research has explored the impact of fund flows on equity
mutual funds, little research has been devoted to exploring
the impact of fund flows on the subsequent performance of
actively managed fixed-income mutual funds.
This paper explores the impact of new monies,
defined as net mutual fund flows, on the future performance
of actively managed mutual funds classified as
Intermediate-Term Bond by Morningstar from 1996 to
2009. The cost of putting new monies to work, though—
or the “cost” of fund flows—was estimated to be approximately
40 bps in this analysis. Additionally, this research
notes that more expensive bond managers do not appear
to be “worth” their fees (i.e., there is no relationship
even on a gross return basis with regard to the relative
performance of bond managers), while the mutual fund
expense ratio was a key driver of relative performance.
Taken together, this research suggests a bond investor
is best served by buying a low-cost investment option,
such as a passive portfolio, or a fund that is expected to
receive few relative inflows versus its peers.
Bond Fund Assets
The last few years have been good for bond funds from a
net flow perspective. As of February 2010, 21 percent of all
mutual fund assets were invested in bond funds, according
to the ICI. Bond mutual funds received $246 billion in net
inflows in the year 2010, versus outflows of $29 billion for
equity mutual funds. Figures 1 and 2 have been included
to give the reader an indication as to the growth of bond
fund assets through time and the relative significance of
the recent monies flowing to bond funds, which have been
significant both from a total dollar perspective and a percentage
of assets perspective.
According to the ICI 2010 Fact Book, since 2004, inflows
to bond funds have been stronger than what would have
been expected based on the historical relationship between
bond returns and demand for bond funds. A few secular
and demographic factors may have contributed to this
development: the aging of the U.S. population, growing
aversion to investment risk by investors of all ages, and the
increasing use of “funds of funds.” First, the leading edge
of the baby boomer generation has just started to retire,
and because investors’ willingness to take investment risk
tends to decline as they age, it is natural for them to allocate
their investments increasingly toward fixed-income
securities. Second, the aggregate decline in risk tolerance
likely boosted flows into bond funds in 2009. Lastly, funds
of funds remained a popular choice with investors, and a
portion of the flows into these funds was directed to underlying
bond funds.
Follow The Money
According to Morningstar, inclusive of all share classes,
the Pimco Total Return Fund had more than $240 billion in
assets as of Dec. 31, 2010. This represents 29 percent of all
the assets invested in the Morningstar Intermediate-Term
Bond category. In contrast, the next-largest mutual fund,
an equity fund, The Growth Fund of America, has $154
billion across all share classes, representing 19 percent of
the total assets invested in the Morningstar Large Growth
category, as of Dec. 31, 2010. How is it that the Pimco Total
Return Fund has staked such a large portion of investor
dollars in the Intermediate-Term Bond category and fixedincome
assets in general? While there are potentially many
reasons, the most important is likely performance, or really
outperformance. Pimco’s bond funds, especially those
managed by Bill Gross, have performed very well historically,
both relative to their respective peers and in absolute
terms, given the relatively poor recent equity returns.
Sirri and Tufano [1998] were among the first to note that
consumers base their mutual fund purchase decisions on
Figure 1
Billions
Monthly Total Assets And Rolling 12-Month Net Flows
In The Morningstar Intermediate-Term Bond Category
December 1995 to September 2010
$900
$800
$700
$600
$500
$400
$300
$200
$100
$0
-$100
Dec
1995
Source: Morningstar
Figure 2
25%
20%
15%
10%
5%
0%
-5%
-10%
Dec
1995
Dec
1997
Dec
1997
Dec
1999
Dec
2001
Dec
2003
Period Ending
Dec
2005
N Total Assets N Rolling 12-Month Net Flow
Dec
1999
Dec
2001
Dec
2003
Dec
2005
Dec
2007
Dec
2007
Dec
2009
Monthly Rolling 12-Month Net Flows As A Percentage Of Total
Assets In The Morningstar Intermediate-Term Bond Category
December 1995 to September 2010
Total Assets
Source: Morningstar
Period Ending
Dec
2009
www.journalofindexes.com July / August 2011
29

Figure 3
Average Annual Net Fund Flows (M)
Average Annual Net Fund Flows (M)
Average Annual Net Fund Flows For Intermediate-Term
Bond Funds By Previous One-Year Performance Decile
$400
$350
$300
$250
$200
$150
$100
$50
$0
-$0
-$100
Source: Morningstar
Figure 4
Average Annual Net Fund Flows For Intermediate-Term
Bond Funds By Expense Ratio Decile
$600
$500
$400
$300
$200
$100
$0
-$100
Source: Morningstar
1 2 3 4 5 6 7 8 9 10
High
Low
Intermediate-Term Bond Category
Previous One-Year Performance Decile Rank
Average Future One Year Outperformance Vs. Category
Average By Previous One-Year Performance Decile Rank
Future 1-Year Outperformance
Vs. Category Average
.30%
.20%
.10%
0%
-.10%
-.20%
-.30%
-.40%
-.50%
-.60%
-.70%
1 2 3 4 5 6 7 8 9 10
Past 1-Year Performance Decile
High
Low
N Net Performance N Gross
Source: Morningstar
Figure 5
1 2 3 4 5 6 7 8 9 10
Low
Intermediate-Term Bond Category Previous
One-Year Performance Decile Rank
High
prior performance information. They note investors tend
to purchase funds on an asymmetric basis, by investing
money disproportionately into funds that have recent
superior performance, while investing less in funds with
poor recent performance. Additional research by Chevalier
and Ellison [1997], Ippolito [1992] and Gruber [1996] confirmed
this effect. Figure 3 includes information about historical
performance and flows for bond mutual funds from
1996 to 2009, where the average annual net fund flows for
intermediate-term bond funds are compared against the
previous one-year performance decile rank.
Figure 3 demonstrates the strong historical relationship
between past performance and fund flows for bond funds.
Those funds with the highest recent performance tend to
receive the lion’s share of new monies going into the category.
Allocating money to recent outperformers can either be a
“smart” or “dumb” decision depending on whether or not the
performance is persistent. Performance persistence is also
known as momentum, which is an effect that has been documented
by Jegadeesh and Titman [1993], among others.
Research by Gruber [1996] and Zheng [1999] suggested
that individual investors can detect that skill and send their
money to skilled managers. They show that the short-term
performance of funds that experience inflows is significantly
better than those that experience outflows, suggesting
that mutual fund investors have selection ability. These
findings were contradicted by Frazzini and Lamont [2008],
who found that fund flows are actually “dumb money,”
whereby in reallocating across different mutual funds,
retail investors reduce their wealth in the long run. What
about bond funds? Figure 4 includes information about the
future performance of intermediate-term bond funds as
sorted into deciles based on previous-year performance.
If bond funds that performed well continued to perform
well against their peers, allocating the majority of new monies
would be considered a “smart” decision; however, based on
the results in Figure 4, there appears to be little momentum
effect for bond funds. The only performance that appears to
be notable is that funds that performed poorly the previous
year tended to repeat as incredibly poor performers the following
year, both on a net return and gross return basis.
Expense ratios are especially important for bond funds—
at least more so than for equity funds—given the lower
historical performance of bonds vs. equities. In other words,
an expense ratio represents a return reduction of 20 percent
if bonds return 5 percent, versus a 10 percent reduction for
equities if equities return 10 percent. Not surprising, while
there was clearly a relationship between past performance
and fund flows (Figure 3) there is also a relationship between
expense ratios and fund flows, whereby funds that have
lower expense ratios tend to receive more inflows than funds
with higher expense ratios. Actively managed intermediateterm
bond funds in the cheapest two deciles received the
most net inflows from 1996 to 2008 in all but one year.
Analysis
There is clearly a link between past returns and future
flows for fixed-income funds, as exhibited in Figure 3. There
is also a relationship between expense ratios and future flows
for fixed-income funds, as exhibited in Figure 5. What is less
clear is the joint impact of these on performance. In order to
determine this, an analysis was conducted that jointly considered
the impact of expense ratios and fund flows on the
30
July / August 2011

Figure 6
Gross And Net Intermediate-Term Bond Performance By Flow And Expense Ratio Quartile Groups
Source: Morningstar; author’s calculations.
Low
Low
Low
1
1
1
Past One-Year Flow Quartile
2
Past One-Year Flow Quartile
2
Past One-Year Flow Quartile
2
3
3
3
4
4
4
High
High
High
Avg
Avg
Avg
1 Minus 4
Low 1 0.08% 0.11% 0.16% -0.07% 0.07% 0.16%
Exp. Ratio Quartile
2 -0.14 0.08% -0.39% -0.31% -0.19% 0.17%
3 0.31% 0.06% 0.19% -0.39% 0.04% 0.70%
4 0.39% 0.24% -0.01% -0.25% 0.09% 0.64%
High Avg 0.16% 0.12% -0.01% -0.26%
1 Minus 4
Low 1 0.44% 0.49% 0.49% 0.29% 0.43% 0.16%
Exp. Ratio Quartile
2 -0.04% 0.15% -0.28% -0.18% -0.09% 0.14%
3 0.23% -0.04% 0.11% -0.46% -0.04% 0.68%
4 0.06% -0.17% -0.45% -0.55% -0.28% 0.61%
High Avg 0.17% 0.11% -0.03% -0.22%
Low 1 13.31 10.62 14.38 23.85 15.54
Exp. Ratio Quartile
Future One-Year Gross Performance
Future One-Year Net Performance
Average Number Of Test Funds Per Period
2 15.85 11.85 15.23 21.92 16.21
3 17.69 18.38 17.00 11.38 16.12
4 15.85 19.69 15.23 11.54 15.58
High Avg 15.67 15.13 15.46 17.17
Expense ratios are especially important for bond funds—
at least more so than for equity funds—given the lower
historical performance of bonds vs. equities.
future performance of fixed-income mutual funds.
All data used for the analysis was obtained from
Morningstar, primarily Morningstar Direct. Only actively
managed mutual funds categorized as Intermediate-Term
Bond funds are are included in the analysis. All funds flagged
as an Index fund or an Enhanced Index fund by Morningstar
were removed. Funds with multiple share classes are limited
to the share class with the fund with the oldest inception
date. For those mutual funds with multiple share classes and
the same inception date, the fund with the lowest expense
ratio is selected to represent that fund.
For the analysis, 14 independent consecutive calendaryear-end
periods are reviewed from 1996 to 2009. The years
1996 to 2008 include both classification periods and test
periods, while in 2009, only the returns are used (as the
future returns for the 2008 calendar-year ranking period).
1996 was selected as the starting point for the analysis
because it is the year Morningstar categories were introduced.
Net returns (annual return reduced by the expense
ratio) as well as gross returns (annual return excluding
expense ratios) are included in the analysis.
In an attempt to minimize the impact of survivorship
bias and to better capture the fund’s attributes over time,
independent rolling data periods were used (versus a
single look-back period, e.g., Dec. 31, 2009). Using independent
data periods minimizes the potential impact of
survivorship bias, since many funds (especially those with
poor performance) have likely gone out of business since
the beginning of the test period. While the possibility of
survivorship bias still exists intra-year—since a fund had to
have an annual return to be included for that test year—the
continued on page 58
www.journalofindexes.com July / August 2011
31

Talking Indexes
Bubble Bubble,
Toil And Trouble
Fire burn, and cauldron bubble 1
By David Blitzer
We believe bubbles in markets or the economy are
aberrations—as if they are “black swans” that
descend upon us out of nowhere. That’s not the
way the world is. Bubbles are common and very much a part
of the normal behavior of markets. A market where the price
of almost any stock equaled the discounted present value
of expected future dividends and never moved more than
what could be justified by changes in expected dividends or
the discount rate would be strange. Investors look for stocks,
bonds, commodities or other investments where profits can
be made as prices move, not where prices are locked to values.
Bubbles can lead to outsize returns, or losses.
The prevalence of bubbles and the absence of prices
tied to dividends, earnings and discount rates make investing
with indexes attractive. Besides being lower cost, index
investing is attractive because bubbles are hard to recognize
and even harder to predict, so picking the right stocks
is difficult. Further, given how fickle a bubble can be,
investors seek the protection offered by the diversification
inherent in broad market indexes.
History confirms that bubbles are with us more often
than not. The housing bubble dominated the decade just
ended, and its fallout is all too well known. Before housing,
we had the technology and telecom bubble in the 1990s,
when everyone thought the Internet would create profits
out of thin air. Roll back another decade to the 1980s when
markets surged as interest rates and inflation tumbled,
producing a double bubble of bonds and stocks. The 1970s
saw both inflation and a love for anything that looked like
an inflation hedge: gold, real estate and REITs. Corrected
for inflation, the all-time high price of gold was set long
ago in the 1970s bubble. The 1960s, dubbed the “go-go”
years, saw conglomerates and the Nifty Fifty. We could
continue to walk back through history, finally reaching the
beginning of financial markets that would be recognizable
to today’s investors in 15th-century Holland. The bubble
then, in 1637, was in tulip bulbs.
Before leaving history aside, one should note the dark
side of bubbles: They usually end with market declines
and weak economies. The Great Recession of 2007-2009
is the most recent example. After the 1990s tech boom,
the market dropped about 50 percent; the 1980s bull
market dropped 20 percent from late August to mid-
October in 1987, and then crashed another 20 percent in
one day on Oct. 19, 1987. The 1960s go-go years ended
with the deep recession in 1973-1975; the 1970s inflation
was squeezed out of the economy in two back-to-back
recessions in 1980 and 1981-1982. Bubbles offer investment
opportunities for some, but risks for all.
If bubbles are common and prices don’t constantly align
with the theoretical values based on discount rates and
expected future returns, what good are the theories of price
and value? Although the theories rarely foretell tomorrow’s
or next month’s price, they can be a guide to how far the
price may be from a reasonable level. As prices—driven by
emotions and excitement—rise farther and farther above
sensible levels suggested by future returns and discount
rates, many find explanations why prices should climb even
higher and why the pitfalls of the past might have really been
passed. Occasionally, the theoretical values reassert themselves
quickly, and more often than not, we get a bubble.
The response should not be to throw out the theory.
Rather, the relation between price and value should be seen
as an indicator of how big the bubble is and maybe how close
it is to bursting. Looked at this way, we can recognize that
bubbles are common events, not rare exceptions, and that
32
July / August 2011

theoretical measures of value can help us understand how
irrational a market might be. Those who compared house
prices to either rents or income levels in the recent years saw
that houses were far too expensive compared to the costs of
renting. Comparisons to income showed that prices eventually
reached levels where few could afford to buy.
Those who compared house prices to either rents or
income levels in the recent years saw that houses were far too
expensive compared to the costs of renting.
Those comparisons to income and rents provided indicators
of bubbles and values for the housing market. For
stocks, indexes provide useful measures. In the technology-telecom
boom of the 1990s, stocks associated with the
Internet saw prices grow to the sky. When values in those
stocks were measured by ratios such as price-to-earnings
or price-to-sales, they were far out of line from the same
measures applied to broad market indexes. Moreover, the
indexes themselves were twisted away from their usual
shape as the bubble sectors swelled to much larger proportions
of the indexes, or the market, than was the norm.
These were signs that the telecom and tech stocks were
bubbling up. The same indicators showed that the indexes
were working—they were reflecting the market’s conditions
at the time, even while their history was pointing to
the momentary triumph of excitement and irrationality
over future returns and values.
The theory of how value and price align is correct in
equilibrium. However, emotions and excitement often drive
markets far from equilibrium. In the heat of the moment,
it is too easy to make excuses for the theories of value and
believe only in prices. The result is another bubble.
Endnote
1 Apologies to William Shakespeare and the witches of Macbeth
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www.journalofindexes.com July / August 2011
33

The Importance Of Dividends
And Buybacks 1
Ratios
For Gauging Equity Values
Don’t rule out the significance of either one
By Jeremy Schwartz
34
July / August 2011

Analysts who are the most bearish on the U.S. equity
markets point to expensive valuation ratios on the
S&P 500, notably the dividend yield, 2 which is considerably
below its long-term average. John P. Hussman,
Ph.D., president and principal shareholder of Hussman
Econometrics Advisors, the investment advisory firm that
manages the Hussman Funds, is well known for being in
this bearish camp. Summarizing his case for the U.S. equity
market, Hussman wrote last year:
“Over the past 13 years, the total return for the S&P
500 [Index] has averaged just 3.23%. Why have stocks
performed so poorly? One word. Valuation. . . . It is not
a theory, but simple algebra, that the total return on the
S&P 500 [Index] over any period of time can be accurately
written in terms of its original [dividend] yield, its terminal
[dividend] yield, and the growth rate of dividends.” 3
Hussman then points out that the current dividend yield
on the S&P 500 Index is just around 2 percent, when the
average across time was considerably higher. Similarly,
Robert Shiller’s research on the equity markets shows that
from 1871-1982, the average dividend yield for the S&P 500
Index was above 5 percent. 4 Given that current dividend
yields on the S&P 500 Index are well below that historical
average, at face value, the bearish arguments may unwittingly
scare investors out of the equity markets.
While the idea of the market being driven by yield is
compelling in its simplicity, I believe Hussman’s analysis
fails to account for a critical market dynamic: share buybacks.
Firms generally have three strategic ways they can
utilize excess cash: Firms can either pay dividends; engage
in share buybacks; or use the cash for other investments,
such as acquiring other companies or expanding operations.
An increasing number of companies, perhaps driven
by a belief that modern equity investors have more appetite
for capital appreciation than income, have opted to
supplement their traditional dividend payments with share
buybacks. In a share buyback, a company invests in itself
by using cash to repurchase its shares from investors; this
share buyback results in the company reducing its float,
thus causing share prices to rise, all else being equal. When
one accounts for the combined cash that is being returned
to shareholders both from share buybacks and dividends,
the market’s valuation levels look more enticing.
Dividends Or Buybacks: What’s The Difference?
Firms have engaged in increased share buyback activity
over recent years. While theoretically buybacks function in
very similar ways as dividends as a method of returning cash
to shareholders, there are some key differences between
dividends and buybacks. The key differences include:
1) Distribution of Cash
r%JWJEFOET All shareholders of a firm receive dividends
when they are distributed.
r#VZCBDLTA select group of investors sells shares back
to the company either in the open market or during a period
in which investors receive the option to sell all or a portion of
their shares back to the company within a certain time frame
known as a “tender offer” period. Only those who elect to
sell their shares back to the company during the buyback
program receive cash, and there is risk that if investors defer
selling to the future that stock prices will move lower.
2) Timing of Benefit
r %JWJEFOET The benefit, or the cash received, from
dividends occurs at the time the dividends are paid, and
therefore reflect a historical measure.
r#VZCBDLTThe benefit from share buybacks—a reduction
in shares outstanding—is a benefit that applies to
future distributions. Even though only a portion of shareholders
sell their shares back to the company, the reduction
in shares benefits all the remaining shareholders; the
total future cash distributions by the firm are divided in the
future among a smaller shareholder base. The concomitant
rise in share price associated with the reduction in float
benefits all investors on paper at the time of the buyback,
and at the time of some future sale in cash terms.
3) Transparency
r %JWJEFOET Once firms state their intention to pay a
regular dividend, the vast majority in the United States
follow through with that commitment unless there is an
extraordinary downturn in business prospects.
r#VZCBDLT Firms announce plans to buy back stock
that often are not carried through to execution.
In pure finance theory, when it comes to weighing the
pros and cons of the features of dividends and buybacks
outlined above, share repurchases are often a preferred
method for returning cash to shareholders. Investors like
share buybacks because they support higher stock prices 5
and one can choose the timing of share sales (and tax
consequences) at a point in the future; dividends, by contrast,
are taxed at time of distributions and the investor
has no choice for when she receives the dividends.
In practice, however, firms do not consistently implement
a share buyback program at the regular quarterly frequencies
that firms pay cash dividends. On balance, whether
firms use their cash for share buybacks or dividends, at
worst, finance theory leads me to believe investors should
be indifferent, and at best prefer that firms undertake share
buybacks. The key point to realize is that firms are distributing
cash to shareholders both by dividends and share buybacks,
and one must account for both ways when gauging
the historical relative valuation levels of the market.
Historical S&P 500 Buyback Data
Howard Silverblatt of Standard & Poor’s publishes historical
dividends and buyback data on the S&P 500 Index only
as far back as the last decade. As of Dec. 31, 1999, buybacks
had surpassed dividends, but each was only slightly more
than 1 percent, so the combined dividend and buyback ratio
was just above 2 percent (see Figure 1). The collapse of the
financial sector caused dividends to decline 20 percent from
www.journalofindexes.com July / August 2011 35

Figure 1
S&P 500 — Trailing 12 Month Data
S&P 500
Index Price
Dividends
($B)
Buybacks
($B)
Dividend
Yield
Buyback
Ratio
Dividend
& Buyback Ratio
12/31/2010 1257.64 $205.83 $298.82 1.80% 2.61% 4.42%
12/31/2009 1115.10 $195.61 $137.64 1.97% 1.39% 3.36%
12/31/2008 903.25 $247.29 $339.65 3.15% 4.33% 7.48%
12/31/2007 1468.36 $246.58 $589.11 1.92% 4.58% 6.49%
12/31/2006 1418.30 $224.76 $431.83 1.77% 3.39% 5.16%
12/31/2005 1248.29 $201.84 $349.23 1.79% 3.10% 4.90%
12/31/2004 1211.92 $181.02 $197.47 1.60% 1.75% 3.35%
12/31/2003 1111.92 $160.65 $131.05 1.56% 1.27% 2.84%
12/31/2002 879.82 $147.81 $127.25 1.82% 1.57% 3.39%
12/31/2001 1148.08 $142.22 $132.21 1.36% 1.26% 2.62%
12/31/2000 1320.28 $141.08 $150.58 1.20% 1.29% 2.49%
12/31/1999 1469.25 $137.53 $141.47 1.12% 1.15% 2.27%
Source: Standard & Poor’s. Data as of Dec. 31, 2010.
The buyback ratio is a market valuation measure used to gauge what percentage of index market value is being reduced by share buyback activity of firms. The dividend and
buyback ratio aggregates the dividends and buybacks together to represent a market valuation metric based on two common ways (dividends and buybacks) that firms distribute
cash to shareholders.
2008 to 2010. Still, dividends increased cumulatively 45 percent
over the last decade. Buybacks were more volatile than
dividends over the decade but also increased significantly,
and as of Dec. 31, 2010, the S&P 500 Index level was still well
below its December 31, 1999, level of 1469.
Because the prices were down, and dividends and buybacks
were each up significantly, the dividend and buyback
ratios on the S&P 500 Index approximately doubled from
Dec. 31, 1999 to Dec. 31, 2010. Note as of Dec. 31, 2008, the
combined dividend and buyback ratio was over 7 percent,
and at the bottom of the market in March 2009—when the
S&P 500 Index touched 666—the dividend and buyback
ratio was over 10 percent of the index price.
Why is analysis of dividend and buyback
ratios rare in the industry?
If the dividend and buyback data is so important for monitoring
the valuation levels of the market, one might ask why it
is not a more common practice among index data providers.
The fact is that data on index-level share buyback activity is
currently not widely available (aside from the above insightful
analysis provided by Standard & Poor’s on the S&P 500 Index).
To combat this dearth of data availability, WisdomTree began
collecting data as of the trailing 12 months for the 2010 year-end
on share buyback activity across its global index family, starting
to help give context for how dividend and buyback ratios range
in various parts of the world as well as in U.S. markets.
Aggregate US Share Buybacks Are Now Higher
Than Aggregate US Dividends
To further explore the role of buybacks in the equity
markets, we examined our in-house index series, and found
that in the United States, share buybacks have surpassed
dividends in terms of aggregate distributions to shareholders
(see Figure 2). WisdomTree has two U.S. equity families.
One family, the WisdomTree Earnings Indexes, is generally
based on the profitable companies in the United States; the
other, the WisdomTree Dividend Indexes, is generally based
on the dividend payers in the United States.
Analysis of the buyback levels on these indexes reveal some
key insights about what types of companies are issuing buybacks.
This analysis is solely meant to be used as a commentary
on how firms are distributing their cash to shareholders and
the resulting implications for the overall valuation levels of
WisdomTree’s indexes and the markets covered by them.
r%JWJEFOE4USFBN The total aggregate dollar value of
dividends paid for the WisdomTree Dividend Index as of
Dec. 31, 2010 was $247 billion.
r #VZCBDLT The total aggregate share buybacks over
the prior 12 months for the WisdomTree Earnings Index as
of Dec. 31, 2010 was $306 billion, about 24 percent higher
than its trailing 12-month dividend stream.
r The buybacks for the WisdomTree Dividend Index
were $240 billion, about $66 billion below those of the
WisdomTree Earnings Index. The higher level of buybacks
for the Earnings Index is largely a result of technology
companies preferring buybacks over dividends and the fact
that technology stocks comprise the largest weight in the
WisdomTree Earnings Index but are less represented in the
WisdomTree Dividend Index. Technology sector companies
comprised $80 billion of the $300 billion in buybacks from
the Earnings Index total, or approximately 26 percent.
Because share buybacks function largely in the same theoretical
way of returning firm cash to shareholders as paying
dividends, an evaluation of the market’s valuation ratios more
appropriately includes analysis of the dividend yield and
share buyback ratios. The buyback ratio for the index is calculated
in a similar fashion as a dividend yield is calculated. 6
36
July / August 2011

Figure 2
Dividend And Buyback Ratios On WisdomTree U.S. Indexes (As Of Dec. 31, 2010)
Inception
Date
Trailing
12-Month
Buybacks
($B)
Trailing
12-Month
Dividends
($B)
Dividend
Yield
Buyback
Ratio
Dividend
& Buyback
Ratio
1-Year
Return
Since
Index
Inception
Return
U.S. Dividend Family
WisdomTree Dividend Index 6/1/2006 $240 $247 3.22% 2.06% 5.28% 17.31% 1.50%
WisdomTree Equity Income Index 6/1/2006 $47 $122 4.35% 1.41% 5.76% 18.16% -1.17%
WisdomTree LargeCap Dividend Index 6/1/2006 $218 $211 3.14% 2.21% 5.36% 15.58% 1.03%
WisdomTree MidCap Dividend Index 6/1/2006 $17 $26 3.50% 1.21% 4.71% 22.71% 3.02%
WisdomTree SmallCap Dividend Index 6/1/2006 $5 $10 4.19% 1.00% 5.18% 27.23% 2.45%
WisdomTree Dividend ex-Financials Index 6/1/2006 $68 $119 4.10% 1.66% 5.76% 22.01% 34.91%
U.S. Earnings Family
WisdomTree Earnings Index 2/1/2007 $306 $247 1.92% 2.47% 4.39% 14.95% -0.41%
WisdomTree Earnings 500 Index 2/1/2007 $276 $232 2.00% 2.57% 4.57% 13.60% -1.00%
WisdomTree MidCap Earnings Index 2/1/2007 $23 $22 1.36% 1.90% 3.26% 26.10% 4.24%
WisdomTree SmallCap Earnings Index 2/1/2007 $7 $8 1.37% 1.48% 2.85% 26.60% 2.78%
Sources: WisdomTree, Bloomberg, S&P
The buyback ratio is a market valuation measure used to gauge what percentage of index market value is being reduced by share buyback activity of firms. The dividend and buyback ratio
aggregates the dividends and buybacks together to represent a market valuation metric based on two common ways (dividends and buybacks) that firms distribute cash to shareholders.
Key data highlights as of Dec. 31, 2010:
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continued on page 50
www.journalofindexes.com July / August 2011 37

Developed, Emerging Or
Frontier Markets?
Creating a new framework for country classification
By Francis Gupta
38
July / August 2011

Early in 2011, Dow Jones Indexes introduced a new
methodology for classifying global equity markets.
This methodology is novel in its approach to categorizing
markets in that its classifications are based entirely
on market-centric attributes and investor-centric experiences
in those markets.
Since the new methodology is market-centric in its
approach to country classifications, it focuses only on the
attributes of the equity markets within the countries under
consideration (i.e., members of the Dow Jones Indexes
country classification universe) and does not incorporate
other characteristics, such as socioeconomic indicators of
the countries themselves. This distinction, though subtle,
is important. Consequently, one goal of the new methodology
is to use the merits (and the demerits) of the equity
markets of the member countries as a key factor in grouping
the countries into categories.
The new methodology is also investor-centric. In addition
to the attributes of the equity markets, the country
classifications explicitly incorporate the experiences of
nonlocal investors participating in those markets. This
includes the impact of trading in a market that is unfamiliar
to investors, as well as the processes and regulations
involved in obtaining ownership (and the benefits
thereof) in a foreign market. Consequently, the other goal
of the new methodology is to group markets into categories
based on the type and magnitude of the risks that
participants are exposed to as a result of the regulatory
structure, trading environment and operations associated
with settlement and clearing within a foreign market. 1
The analysis of the global equity markets using the
market-centric and investor-centric approach led Dow
Jones Indexes to classify all country-specific markets
into three categories: developed, emerging and frontier. 2
Countries within a particular category have more in common
with one another in terms of the attributes of their
equity markets and the trading experiences of nonlocal
investors than countries across categories.
Some have suggested that the nomenclature used for the
categories—namely developed, emerging and frontier—
might be a misnomer, as the methodology is not an evaluation
of the countries themselves or their economies per se,
but rather an assessment of their equity markets. However,
market attributes and investor experience do differ significantly
across the three categories. Because more “mature”
and “evolved” equity markets also tend to rate higher in
terms of market efficiency and better investor experiences, it
is not a stretch to refer to the markets within the three groups
as developed equity markets (DM), emerging equity markets
(EM) and frontier equity markets (FM) as long it is clear that
these terms are an indication of the markets themselves.
Another way to view the new methodology is in terms
of the efficiency of the markets. The approach used seeks
to calibrate the markets in terms of factors that are most
important for investors. Therefore, the new Dow Jones
Indexes’ country classifications could also be viewed as
a proxy for how developed and efficient the local equity
markets are in those countries.
Market Size & Breadth And Developmental Status
Figure 1 presents the outcome of implementing the new
classifications methodology for the countries that make up
the Dow Jones Indexes country classification universe. The
countries are ranked by (the logarithm of) the market capitalization
of all companies listed for trading that are domiciled
domestically (as per the Dow Jones Global Total Stock
Market Index methodology) in all of the equity exchanges
within each country. Because a country can only be mapped
into one country classification group, this approach avoids
double counting (or multiple counting) of companies that
are listed on two or more exchanges.
Even though we have not included foreign domiciled
companied that are traded on the local exchanges in this
analysis (see Figure 2 for a count of these listings), doing so
might have been insightful. The availability of foreign companies
listed in a local market makes it much easier for local
investors to assess those companies. In addition, the experience
of an investor transacting in the equity of a locally listed
foreign company would be similar to the investor’s experience
of transacting in the equity of a locally listed domestic
company. Put differently, from the perspective of a foreign
investor, the domicile of the company matters less than the
characteristics and environment of the market it is trading
in. Also, and more importantly, the number of foreigndomiciled
companies trading on a market is an indication of
the breadth of geographic coverage of the market and could
be seen as closely related to the developmental status of the
market since breadth of coverage can be interpreted as a
proxy for the extent to which the market is moving toward
becoming a global equity market. 3
A cursory analysis of Figure 1 suggests that the larger the
equity market (in terms of the market capitalization of the
domiciled companies listed), the more likely that the market
will be classified as developed or emerging. With a few
exceptions, the size of the market is a key indicator of the
developmental status of the market. However, this should
not come as a surprise: A market classifications methodology
that is based on a market-centric (market attributes) and
investor-centric (investor experience) approach will most
likely favor larger markets. This is because the larger the
equity market, the more transparent and liquid it is likely to
be, and therefore the more efficient it will be. Also, because
of the economies of scale associated with the costs of many
market activities, the larger markets are more likely to have
a greater number of market-participating entities (such as
market makers, institutional buyers and sellers, clearinghouses)
that are willing to make upfront investments in
technology and infrastructure to reap the benefits of reduced
costs. These investments in turn enhance the attributes of
the market, which in turn lead to an improvement in the
market efficiency. This makes participation in the market
more attractive to potential investors, thereby increasing the
liquidity of the market, and so the cycle continues. 4
In summary, the size and activity of the market play an
important role in determining its attributes and the investor
experience in the market—both of which in turn influence,
in a crucial way, the market’s size and activity. 5 The
www.journalofindexes.com July / August 2011
39

Figure 1
Market Capitalization Of All Domestic Equity Listings ($M)
U.S.
Japan
U.K.
Canada
France
China
India
Germany
Australia
Brazil
Hong Kong
Switzerland
South Korea
Russia
Taiwan
Spain
Italy
Sweden
Singapore
South Africa
Netherlands
Malaysia
Mexico
Indonesia
Norway
Chile
Turkey
Belgium
Thailand
Denmark
Finland
Israel
Poland
Colombia
Austria
Kuwait
Philippines
Qatar
Portugal
Peru
Egypt
Greece
Ireland
Morocco
United Arab Emirates
Argentina
Czech Republic
Pakistan
New Zealand
Jordan
Hungary
Oman
Sri Lanka
Bahrain
Romania
Slovenia
Cyprus
Mauritius
Lithuania
Malta
Estonia
Slovakia
Iceland
Bulgaria
Latvia
0
2 4 6 8 10 12 14 16
■ Developed ■ Emerging ■ Frontier
Dow Jones Indexes
See Figure 2 for company counts, market capitalizations and coverage of this universe.
40
July / August 2011

speed at which the size and activity of a market interacts
with market attributes and investor experiences—thereby
changing and evolving the market—is the cornerstone of
our global equity markets classification methodology. 6
Market Environment And Regulatory Framework
This section of the methodology examines differences in the
attributes across markets as defined by the environment and
regulatory framework. Note that most, if not all, of the attributes
are exogenous, i.e., they are put into place by an entity outside
of the market, such as a government or regulatory agency.
One key difference between the three major categories
of markets is the extent of openness of the markets to
foreign capital. In general, a market cannot be efficient if
access to capital within a market, together with the flow
of capital across markets, is restricted. Though unlimited
access to capital is not feasible (and is dictated largely by
the local capital markets), the restrictions to the flow of
capital across markets are determined by local market policy
decisions that are made by the local regulatory bodies.
Restrictions on foreign ownership imply that full access to
the market is granted only to a select set of participants.
In theory, the market environment and regulatory framework
can be constructed to improve the efficiency of the
market, thereby leading to the welfare enhancement of all
who are involved. But even though the creation of such a
regulatory framework could be compatible with the interests
of all market participants, in practice such a policy
framework might be difficult to implement. This section
of the methodology evaluates the entire universe of equity
markets on aspects of the regulatory frameworks and market
environments that are in place and are put there to stimulate
improvements in the efficiency of the markets. 7 The following
are the aspects of the market environment and regulatory
framework that are taken into consideration by the new
Dow Jones Indexes country classifications methodology:
Foreign ownership limits and foreign room levels –
Nonexistent limits is the goal; otherwise, the smaller the
limits, the better.
Fair and equal treatment of investors based on domicile
or shareholder status – All investors are viewed equally and
treated identically by the market.
Foreign capital flow restrictions – None are required for
efficient markets.
Level of foreign currency exchange market development –
All currencies are fungible and can easily be exchanged
into another without incurring significant costs. This is one
of many functions of the local capital markets. 8
Special foreign registration or qualification requirement –
Barriers to market participation are undesirable and lead
to undesirable outcomes.
Competitive landscape and presence of anticompetitive
clauses – The former leads to efficient pricing that is beneficial
to consumers and investors, and the latter encourages monopolistic
pricing and overvaluations that are unhealthy for the
economy and detrimental to consumers and investors.
Active regulatory bodies – These should create and
enforce policies that are geared toward generating market
efficiency and increasing total welfare across and for all
entities that participate in the market.
Trading: Market Aspects And Infrastructure
Another key criterion that is evaluated to differentiate
between global equity markets is the experience of investors
in terms of transacting in a foreign market. The market
is a place where buyers and sellers meet to act on their
views about the performance of securities that are traded
in the market. This section of the Dow Jones Indexes country
classifications methodology evaluates the marketplace
in terms of factors that are important to a buyer and seller
that are engaging in such a transaction. The following factors
of the equity markets are considered:
Transaction costs – These can be thought of as the price
that market makers charge for matching up buyers and
sellers and assisting in the trade, or as the price that buyers
and sellers have to pay to participate in the trade. 9 In
general, the more active the market, as measured by volume
and participants, the smaller the transaction costs.
In an ideal market, transaction costs would be negligible
relative to the value of the trade.
Efficient trading platforms – These do the best job at
matching up buyers and sellers. A buyer and seller indicate
the prices at which they are willing to trade through their
“bids” and “asks,” respectively. At any given time, because
there are multiple buyers and sellers interested in trading
any given stock, multiple bids and asks are in the offering.
An efficient trading platform seeks to match up buyers and
sellers so that each seller gets the highest possible price
(given her ask) and each buyer gets the lowest possible
price (given her bid). A good trading platform guarantees
efficiency and is equitable both to buyers and sellers.
Competitive brokerage services – These serve at least three
purposes; they: (i) act as market makers and ensure that
transaction costs are competitive; (ii) act to ensure that trading
platforms are efficient and state of the art; and (iii) act as
counterparties (when lending cash and/or stocks), thereby
allowing increased investor participation (in terms of differing
market views) and consequently enhancing liquidity.
Sufficient level of liquidity to support investor demand –
A security that lacks liquidity can lead to spreads (the difference
between a seller’s ask and a buyer’s bid) that are
so large as to discourage price discovery; ultimately buyers
and sellers will dwindle and vanish, thereby eliminating
the market for the security altogether. When this happens
for a number of securities, the participation in the market
will ultimately dwindle. The market needs liquidity to support
investor demand, and vice versa.
Level of access to market depth and trade-reporting information
– Information on the interests of buyers and sellers
and timely reporting on the prices of ongoing trades assist
in the price discovery process and improve liquidity. When
all of this information becomes available to all entities in
the market in real time, it is an indication that the market
is on its way to becoming efficient.
Short selling and stock lending – Short selling leads to
more efficiency in markets by allowing participants to lever-
www.journalofindexes.com July / August 2011
41

Figure 2
The Dow Jones Country Classification Universe: Counts, Market Capitaliztions And Coverage By Country
Dow Jones Global Total Stock Market Index As Of 12/31/2010
Classification Country # Of Components MCAP ($USB) % MCAP COVERAGE
All Equity Exchanges
As Of Q4 2010 Review
LISTING #
Developed U.S. 3894 15470.9 100% 18248
Japan 1397 3733.5 98% 3843
U.K. 343 2992.0 98% 2388
Canada 449 1857.1 98% 8646
France 160 1766.5 98% 1014
Germany 152 1322.0 98% 10185
Australia 309 1296.0 98% 2001
Hong Kong 500 1181.2 98% 1123
Switzerland 98 1159.9 98% 329
Spain 61 608.6 98% 161
Italy 132 588.2 98% 364
Sweden 131 570.3 98% 567
Singapore 211 565.7 98% 769
Netherlands 53 378.8 98% 184
Norway 85 273.1 98% 238
Belgium 59 251.9 98% 281
Denmark 59 224.0 98% 202
Finland 64 205.9 98% 141
Israel 157 200.7 98% 768
Austria 31 121.5 98% 125
Portugal 21 80.8 98% 69
Greece 87 65.0 98% 299
Ireland 22 56.2 98% 56
New Zealand 39 33.8 98% 170
Iceland 2 1.4 98% 11
Emerging China 173 1527.6 95% 514
India 459 1481.5 95% 2626
Brazil 110 1260.5 95% 714
South Korea 694 972.9 98% 1943
Russia 68 825.5 95% 684
Taiwan 490 786.7 98% 775
South Africa 88 487.8 95% 853
Malaysia 228 372.6 95% 902
Source: Dow Jones Indexes
age their views on prices and by increasing liquidity. Shortsellers
need to be able to borrow stock that they can sell.
Derivative products and markets – These allow participants
to not only trade on their current views regarding
prices, but on their future views as well. But more
importantly, the derivative products and markets provide a
means for participants to manage the risks associated with
their investments and income objectives (for instance, to
smooth out income or earnings).
Depositary receipts – These are securities that are traded
outside the company’s local market but are treated identically
to the local stock; companies issue them seeking to
increase nonlocal interest and participation and increase
liquidity. Since these instruments are issued by companies
and not domiciled in the local market, they also increase
the coverage, or breadth, of the foreign market.
Transferability – From the vantage point of the market,
equity ownership should not be tied to a particular investor;
that is, owners of equity should be able to transfer ownership
to whomever they please. Rules that don’t allow for,
or restrict, transferability of ownership discourage longterm
ownership because they work against investor goals.
Operations: Clearing And Settlement
The final factor in the Dow Jones Indexes country classifications
methodology relates to the management of risks
that buyers, sellers and other market entities (such as market
makers) are faced with in the execution and completion
of a trade or transaction. The more developed markets have
evolved systems and parties in place that minimize the risks
for all of the entities. The risks to the entities arise from the
following features of the securities transaction cycle:
Settlement cycle – This is defined as the receipt of payment
by the seller and receipt of securities by the buyer, and is deter-
42
July / August 2011

Figure 2 cont’d
The Dow Jones Country Classification Universe: Counts, Market Capitaliztions And Coverage By Country
Dow Jones Global Total Stock Market Index As Of 12/31/2010
Classification Country # Of Components MCAP ($USB) % MCAP COVERAGE
All Equity Exchanges
As Of Q4 2010 Review
LISTING #
Emerging Cont’d Mexico 35 345.9 95% 457
Indonesia 80 306.1 95% 411
Chile 48 268.4 95% 285
Turkey 112 262.8 95% 339
Thailand 128 250.9 95% 616
Poland 127 172.6 95% 388
Philippines 46 107.9 95% 305
Peru 19 75.4 95% 277
Egypt 70 65.9 95% 636
Morocco 15 55.0 95% 78
Czech Republic 7 42.5 95% 27
Hungary 6 24.7 95% 46
Frontier Colombia 14 172.1 95% 97
Kuwait 89 111.9 95% 168
Qatar 23 96.8 95% 48
United Arab Emirates 22 54.1 95% 119
Argentina 22 45.8 95% 219
Pakistan 90 33.9 95% 599
Jordan 59 26.2 95% 256
Oman 32 17.4 95% 54
Sri Lanka 68 15.8 95% 247
Bahrain 14 15.5 95% 33
Romania 16 12.1 95% 156
Slovenia 12 7.5 98% 80
Cyprus 14 5.3 98% 131
Mauritius 10 4.3 95% 80
Lithuania 15 3.2 95% 38
Malta 3 2.6 98% 19
Estonia 9 2.1 95% 17
Slovakia 2 1.9 95% 91
Bulgaria 11 1.2 95% 382
Latvia 5 0.6 95% 80
Source: Dow Jones Indexes
Note. “% MCAP Coverage” indicated are minimums to satisfy the index methodology. The number of listings in the “All Equity Exchanges” column includes listings on all
exchanges within the country (even listings of companies domiciled in countries outside of the Dow Jones Indexes Country Classification Universe). Go to www.djindexes.
com for the methodology used to select and map components for the Dow Jones Country Total Stock Market Indexes. Go to http://www.djindexes.com/mdsidx/downloads/
Pricing_and_Exchanges_Table.pdf for a full listing of country coverage by Dow Jones Indexes.
mined by regulatory, bureaucratic and practical constraints.
Assuming everything else is the same across two markets (that
is, all other risks are identical in two markets), the market with
the shorter settlement cycle is the better market. 10
Settlement methods – The preferred method of settlement
is for the exchange of the securities transacted and the payment
for those securities to occur at exactly the same time.
But that ideal may not be feasible in some markets, and
some markets may be governed by other rules. The main
point here is that the settlement method used should not
generate additional risks to anyone involved in the transaction
(namely, the buyer, seller or market maker).
Possibility of using overdrafts – If the trade is agreed
upon by the market maker, the buyer should be able to pay
the seller even if short on funds. The existence of margin
accounts provided by a market maker, or brokerage, to the
buyer is one method to complete the trade. Another is the
availability of overdraft protection provided to the buyer by
a bank or other capital market’s entity.
Availability of omnibus structures – These structures
assist in making local markets accessible to foreign investors—basically,
the more the merrier.
Absence of prefunding practices – The presence of prefunding
constraints imposed on the buyer is neither a fair
requirement nor an attractive feature of an equity market.
Well-functioning central registry – The central registry is
an entity that records all equity transactions. A developed
market has a well-functioning central registry.
Custodian banks and related services – By safeguarding the
continued on page 51
www.journalofindexes.com July / August 2011
43

‘The Devil’s Invention’
An excerpt from ‘The House That Bogle Built’
By Lewis Braham
44
July / August 2011

In “The House That Bogle Built,” journalist Lewis Braham
digs into the details of the life of the man known as the father
of indexing and to many as “Saint Jack.” The book follows
Bogle from his tumultuous childhood through the founding
of one of the world’s best-known mutual fund companies to
his ouster from his own company and rebirth as an investor
advocate. What follows is an excerpted version of Chapter
11, which recounts the development and rise of Vanguard’s
indexing business and the advent of the ETF boom.
Vanguard launched the first index mutual fund,
appropriately named First Index Investment Trust,
in August 1976. Later, the name was changed to
Vanguard 500 Index Fund. The company was not, however,
the first money manager to track an index or even the S&P
500. But if you say to Jack Bogle that he created the first
retail index fund, he’ll holler, “No, no, no, no; don’t use the
word ‘retail’! This is the first index mutual fund—period!”
Although he readily admits that he wasn’t the ur-indexer, he
has, to put it mildly, a lot of pride in the invention, and certainly
without him it’s hard to imagine the index fund ever
getting off the ground with the general public. The concept
may have stayed within the rarefied field of academia or
remained the exclusive province of institutional investors.
But the indexing idea had been kicked around for a long
time before Vanguard launched its famous fund. Bogle
himself had stated in his 1951 Princeton thesis that, “Funds
can make no claim to superiority over the investment
averages, which are in a sense investment trusts with fixed
portfolios,” although in the very same work he would go on
to explain the benefits of actively managed funds. In fact,
in 1960, when two University of Chicago finance wonks
published an article titled “The Case for an Unmanaged
Investment Company” in the Financial Analysts Journal,
Bogle published a rebuttal titled “The Case for Mutual
Fund Management” a few months later, using the pen
name John B. Armstrong so as to avoid getting his employer,
Wellington Management, in trouble with the SEC. In it
he detailed how four unnamed funds—one of which was
Wellington Fund—had beaten the Dow Jones industrial
average for 30 years with less volatility than the market. 1
The first indexed account was created by William Fouse
and John McQuown at Wells Fargo Bank in 1971. Because
at the time the Glass-Steagall Act prohibited banks from
managing mutual funds, Wells Fargo could not launch
an index fund for individual investors. So instead, Wells
Fargo started to run institutional index money in a private
$6 million account for Samsonite, the luggage manufacturer.
Problems immediately resulted, though, because
the benchmark Wells Fargo decided to track was the New
York Stock Exchange, and McQuown and Fouse chose
to equal-weight each of its 1,500 stocks. To maintain an
equal position size in each stock required a great deal of
turnover, and transaction costs consumed too much of
the returns as a result. So in 1973, Wells Fargo switched to
the S&P 500, a low-turnover market-cap-weighted index.
Money manager Batterymarch Financial Management and
the American National Bank in Chicago created similar
indexed accounts for institutions at around the same time.
Although he always thought that most managers would
lag the index, Bogle became a real convert in 1974 after
reading an article titled “Challenge to Judgment” by famed
economist Paul Samuelson in the Journal of Portfolio
Management. In the article, Samuelson pleaded for someone
to start an index fund for retail investors. Bogle then
read Charles Ellis’ article “The Loser’s Game” the following
year, which outlined the basic argument for indexing:
Professional money managers now were the market in
aggregate and would lag it after deducting their fees. 2 Ellis
would later join Vanguard’s board of directors.
As it happened, the timing to create an index fund
couldn’t have been better for Bogle. He had just launched
Vanguard in May 1975 and was looking to internalize
the advisory function of the mutual funds as one of the
steps in “cutting the Gordian knot” that tied Vanguard to
Wellington Management. “The biggest problem was selling
it to Vanguard’s board of directors because we had
agreed not to get into investment management,” says
Bogle. “So I said, ‘This fund didn’t have a manager.’ The
directors bought that. Of course, technically, it’s true. The
fund is unmanaged.” Former and present Vanguard index
fund managers Jan Twardowski, George “Gus” Sauter,
and Michael Buek might beg to differ, and Bogle himself
would later say of his unmanaged fund pitch, “It was one
of the greatest disingenuous acts of opportunism known to
man.” 3 Even index funds need a manager to make sure that
the assets are invested appropriately.
Although he may have had some ulterior motives for
starting the fund, certainly Bogle believed that indexing
would produce the best results for investors. “We started
operations in May 1975 and I had the proposal for the
index fund on the directors’ desk in June of 1975—the first
thing we did,” he says. “Then the idea had to be sold to the
directors, sold with data.” Bogle crunched the numbers
himself, calculating returns for the average mutual fund for
the past 30 years versus the S&P 500 and proving that the
index had an edge of 1.6 percentage points a year. “That
was the evidence I needed to persuade the directors,” he
says. “I didn’t need any persuasion myself.” In May 1976,
Vanguard’s board approved the filing of the First Index
Investment Trust’s prospectus.
But convincing the board was only the first step. Bogle
also had to sell the index fund concept to investors and
Wall Street itself. The reaction within the fund industry
after the 1976 launch was decidedly negative: “the pursuit
of mediocrity,” one commentator called it; “un-American,”
said another; “the devil’s invention,” said a third;
“a formula for a solid, consistent, long-term loser,” said a
fourth. Despite the naysayers, Bogle ultimately persuaded
Dean Witter to lead an underwriting of the new fund.
He’d hoped for $150 million, but it took three months to
raise the $11 million that formed the initial base for the
fund. By the end of 1976, the fund had grown to only $14
million. It was not going to be easy to convince investors
to put their money into a fund that would merely match
the market; investors wanted to beat the market.
www.journalofindexes.com July / August 2011
45

Once the fund was launched, there were a number of
technical challenges to running it. Computing technology
was primitive in the 1970s compared with today, and
instead of PCs, the fund’s first manager, Jan Twardowski,
had to dial in to a mainframe from a terminal via a slow
acoustic coupler modem. Mainframes were big expensive
devices that were shared with multiple users. Twardowski
wrote the program to build the S&P 500 Index portfolio
using an antiquated computing language called APL. But at
the time, the fund didn’t have enough assets to buy all 500
stocks in the index, so Vanguard had to employ a sampling
process of buying the larger stocks in the index and keeping
sector weightings and other aspects of the fund similar
to the index. Even though the turnover in a cap-weighted
index is minimal, there were still significant challenges to
buying and selling hundreds of stocks. Trading for most
funds back then was usually in large blocks of single stocks,
but the index fund needed to buy small blocks of hundreds
of stocks. Vanguard had a special arrangement with an
institutional broker to lower its transaction costs to a nickel
a share, which, at the time, was a bargain.
Gradually, technology improved, transaction costs
declined, and, most important, Vanguard began to win
the ideological argument with investors and the rest of the
fund industry about indexing. The traditional approach to
equity portfolio management, and the one that remains
the industry’s modus operandi today, is to identify specific
stocks that the fund manager believes will best achieve
a fund’s investment objectives and, most important, will
perform better than “the market” itself. In this model, the
advisor actively manages the portfolio by buying and selling
stocks as perceived relative values change.
Vanguard’s introduction of the First Index Investment
Trust represented a complete reversal of this active management
approach—that is, a passive management approach,
under which the manager, in effect, buys stocks in percentages
representing the particular market to be emulated,
essentially holding the securities on a permanent basis and
hoping to replicate the performance of either the overall
market or a predetermined, discrete sector of the market.
Under the passive approach to investing, an index fund
should perform about as well as the market it tracks. Active
investors as a group—fund managers, individuals, pension
managers, and so on—should also match the performance
of the market; indeed, as a group, they are the market. But
active fund managers as a group end up underperforming
the market for their shareholders, largely because of their
funds’ advisory fees, operating expenses and transaction
costs, not to mention any sales loads paid by the investors
who purchase the funds’ shares.
Proponents of the passive school of investing argue that
for the overwhelming majority of funds, active management
works only in the short term, and then only for the gifted or
the lucky. Ultimately, the returns on a mutual fund regress
to the mean and then end up below the mean when expenses
are taken into account. While this line of thinking had
long been argued in academia, gradually the popular media
began to take notice. In particular, the 1973 publication of
Princeton professor Burton Malkiel’s “A Random Walk Down
Wall Street” marked a watershed moment in the history of
finance; not because the ideas were new, but because the
book explained the concept of efficient markets in lay terms
and went on to be a best-seller, selling millions of copies. The
book is currently in its ninth edition. Although he hadn’t read
the book prior to launching Vanguard’s index fund, when he
did, Bogle was amused by Malkiel’s classic assertion that, “A
blindfolded chimpanzee throwing darts at The Wall Street
Journal can select a portfolio that can do just as well as the
experts.” Malkiel would go on to join Vanguard’s board of
directors, and he served from 1977 to 2005.
As it evolved, the efficient market hypothesis, or EMH,
as it is sometimes called, splintered into three categories or
“forms” of theory—weak, semistrong and strong. Weak-form
EMH asserts that stock prices are random, and therefore
most money managers cannot exploit the market to gain an
edge. Although there is an acknowledgment that fundamental
analysis might provide some excess return, whether or
not money managers could exploit valuation inefficiencies
in the market effectively over the long term is called into
question. Semistrong-form efficiency takes the argument a
step further, claiming that the markets adapt so quickly to
all publicly available information that even fundamental
analysis doesn’t add any value. Strong-form efficiency arrogates
that the market is so efficient that it already prices in all
public and nonpublic information, and that even corporate
insiders with private insights can’t gain any legal advantage.
According to both the semistrong and strong versions of the
theory, the price of a company’s share of stock immediately
reflects all available information, as well as investor expectations,
related to the company; in other words, the market
is perfect and right all the time in its assessments of stocks’
underlying intrinsic values.
Bogle never subscribed completely to the efficient market
hypothesis, but rather to something he half-jokingly
dubbed the “cost matters hypothesis.” He examined the
past performance records achieved by both the active and
passive schools. He also examined the costs of each type
of management. He concluded that a fund was far more
likely to produce above-average returns under passive
management than under active management. He based
his conclusion on two factors:
1. All investors collectively own all of the stock market.
Because passive investors—those who hold all stocks in the
stock market—will match the gross return (before expenses)
of the stock market, it follows that active investors as
a group can perform no better: They must also match the
gross return of the stock market.
2. The management fees and operating costs incurred
by passive investors are substantially lower than the fees
incurred by active investors. Additionally, actively managed
funds have higher transaction costs because their
managers’ tactics drive them to buy and sell frequently,
increasing portfolio turnover rates and therefore total
costs. Since active as well as passive investors achieve
equal gross returns, it follows that passive investors, whose
costs are lower, must earn higher net returns.
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July / August 2011

Putting numbers to this theory, the cost difference
is dramatic. Vanguard was saving its index fund investors
about 1.8 percent per year—the expense ratio of the
Vanguard 500 portfolio was 0.2 percent versus 2.0 percent
for the average equity fund (expenses plus transaction
costs). To put that amount into perspective, in a market
with a 10 percent annual return, an index fund might provide
an annual return of 9.8 percent, while a managed fund
might earn an annual return of 8.0 percent. If this happens,
over 20 years, a $10,000 initial investment in an index fund
would grow to $64,900, while an identical investment in a
managed fund would grow to $46,600, a difference of more
than $18,000 in the accumulated account value.
Even though he was deeply committed to indexing, Bogle
was willing to admit that some active investment managers
could add value to the fund management process. In most
cases, he argued, these managers either were lucky or were
among a tiny group of true investment geniuses—market
wizards such as Warren Buffett, Peter Lynch, Michael Price
and Vanguard’s own John Neff. In general, though, Bogle
maintained that trying to outperform the market was a
$1 billion mark in 1988 and beginning the 1990s with $1.8
billion. It then grew to $9.4 billion by 1995 and finally surged
to $107 billion by the March 2000 peak, ultimately surpassing
its archrival the Fidelity Magellan fund in the following
month to become the largest mutual fund in the world.
Along the way, the technology for managing the “unmanaged”
fund had improved dramatically. The fund’s second
manager, Gus Sauter, who today is Vanguard’s CIO, took
over the fund in 1987 and ran it through 2005. “When Gus
first got here and looked at the software that was being
used to manage the index funds, he said, ‘You’ve got to
be kidding me,’” says Vanguard CEO Bill McNabb. “The
software was from the 1970s, a decade old. Gus came in,
taught himself the old computer language, did diagnostics,
and rewrote all the code in his spare time. You can see the
difference in the index funds from the point Gus took over.
There were two factors—one, he rewrote the software, and
two, he figured out how to use [index] futures. You can look
at the tracking error in the early 1980s, and when Gus came
in 1987, and you see this tremendous change in how tightly
the funds began to track their benchmarks.”
John
Bogle
Even though he was deeply committed to indexing, Bogle
was willing to admit that some active investment managers
could add value to the fund management process.
futile exercise. “Index funds,” he said, “are a result of skepticism
that any given financial manager can outperform the
market. How can anyone possibly pick which stock funds
are going to excel over the next 10 years?” In this context,
the best strategy is simply to try to match the market in
gross return and count on indexing’s low costs to earn a
higher net return than most competitors.
All of this, of course, was heresy to traditional active
fund managers, who argued that the only reason to invest
in mutual funds in the first place was to try to maximize
returns, not simply match the market on the way up and the
way down. But eventually, despite the ridicule of active fund
managers, indexing began to catch on. The Vanguard 500
Index enjoyed positive net cash flow in each year of its existence
and had grown to $500 million by the end of 1986—a
decade after its launch. That same year, the Colonial Group
introduced an index fund, the industry’s second. (It would
be out of business by 1990, however, because it carried a
punitive load and a high expense ratio, thus eliminating any
ability to match the index.) By 1988, Fidelity and Dreyfus had
followed suit with their own index fund offerings.
Initially, Bogle spoke of the index fund as “an artistic,
if not a commercial, success,” but that changed during the
1990s, when investors started to notice that the fund was
beating most of its peers. From 1985 through the end of
1999, the Vanguard 500 earned a return of 1,204 percent,
compared to the 886 percent average for the large-cap
blend fund category, according to fund tracker Morningstar.
Gradually, the fund’s assets gathered steam, first topping the
For Bogle, an index fund modeled on the S&P 500 was
only the beginning. As the Vanguard 500 fund grew in
market acceptance and successfully operated at minimal
cost, Bogle’s confidence in the concept increased. The
Standard & Poor’s 500 represented roughly 70 percent of
the market’s capitalization. What about a portfolio that
tracked the remaining 30 percent? Vanguard’s Extended
Market Index, formed in 1987, enabled investors to do
exactly that, tracking the Wilshire 4500 Index.
Later, to simplify the process of holding both the S&P 500
Index and the Wilshire Extended Market Index, Vanguard
offered the Total Stock Market Index, essentially owning the
entire stock market by tracking the Wilshire 5000 Index, the
most comprehensive market benchmark available. In 1989,
the Small-Cap Index was introduced, using the Russell 2000
Index of small stocks, and a lower-cost 500 portfolio was
designed for institutional investors with at least $10 million
to invest. (Originally, most of the above index funds had
slightly different names, often using the word “portfolio”
instead of “index.”) Today, assets in the Total Stock Market
Index actually exceed those in the S&P 500 Index, and Bogle
himself prefers it as the best proxy for the U.S. stock market.
In a speech before the Financial Analysts of Philadelphia
in 1990, Bogle said, “The introduction of index funds
focusing on growth stocks and value stocks awaits only
the development of a growth index and a value index.”
Standard & Poor’s introduced these two new indexes in
May 1992, and just two months later, Vanguard launched
portfolios with similar objectives. Bogle was confident that
www.journalofindexes.com July / August 2011 47

the principles of indexing would also work in world markets—perhaps
work even better, since the expense ratios
and port folio transaction costs of international mutual
funds were far higher than they were for U.S. funds. The
Vanguard International Equity Index Fund was introduced
in 1990, with European and Pacific Rim portfolios; an
Emerging Markets index was added in mid-1994.
Nearly a decade after introducing the first equity index
fund, Vanguard applied the indexing theory to the bond market,
using the Lehman Aggregate Bond Index as a benchmark.
(This index was renamed the Barclays Capital Aggregate Bond
Index in 2008, after Lehman Brothers went bankrupt.) The
Total Bond Market Index Fund, reflecting the market value of
all taxable U.S. bonds, was founded in late 1986 to provide the
same advantages of low-cost, high-quality and broad diversification
to bond fund investors that the Vanguard 500 provided
to equity fund investors. Early in 1994, without much
enthusiasm from his associates, Bogle inaugurated three
additional bond portfolios—short term, intermediate term
and long term—based on the appropriate Lehman indexes.
The three new portfolios, like the original all-market bond
portfolio, met with modest early acceptance but gradually
became increasingly popular. As of October 2010, the Total
Bond Market Index Fund had $89 billion in it, making it one
of Vanguard’s most popular funds.
Although Fidelity and Dreyfus funds joined the indexing
fray in the 1980s, more out of expediency than out of desire,
Vanguard faced no real competition from them in this area
because they weren’t really interested in selling such lowmargin
products. But gradually some other players that
initially had flown beneath the radar emerged as a genuine
threat to Vanguard’s index fund dominance.
Perhaps it should come as no surprise that some of the
same academics involved with the foundations of efficient
market theory helped create Vanguard’s first real competitors.
One of the earliest was Dimensional Fund Advisors
(DFA), which is based in Austin, Texas. Its founders,
University of Chicago MBA graduates David Booth and
Rex Sinquefield, were indexing even before Vanguard,
because Booth and Sinquefield worked, respectively,
at Wells Fargo and American National Bank of Chicago
on their institutional index accounts in the early 1970s.
Together they launched DFA in 1981, providing indexlike
offerings with low expenses not to individual investors,
but to financial advisors and institutions. Other efficient
market “luminaries” such as Eugene Fama and Kenneth
French soon joined DFA’s board of directors.
DFA’s approach to indexing differed from Vanguard’s in
that DFA wasn’t afraid to venture into lesser-known, riskier
areas of the securities markets such as micro-cap stocks and
Japanese small-cap stocks. Its oldest fund, DFA U.S. Micro
Cap, was launched in 1981. The firm was also not such a
purist when it came to indexing, since it would sometimes
tweak published benchmarks to gain an edge, tilting them
more toward a valuation-driven model. Or it would create
its own in-house indexes that it saw as superior to published
ones. It also developed a proprietary trading system
to minimize transaction costs. Although the value ($8.3 billion)
of its largest fund, DFA Emerging Markets, is dwarfed
by Vanguard’s heavy hitters, its low-cost index philosophy
was inspired by the same spirit of modern portfolio theory
as Vanguard’s, and many of its funds have proven highly
competitive with Vanguard’s best.
A far more significant threat emerged from State Street
Global Advisors and Barclays Global Investors in the
form of exchange-traded funds (ETFs). These two money
managers had already become fierce competitors in the
institutional investor space for indexed assets in the 1980s
and 1990s. For instance, total assets under management
at State Street grew from $38 billion in 1988 to $142 billion
by the end of 1993, and much of that institutional money
was in passively managed indexed strategies. But then in
1993, State Street fired a broadside at Vanguard’s retail
business by launching the first ETF in the United States,
the Standard & Poor’s Depositary Receipt, or the SPDR
S&P 500 ETF, as it came to be called. The ETF followed
the same benchmark as the Vanguard 500 fund, but it was
tradable all day long like a stock and therefore was easily
accessible to individual investors. What’s more, the management
fees were competitive with Vanguard’s. In fact,
by March 2000, State Street had reduced the SPDR S&P
500’s expense ratio to 0.12 percent, which was less than
the Vanguard 500’s 0.18 percent for individual investors
at the time. By then the ETF had already attracted some
$17.3 billion in assets.
It wasn’t long before Barclays also entered the arena.
The same division of wonky efficient market enthusiasts
at Wells Fargo Bank that created the first institutional
index account in 1971 was eventually acquired by Britain’s
Barclays Bank for $440 million in 1995 to become Barclays
Global Investors. In the meantime, Barclays had already
become an institutional indexing powerhouse. In 1996,
it collaborated with Morgan Stanley to launch its World
Equity Benchmark Shares, or WEBS, brand of index ETFs
that tracked various international markets such as those
of France, Italy and Japan. These were later rebranded as
iShares in May 2000, which was about the same time that
Barclays started to aggressively launch other ETFs that
tracked U.S. benchmarks similar to Vanguard’s. By the
market’s peak in 2000, Barclays was already managing
$800 billion worldwide, primarily in institutional assets,
but the storm clouds were brewing.
At the time, Vanguard officially claimed that it didn’t see
ETFs as much of a threat. “To me it’s effectively a product
extension like instant coffee,” said Vanguard spokesman
Brian Mattes in March 2000, just as Barclays was preparing for
a major rollout of new ETFs. “When instant coffee debuted,
did it really hurt the sales of brewed coffee? No. People still
liked brewed coffee. But it put coffee in the hands of people
who couldn’t wait for it to percolate.” 4 But behind the scenes,
the pressure was mounting. Indeed, although index funds
had grown from 9 percent of total equity fund assets in 1999
to 17 percent by 2007, 7 percentage points of that number
were from index ETFs. Without ETFs, the index mutual fund
market share would have grown to only 10 percent.
Bogle, for his part, has always seemed ambivalent about
48
July / August 2011

ETFs. He thinks the low costs, broad diversification and
tax efficiency of the more conventional S&P 500 type of
ETFs have the same advantages as traditional index funds,
but he frets that excess speculation in them will eat into
investors’ returns via high transaction costs and thus cause
investors to buy and sell them at inopportune times. “The
ETF is a little bit like the famed Purdey shotgun that you
buy over in London,” he says. “It’s the greatest shotgun
ever made. It’s great for killing big game in Africa, but it’s
also great for suicide.” Needless to say, Vanguard launched
no ETFs under Bogle’s watch as CEO or chairman. And yet
once he stepped down as chairman in 1999, it wouldn’t be
long before Vanguard, too, felt the need to enter the fray.
Perhaps, despite Bogle’s best intentions, his beloved index
fund was on its way to becoming the devil’s invention.
This article was lightly edited to reflect the editorial conventions
of the Journal of Indexes.
Copyright © 2011 by Lewis Braham.
Reprinted with permission of McGraw-Hill.
Endnotes
1 As described in Justin Fox, “The Myth of the Rational Market” (New York: HarperCollins, 2009), pp. 111-112.
2 Ibid., p. 130.
3 Ibid., p. 129.
4 Lewis Braham, “Vanguard’s Arachnophobia,” Fund Watch column, SmartMoney.com, March 23, 2000.
Nolan and Sproehnle continued from page 18
Figure 6
Developed Vs. Emerging Markets
280
260
240
220
200
180
160
140
120
100
80
20.04.2010
04.05.2010
18.05.2010
01.06.2010
15.06.2010
29.06.2010
13.07.2010
27.07.2010
10.08.2010
24.08.2010
07.09.2010
21.09.2010
05.10.2010
19.10.2010
02.11.2010
16.11.2010
30.11.2010
14.12.2010
28.12.2010
11.01.2011
25.01.2011
08.02.2011
22.02.2011
08.03.2011
22.03.2011
05.04.2011
19.04.2011
Markit iTraxx SovX Western Europe
Markit iTraxx SovX CEEMEA
Source: Markit
Some traders have taken positions on the SovX
WE and the Markit iTraxx Senior Financials. The two
indexes have been closely correlated—sovereigns have
bailed out banks and banks are holding government
debt. But this correlation has started to break down in
recent months. The financials index has rallied sharply,
a marked contrast to the volatility in the SovX WE.
Investors are feeling more confident about many of the
banks in the eurozone, with several managing to raise
funds from the capital markets prior to the upcoming
stress tests. But the fiscal situation of the peripheral
countries shows little sign of improvement, and investors
are still bearish on this sector.
Another topic of recent times has been the rise of
emerging markets and the relative decline of developed
countries, when measured in terms of creditworthiness.
Figure 6 shows the convergence of the Markit iTraxx
SovX CEEMEA and the SovX WE over the past year.
When the CEEMEA was launched in January 2010, it
was trading at 221 bp, more than 130 bp wider than the
SovX WE. A year later, the CEEMEA was trading tighter
than the SovX WE, a state of affairs that few would have
foreseen. Again, caveats need to be stated when making
this comparison. The CEEMEA isn’t equally weighted
like the SovX WE: Turkey and Russia account for 30
percent of the index. Both of these sovereigns have
performed relatively well in recent years, and this has
no doubt helped the CEEMEA over this period. But the
main reason for the convergence in the indexes was the
deterioration in peripheral eurozone credit. Investors
will continue to use the two indexes to reflect their views
on developed vs. emerging markets.
www.journalofindexes.com July / August 2011 49

Schwartz continued from page 37
Figure 3
Dividend And Buyback Ratios On WisdomTree International And U.S. Indexes (As Of Dec. 31, 2010)
Inception
Date
Trailing
12-Month
Buybacks
($B)
Trailing
12-Month
Dividends
($B)
Dividend
Yield
Buyback
Ratio
Dividend
& Buyback
Ratio
1-Year
Return
Since
Index
Inception
Return
Regional Analysis
WisdomTree Global Dividend Index 7/1/2008 $282.0 $912 4.04% 0.70% 4.73% 11.60% -0.41%
WisdomTree Emer. Mkts. Dividend Index 6/1/2007 $26.0 $158 3.81% 0.46% 4.27% 23.37% 8.82%
WisdomTree DEFA Index 6/1/2006 $14.0 $451 4.49% 0.08% 4.57% 4.31% 1.63%
WisdomTree Dividend Index 6/1/2006 $240.0 $247 3.22% 2.06% 5.28% 17.31% 1.50%
Equity Income Indexes (High Dividend Yield Subset)
WisdomTree Emer. Mkts. Equity Inc. Index 6/1/2007 $3.0 $59 5.57% 0.32% 5.89% 24.92% 12.35%
WisdomTree DEFA Equity Income Index 6/1/2006 $4.0 $268 5.67% 0.07% 5.74% -1.54% 0.30%
WisdomTree Int’l Div. Ex.-Financials Index 6/1/2009 $1.0 $154 5.50% 0.07% 5.57% 5.43% 26.76%
WisdomTree Global Equity Income Index 12/3/2007 $38.0 $461 5.20% 0.35% 5.55% 6.52% -7.14%
Small-Cap Indexes
WisdomTree SmallCap Dividend Index 6/1/2007 $5 $10 4.19% 1.00% 5.18% 27.23% 2.45%
WisdomTree Emer. Mkts. SmallCap Index 8/1/2007 $0.6 $19 4.36% 0.15% 4.51% 29.96% 8.51%
WisdomTree Int’l SmallCap Dividend Index 6/1/2006 $1.6 $29 4.27% 0.16% 4.42% 19.24% 3.59%
WisdomTree Eur. SmCap Dividend Index 6/1/2006 $0.1 $8 4.03% 0.06% 4.09% 18.21% 1.19%
WisdomTree SmallCap Earnings Index 2/1/2007 $6.6 $8 1.37% 1.48% 2.85% 26.60% 2.78%
Sources: WisdomTree, S&P, Bloomberg
The buyback ratio is a market valuation measure used to gauge what percentage of index market value is being reduced by share buyback activity of firms. The dividend and
buyback ratio aggregates the dividends and buybacks together to represent a market valuation metric based on two common ways (dividends and buybacks) that firms distribute
cash to shareholders.
There are a number of takeaways from our analysis of
dividend and buyback ratios on WisdomTree indexes and
how they fit into the above formula for the markets.
The total return decomposition serves as a reminder
about how one must constantly evaluate the trade-off
between starting dividend yield and future growth rates of
dividends when arriving at return expectations for a given
market. Indexes that start out with higher dividend yields
must rely less on an uncertain future growth of dividends.
When we look at what the dividend and buyback ratios foretell
for the overall market valuation ratios, we see a fairly attractive
picture. John Hussman was bearish quoting the S&P 500
with a dividend yield close to 2 percent. But this commentary
points out that one must include analysis of share buybacks.
When one adds that into the S&P 500 dividends, the combined
dividend and buyback ratio is closer to 4.5 percent.
When we see the dividend and buyback ratio of the
WisdomTree Dividend Index above 5 percent—and one
adds on top of that any normal expectation for future dividend
growth—we see a broad U.S. equity market that looks
very reasonably priced. Moreover, WisdomTree’s regional
equity income indexes had combined dividend and buyback
ratios of 5.5 percent to 5.9 percent, which represent
to us even more attractive valuations for those indexes,
especially when compared to the most common alternative
asset class of choice: U.S. bonds.
Disclosures
You cannot invest directly in an index. Index performance does not represent actual fund or portfolio performance. A fund or portfolio may differ significantly from the
securities included in the index. Index performance assumes reinvestment of dividends, but does not reflect any management fees, transaction costs or other expenses
that would be incurred by a portfolio or fund, or brokerage commissions on transactions in fund shares. Such fees, expenses and commissions could reduce returns.
Endnotes
1. Share buybacks are defined as a company using cash to repurchase shares from investors, thus reducing the company’s shares outstanding.
2. The dividend yield of the S&P 500 is defined as index dividends per share divided by index price.
3. Hussman, John, “No Margin of Safety, No Room for Error,” Oct. 11, 2010, http://www.hussmanfunds.com/wmc/wmc101011.htm
4. Source: Robert Shiller, http://www.econ.yale.edu/~shiller/
5. Share buybacks support higher prices because they reduce the shares outstanding for a company, and assuming the same total dividends or earnings, increase the pershare
dividends or earnings of a firm. Assuming no change in the valuation ratios, the growth in per-share earnings or dividends should lead to a higher stock price.
6. The calculation aggregates buybacks per share times index shares divided by the index market value (price per share times index shares).
Additional index information is available at www.wisdomtree.com
50
July / August 2011

Gupta continued from page 43
assets of market participants, custodian banks assist with minimizing
the risks associated with the market transaction, i.e., the
exchange of securities for cash. Also, the healthier an equity
market, the healthier the competition among custodian banks,
and the better the services offered to market participants.
Conclusion
In the past, from a global investing perspective, it was standard
practice to view the world as made up of developed and
emerging countries. Going forward, when viewed through
the Dow Jones Indexes country classifications framework,
the equity markets will be categorized into developed,
emerging and frontier markets. More specifically, from the
perspective of building global equity portfolios, participants
will now have three distinct equity asset classes to consider:
DM equity, EM equity and FM equity.
Figure 3 presents the historical performance of the
hypothetical indexes that benchmark the performance
of these three equity asset classes. Even though the correlations
among the three categories are high, the categories
differ significantly in terms of their returns and
volatilities. In addition, because of the classifications
methodology used to categorize the markets, the impact
of various risk factors on the performance of the three
indexes will vary extensively.
With the inclusion of more and more markets in the
global equity investment opportunity set, classifying global
equity into just two categories (developing and emerging)
does not fully communicate the variability in terms of the
risk/return characteristics of all of the markets around the
globe. A finer categorization that includes the frontier category
provides the right balance between highlighting the
differences that exist across categories while also capturing
the similarities in the markets within each category.
Based on the variability of the equity markets, it is
Figure 3
Index Value
The DJI Country Classifications Approach Generates
Three Distinct Equity Asset Classes For Global Equity:
Developed Markets (DM), Emerging Markets (EM)
And Frontier Markets (FM)
2500
2000
1500
1000
500
0
DM
EM
FM
3/18/2005
7/18/2005
11/18/2005
3/18/2006
7/18/2006
Ann. Return
4.4%
15.3%
2.5%
11/18/2006
3/18/2007
7/18/2007
11/18/2007
■ DM ■ EM ■ FM
conceivable to group countries into more than three
categories. However, an added benefit of grouping all of
the markets into only three categories ensures that each
group is well represented so as to sufficiently diversify
away country-specific risks within each classification—a
desirable attribute for an asset class.
Sarah Paretti contributed exceptional research for this article.
3/18/2008
Trade Date
Std. Dev.
19.3%
23.8%
15.2%
Source: Dow Jones Indexes
Note: Uses the Dow Jones Indexes Country Classification Universe. See Figure 2 for
countries included in the three equity asset classes. Asset class correlations use
monthly returns. Data from March 18, 2005 through December 31, 2010.
7/18/2008
11/18/2008
DM
1.00
0.91
0.78
3/18/2009
7/18/2009
11/18/2009
Correlation
EM
–
1.00
0.79
3/18/2010
7/18/2010
FM
–
–
1.00
11/18/2010
Endnotes
1. For investors familiar with investing in foreign markets, it is obvious that the first goal of the methodology (equity market attributes) and second goal of the methodology
(investor experiences) are closely related.
2. The frontier category was introduced in the most recent implementation of the methodology. Prior to the introduction of this methodology, all the markets were classified
as either developed or emerging.
3. The ideal market, from the perspective of investors, would be a global equity market that would list all of the world’s publicly traded companies (irrespective of where they
were domiciled) and would be accessible to all investors globally and transacted using the same regulatory, trading and custody rules, and a single unit of value. In such a
market, a local investor would be identical to a foreign investor. In addition, efficiency would require that the transaction costs within this market were determined within
a competitive framework.
4. Economies of scale are another reason why a single global equity market would be the most efficient.
5. Because good data on volumes for global markets is so hard to come by, market activity is not explicitly addressed in this paper.
6. Since the equity markets of frontier countries are “younger,” one might imagine that the interaction between market size, market activity and policy-implemented market
attributes and investor experience would be a significant driver of change in these markets, therefore evolving them at faster rates than emerging and developed markets. But
because investments in the infrastructure of the markets is more rewarding when the market has attained a critical mass in terms of size and activity (so as to exploit the economies
of scale), the frontier markets tend to lag in terms of evolution as compared to developed and emerging markets, which already have achieved that critical mass.
7. In general these criteria, and those described elsewhere in the paper, are qualitative in nature. The classification methodology is focused on comparing these criteria relatively
across the universe of countries under consideration.
8. The level of development of a country’s equity market is closely related to the level of development of a country’s capital markets.
9. Such as the currency tax imposed by Brazil.
10. Currently, a settlement cycle of T+3 is considered the standard.
www.journalofindexes.com July / August 2011 51

News
Russell Launches
First In-House ETFs
In mid-May, Russell Investments,
the Seattle-based money management
and indexing firm, launched six
exchange-traded funds, its first after a
protracted regulatory process that has
left it a latecomer to the now-crowded
field of ETF sponsors.
That’s not to say Russell isn’t at the
center of the ETF business via its
large indexing business. The firm said
in a recent press release that $84 billion
in assets are benchmarked to its
various indexes. Moreover, it sponsors
two Australia-listed ETFs and
made a U.S.-listed fund its own when
it acquired Reno, Nev.-based One
Fund in February.
The new funds, which it called the
“Russell Investment Discipline ETFs,”
are based on what the firm called the
most prevalent strategies professional
investment managers use when selecting
individual securities. They are all
priced at 0.37 percent and include:
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Russell had been trying to obtain
permission from the Securities and
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own line of both active and passive
ETFs for about two years. The process
usually takes anywhere from six to
nine months, though sources at Russell
disputed the notion that its so-called
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were somehow being held up. Industry
sources have said the delays for Russell
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granting exemptive relief to a
firm that already has such a large presence
in the world of indexing.
The six new ETFs all make use of a
new family of indexes Russell launched
in May. Other ETF firms use their own
indexes on their proprietary ETFs—
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7FDUPST&5'TBTXFMMBT8JTEPN5SFF
but the sources said the sheer size of
Russell gave the commission pause.
Each Russell Investment Discipline
ETF tracks the performance of a corresponding
Russell Investment
Discipline Index, which is independently
screened and constructed in
order to reflect the return patterns of a
particular investment strategy, according
to the press release. The Russell
Investment Discipline indexes are constructed
from companies in the Russell
1000 Index, which Russell called the
most widely used U.S. large-cap index
among institutional investors.
Nasdaq-100 Rebalance
Shakes Up Q’s
In early April, Nasdaq said it was
planning a special rebalancing of the
Nasdaq-100 Index, effective May 2,
that would cut Apple Inc.’s percentage
in the benchmark by more than
40 percent. The expected move
immediately sparked selling of Apple
by managers who run index funds
like the Power Shares QQQ Trust
/:4&"SDB222
The rebalancing was the first since
1998, when the exchange adjusted
Microsoft’s and Intel’s outsized positions
in the portfolio to address compliance
issues with the Internal Revenue
Service. A one-off occurrence, it reorganized
the portfolio into a straight
market-cap arrangement. But the
index’s underlying modified marketcap
methodology, which was instituted
in 1998, remained unchanged,
Nasdaq said in a press release.
Apple’s weighting in the index
fell to 12.33 percent from more than
20 percent, putting an end to the
company’s outsized position in the
benchmark. A total of 82 stocks were
slated to have lower weights after the
rebalance, Nasdaq said. However,
the weighting of other tech heavyweights
in the benchmark—includ-
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and Intel—was to increase.
The Nasdaq-100, which features the
100 biggest nonfinancial companies
within the broader Nasdaq benchmark,
was rebalanced based on holdings
as of March 31, Nasdaq said.
Case-Shiller Indexes
Suggest Housing Slump
U.S. home prices in some cities are
the lowest they’ve been in more than
a decade, and others continue to test
their 2009 lows in what some economists
say has the makings of a potential
double-dip in housing, according
UP UIF MBUFTU 41$BTF4IJMMFS )PNF
Price Index report covering February.
High unemployment, sluggish
property sales and housing starts, as
well as ongoing foreclosures, continue
to weigh on the U.S. housing market
as it struggles to stage a sustainable
recovery after the market crash of
2008-2009. Prices in 19 of the 20 cities
surveyed fell in February.
The report for February revealed
that home prices nationally are edging
closer to testing their 2009 lows,
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$PNQPTJUFT JO UIF EBUB TFSJFT EPXO
on the year, the latter being “within a
hair’s breadth of a double dip,” S&P’s
$IBJSNBO PG UIF *OEFY $PNNJUUFF
David Blitzer said in the report.
Housing was at the center of the
credit crisis that triggered the worst
U.S. economic downturn since the
1930s, and remains a crucial aspect of
lasting recovery. The home market was
52
July / August 2011

temporarily buoyed by a government
tax-credit program aimed at boosting
demand. But strength faded when the
incentives expired last summer.
In February, the 10-City and 20-
City composites dropped 1.1 percent
month-on-month from January levels,
and are now more than 32 percent
below their mid-2006 peaks. All in all,
home prices nationally were back to
where they were in the summer of 2003.
Nineteen of the 20 cities surveyed
saw month-on-month price declines in
February, and 14 of them have seen
declines for at least six straight months.
ProShares Expands Bond Lineup
With fears of a bond-market selloff
unsettling investors, ETF providers
were launching inverse and leveraged
bond ETFs left and right over the last
few months, attempting to capitalize
on investors’ desires to play the possibilities
in the market. ProShares, for
one, dramatically expanded its lineup
of fixed-income offerings.
Beginning in late March, the firm
rolled out six different ETFs tied to the
corporate and Treasury segments of
the fixed-income market:
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There has been significant debate of
late as to whether the bond market is in
a bubble, and the raft of products from
ProShares makes it easier for both sides
to invest according to their views.
The new ProShares ETFs each charge
annual expense ratios of 0.95 percent.
INDEXING DEVELOPMENTS
MSCI Debuts Risk-Weighted
Index Family
In April, MSCI said that it had
launched alternatively weighted versions
of its MSCI All Country World
Index, MSCI Emerging Markets
Index and MSCI World Index.
Rather than weighting by pure
market capitalization, MSCI’s riskweighted
indexes assign weights
based on historical returns variance,
with lower-volatility stocks receiving
heavier weights.
The MSCI ACWI Risk Weighted
Index, the MSCI Emerging Markets
Risk Weighted Index and the MSCI
World Risk Weighted Index are each
designed to help investors manage
risk; they offer a lower risk profile
than their standard methodology
counterparts.
The new index series is just the latest
nontraditional family of benchmarks
to come out of the MSCI shop. In the
past few years, the firm said in a press
release, it has also debuted minimum
volatility and value-weighted series.
Markit Unveils
LatAm Sovereign Index
Markit announced in late March
that it was launching a benchmark
tracking Latin America’s sovereign
credit default swap market as part of
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5IF .BSLJU J5SBYY 4PW9 -BUJO
America Index covers issues from
Argentina, Bolivia, Brazil, Chile,
Colombia, Mexico, Panama and
Mexico. Components are equal weighted
and selected based on liquidity.
.BSLJUTJ5SBYY4PW9GBNJMZBMSFBEZ
included a variety of regional indexes,
including ones covering Asia Pacific,
8FTUFSO&VSPQFBOEUIF(DPVOUSJFT
among others.
The index is not yet tradable, but
Markit said that could change depending
on investor demand.
S&P Debuts CIVETS Index
Early May saw the launch of the
unusually named S&P CIVETS 60. The
press release said the index targets what
it terms “second-generation” emerging
markets. The CIVETS acronym stands
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they’ve been in more than a decade.
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www.journalofindexes.com July / August 2011 53

News
for Colombia, Indonesia, Vietnam,
Egypt, Turkey and South Africa.
The index includes 60 components,
consisting of 10 liquid stocks from each
of the six targeted countries, the press
release said. Components are weighted
by modified market capitalization.
South Africa carried the heaviest
weight in the index at launch, at 31.6
percent. It was followed by Indonesia
at 28.3 percent, Turkey at 21.8 percent,
Colombia at 12.4 percent, Egypt at 4.9
percent and Vietnam at 1 percent.
Russell Unveils
Global Index Family
In mid-March, Russell Investments
launched a new family of global
indexes headlined by the Russell
Global 3000 Index.
Derived from the broad Russell
Global Index, the Russell Global 3000
Index comprises the largest 1,000 stocks
from a screened subset of the Russell
Global Large Cap Index (which represent
the Russell Global 1000 Index) and
the largest 2,000 stocks from a screened
subset of the Russell Global Small Cap
Index (which represent the Russell
Global 2000 Index). The family also
includes “ex-U.S.” and value and growth
subindexes for each of its size segments.
The narrower global indexes are
designed for use in investable products
and to correlate strongly with the
broader Russell Global indexes, Rolf
Agather, managing director of Russell’s
index business, said in a press release.
In fact, Russell has filed with the
SEC to launch ETFs based on the
indexes in the new family.
New FTSE Index Family
Targets Infrastructure
FTSE rolled out a new index family
at the end of March that focuses on the
infrastructure sector. A press release
said the FTSE Infrastructure Index
Series (FIIS) covers more than 800
stocks from 40 countries and includes
nine indexes, six of them targeting
infrastructure subsectors.
The series’ six subsectors include
telecommunications core infrastructure;
energy core infrastructure;
transportation core infrastructure;
infrastructure-related conveyance
services; infrastructure-related communications
services; and infrastructure-related
materials & engineering.
The FIIS methodology further classifies
companies into two tiers in terms
of infrastructure exposure: Those
deriving more than 65 percent of their
revenues from infrastructure are designated
“core infrastructure” companies,
while companies deriving from 20 percent
up to 65 percent of their revenues
from infrastructure are labeled “infrastructure-related
opportunities.”
The index series can be customized
according to geography, infrastructure
exposure and sector.
Dow Jones Indexes
Adds To RBP Roster
Dow Jones Indexes said in late April
it was adding four new U.S. large-cap
benchmarks to its series of Dow Jones
RBP Indexes.
The style-based Dow Jones RBP U.S.
Large-Cap Growth Index, Dow Jones
RBP U.S. Large-Cap Value Index and
Dow Jones RBP U.S. Large-Cap Core
Index rely on the same quantitative
strategy Dow Jones already employs
in its other 18 RBP large-cap indexes,
which is based on Transparent Value’s
rules-based analytics.
Each benchmark, comprising 100
U.S. large-cap stocks, selects securities
based on the probability a company
has of delivering a performance
that would support its current stock
price, as measured by a methodology
the company calls the Required
Business Performance (RBP), the
company said in its website.
The growth index picks from a pool
consisting of the top 750 U.S. growth
stocks by market capitalization, with
Google, Priceline and Apple being
its biggest holdings. The value-based
stock portfolio currently holds CME
Group, Goldman Sachs and PPG
Industries as its top names, while the
core index is a blend of the two, holding
the top 50 names in each of the
other two portfolios.
Also launched was the Dow Jones
RBP U.S. Dividend Index, the first
within the RBP lineup to rely on dividends
as the key measure used to
select and weight stocks, the company
said in a press release.
The indexes are rebalanced quarterly.
S&P Releases Oil-Hedged
S&P 500 Index
In early May, S&P rolled out the S&P
500 Oil Hedged Index. The index represents
long positions in the S&P 500 and
in a 50-50 mix of NYMEX oil and ICE
Brent crude oil futures, with the equity
and futures positions equal weighted.
The idea is that the oil exposure will
hedge against a potential rise in inflation
or a drop in the value of the U.S. dollar.
S&P specifically notes in the related press
release that the index does not hedge
against standard stock market risk.
The index’s weights are reset on a
monthly basis.
Citigroup Adds To
International Bond Indexes
In late March, Citigroup made
significant additions to its lineup
of sovereign bond indexes targeting
Asian markets.
The Chinese Government Bond
Index and the Sri Lankan Government
Bond Index both joined the firm’s other
Asian bond indexes, with the Sri Lankan
index also being included in the broader
Asian Government Bond Index, which
already covered Indonesia, South Korea,
Malaysia, the Philippines, Singapore,
Taiwan and Thailand. The Chinese
index is not included in the AGBI, but
in conjunction with the Chinese index’s
rollout, Citigroup also debuted the
AGBI-Extended, which combines the
two benchmarks.
But that wasn’t the only new broad
benchmark: The bevy of launches
included the Asia Pacific Government
Bond Index, which encompasses the
AGBI and the sovereign bond markets
of Australia and New Zealand.
Finally, Citigroup announced plans
at the time to launch the Dim Sum
Bond Index, which was to cover yuandenominated
bonds issued in Hong
Kong. It launched in May.
54
July / August 2011

BarCap Launches
Inflation-Fighting Index
In April, Barclays Capital rolled
out the Barclays Capital Equity
Inflation-Response Index. The
index basically targets stocks that
have shown the ability to leverage
their strong pricing power into real
returns during inflationary periods.
Using statistical analysis, Barclays
identifies what it calls “eligible super
sectors” that typically have displayed
above-average performance when
inflation has been high. Currently,
those sectors include oil, mines, beer
& liquor, agriculture, coal, defense,
health care, insurance, business services
and fabricated products. The
index’s selection methodology ranks
the stocks in each sector by dividend
yield and book value, selecting the
top five in each sector for the index.
Currently, Barclays Capital applies
the “Inflation-Response” methodology
to the U.S., Europe, Asia and its emerging
markets classification. Variations
on the long-only index include long/
short and risk-controlled adaptations.
DJI Teams With FXCM
On Dollar Index
Dow Jones Indexes announced in
early May that it had teamed with
FXCM Inc. to create the Dow Jones
FXCM Dollar Index, which measures
the performance of the U.S. dollar
versus an equal-weighted basket of
four currencies.
According to DJI, the euro, British
pound, Japanese yen and Australian
dollar represent 80 percent of the FX
global spot market’s trading volume.
The index’s methodology is such that
component currencies are selected
based on trading activity and the geographic
diversification.
According to the index’s methodology,
rebalances are triggered by an
individual currency position falling
below $1,000 (each position represented
$10,000 at the start of this year) or
by extraordinary events in the form of
structural changes in the FX market.
FXCM is an online brokerage firm
focused on the FX market.
STOXX Rolls Out
Infrastructure Indexes
STOXX Limited debuted the Stoxx
Global Extended Infrastructure 100
and STOXX Global Infrastructure
Suppliers 50 indexes in May.
Components are selected from the
STOXX Global Total Market Index,
excluding the China A-Shares market,
after being screened by Revere Data
LLC, which sorts infrastructure and
infrastructure supplier companies
into 11 infrastructure-related sectors.
The STOXX Global Extended
Infrastructure 100 Index includes the
largest seven infrastructure stocks
from each of the 11 sectors, and then
afterward simply selects the rest of
its components based purely on freefloat
market capitalization from the
remaining pool of all the sectors.
Similarly, the infrastructure suppliers
index selects the top four infrastructure
suppliers from each sector,
before adding its remaining components
from the remaining pool based
on market capitalization alone.
AROUND THE WORLD OF ETFs
First Trust Expands
AlphaDex Lineup
First Trust launched 13 new ETFs
on April 19 tied to its quantitatively
driven AlphaDex indexes, including
nine international and four domestic
equity funds. The move represents a
significant expansion of First Trust’s
overall fund lineup.
The international funds, which
track “enhanced” rules-based S&P
AlphaDex indexes that take into
account growth and value factors when
screening for securities, include:
r'JSTU 5SVTU "TJB 1BDJGJD &Y+BQBO
AlphaDex Fund (NYSE Arca: FPA)
r'JSTU 5SVTU &VSPQF "MQIB%FY 'VOE
(NYSE Arca: FEP)
r'JSTU 5SVTU -BUJO "NFSJDB "MQIB%FY
Fund (NYSE Arca: FLN)
r'JSTU 5SVTU #SB[JM "MQIB%FY 'VOE
(NYSE Arca: FBZ)
r'JSTU 5SVTU $IJOB "MQIB%FY 'VOE
(NYSE Arca: FCA)
r'JSTU 5SVTU +BQBO "MQIB%FY 'VOE
(NYSE Arca: FJP)
r'JSTU 5SVTU 4PVUI ,PSFB "MQIB%FY
'VOE /:4&"SDB',0
r'JSTU5SVTU%FWFMPQFE.BSLFUT&Y64
AlphaDex Fund (NYSE Arca: FDT)
r'JSTU 5SVTU &NFSHJOH .BSLFUT
AlphaDex Fund (NYSE Arca: FEM)
Meanwhile, the new U.S. equity
funds include the following:
r'JSTU5SVTU.JE$BQ(SPXUI"MQIB%FY
Fund (NYSE Arca: FNY)
r'JSTU5SVTU.JE$BQ7BMVF"MQIB%FY
'VOE /:4&"SDB'/,
r'JSTU 5SVTU 4NBMM $BQ (SPXUI
AlphaDex Fund (NYSE Arca: FYC)
r'JSTU5SVTU4NBMM$BQ7BMVF"MQIB%FY
Fund (NYSE Arca: FYT)
The international funds each charge
an expense ratio of 0.80 percent, while
the domestic funds charge 0.70 percent.
First Trust unveiled its AlphaDex
methodology in 2007.
New SPDR Tracks
High-Yield Munis
State Street Global Advisors rolled
out a municipal bond ETF in mid-
April focused on high-yield debt.
The SPDR Nuveen S&P High Yield
Municipal Bond ETF (NYSE Arca:
HYMB) charges an annual expense
ratio of 0.45 percent, including a 0.05
percent fee waiver that will extend for
at least a year, until April 13, 2012. Its
competitor, the $177 million Market
Vectors High-Yield Municipal Bond
ETF (NYSE Arca: HYD), comes with a
price tag of 0.35 percent.
HYMB tracks the S&P Municipal
Yield Index, which includes more
than 21,000 issues. By comparison,
Van Eck’s HYD is benchmarked to the
Barclays Capital Municipal Custom
High Yield Composite Index, comprising
about 5,700 bonds, according to
the company’s website.
Van Eck Debuts
Floating-Rate Bond ETF
In late April, Van Eck launched a
floating-rate bond ETF the company
says is designed to help investors generate
yield while minimizing risk exposure
through a portfolio solely comprising
investment-grade notes. The Market
Vectors Investment Grade Floating
www.journalofindexes.com July / August 2011 55

News
Rate ETF (NYSE Arca: FLTR) has a gross
annual expense ratio of 0.49 percent,
but a net expense ratio of 0.19 percent.
While floating-rate notes are typically
attractive in an environment of
rising interest rates as a short-term
source of income, an investmentgrade
version goes even further by
helping to offset some of the issuer
credit risk as well as liquidity concerns
often associated with belowinvestment-grade
bank loans.
Also, because the notes have variable
coupons linked to the threemonth
Libor (London interbank
offered rate), their values are likely
to fluctuate less when interest rates
change than would bonds with fixed
yields, lowering interest rate risk, Van
Eck said in a press release.
FocusShares Returns
In the final days of March,
FocusShares—now owned by
Scottrade—returned to the ETF market
with the launch of 15 funds tied to
Morningstar indexes.
Notably, many of the products are
the cheapest, or among the cheapest,
ETFs in their asset category. The
funds are also commission free to
Scottrade’s 2 million clients as well as
800 financial advisors who are part of
its Scottrade Advisor Services.
The Focus Morningstar US Market
Index ETF (NYSE Arca: FMU) has
an annual expense ratio of 0.05 percent,
0.01 percent cheaper than the
Schwab U.S. Broad Market Equity
ETF (NYSE Arca: SCHB). And the
Focus Morningstar Large Cap Index
ETF (NYSE Arca: FLG)—also priced
at 0.05 percent—is 1 basis point
cheaper than the Vanguard S&P 500
ETF (NYSE Arca: VOO).
The remainder of the funds cover
the midcap and small-cap size segments,
the real estate market and the
standard 10 sectors.
Global X Rolls Out
Waste Management Fund
Global X recently launched an
equities ETF that’s focused on companies
in waste management industries,
again bringing it into competition with
New York-based Van Eck.
Indeed, the Global X Waste
Management ETF (NYSE Arca: WSTE)
looks quite a lot like the Market Vectors
Environmental Services ETF (NYSE
Arca: EVX). Global X’s WSTE is based
on an index with 28 companies, compared
with a 22-company benchmark in
the case of Van Eck’s EVX. Both indexes
hold some of the same companies.
Van Eck’s EVX, for now, is the
cheaper of the two environmentally
focused ETFs, with a 0.55 percent net
annual expense ratio, while WSTE
costs investors 0.65 percent per year.
DB, PowerShares Roll Out
Sovereign Debt ETNs
In late March, Deutsche Bank
rolled out three pairs of ETNs focused
on German, Italian and Japanese sovereign
debt futures that serve up single-
and triple-long exposure to their
respective indexes. The German bank
uses Invesco PowerShares for marketing
of the notes.
The ETNs include:
r1PXFS4IBSFT %# (FSNBO #VOE
Futures ETN (NYSE Arca: BUNL)
r1PXFS4IBSFT %# Y (FSNBO #VOE
Futures ETN (NYSE Arca: BUNT)
r1PXFS4IBSFT%#*UBMJBO5SFBTVSZ#POE
Futures ETN (NYSE Arca: ITLY)
r1PXFS4IBSFT %# Y *UBMJBO 5SFBTVSZ
Bond Futures ETN (NYSE Arca: ITLT)
r1PXFS4IBSFT%#+BQBOFTF(PWU#POE
Futures ETN (NYSE Arca: JGBL)
r1PXFS4IBSFT %# Y +BQBOFTF (PWU
Bond Futures ETN (NYSE Arca: JGBT)
The triple-exposure securities
rebalance monthly, the same as all
leveraged DB PowerShares products.
The single-exposure ETNs each
have an expense ratio of 0.50 percent,
while the triple-exposure products
have expense ratios of 0.95 percent.
iPath Unveils
18 Commodity ETNs
iPath rolled out 18 new ETNs in late
April focused on commodities and
designed to protect returns by seeking
exposure that minimizes contango.
Each of the new iPath Pure Beta
Commodity ETNs was constructed
around the concept of providing the
best proxy for the average price return
of the front-year futures contracts for
each commodity in the index, while
avoiding parts of the futures curve
that are subject to persistent market
distortions, the company said in a
press release. The underlying indexes
use the Barclays Capital Pure Beta
Series 2 methodology.
The list of products includes a note
tracking a “Pure Beta” version of the
S&P GSCI, the iPath Pure Beta S&P
GSCI-Weighted ETN (NYSE Arca:
SBV), as well as another note—the
iPath Pure Beta Broad Commodity
ETN (NYSE Arca: BCM)—tracking
the Barclays Capital Pure Beta Broad
Commodity Index. The remaining
notes track subsets of the latter,
including seven sectors and nine
individual commodities.
All the new Pure Beta ETNs, and
a separate 19th note introduced at
the same time—called the iPath
Seasonal Natural Gas ETN (NYSE
Arca: DCNG)—come with a 0.75 percent
annual expense ratio.
The Q’s Lose A ‘Q’
Invesco PowerShares changed
the ticker symbol on its popular
Nasdaq-100 ETF, the PowerShares
QQQ Trust (Nasdaq GM: QQQ) to
“QQQ” from “QQQQ” so that the
fund’s name matches its ticker.
The change became effective on
.BSDI1PXFS4IBSFTFNQIBsized
in a prepared statement that
everything else about the funds would
remain exactly the same, including its
listing on the Nasdaq exchange.
WisdomTree Debuts
Asian Bond ETF
WisdomTree Investments debuted
an actively managed Asia ex-Japan
bond fund denominated in local currency
in mid-March.
The WisdomTree Asia Local Debt
Fund (NYSE Arca: ALD) will cast a
wide net, covering China, Hong
Kong, India, Indonesia, South Korea,
Malaysia, Philippines, Singapore,
56 July / August 2011

Taiwan, Thailand as well as Australia
and New Zealand. The fund deliberately
excludes Japan, while Vietnam’s
poor fundamentals mean that it didn’t
make the cut for inclusion.
ALD doesn’t use a benchmark;
rather, its constituents are chosen by
a WisdomTree investment committee
focused on a number of parameters in
a given country, including liquidity,
debt-to-GDP ratio, foreign reserves,
inflation and unemployment.
The fund has an expense ratio of
0.55 percent.
BACK TO THE FUTURES
CME Volume Up
2 Percent In April
April 2011 saw an average daily volume
traded of 12.1 million contracts, a
2 percent year-over-year increase for
the month.
However, equity index products
were the worst-performing category
for the month, averaging 2.2 million
contracts per day, about 18 percent
of the exchange’s total daily volume.
That’s down 14 percent from the
prior-year month. The e-mini S&P
500 futures contract, the CME’s most
popular index product, saw its total
volume for April fall nearly 25 percent
year-over-year to less than 33 million
contracts. Likewise, total volumes
for two other popular index futures
contracts, the e-mini Nasdaq-100 and
e-mini $5 Dow, were down roughly 17
and 32 percent, respectively.
KNOW YOUR OPTIONS
CBOE Debuts GLD-Based
Volatility Options
The Chicago Board Options
Exchange on April 12 launched tradable
options on the CBOE Gold ETF
Volatility Index that are based on
SPDR Gold Shares (NYSE Arca: GLD)
options, allowing investors to hedge
risks of investments in gold.
The CBOE Gold ETF Volatility Index,
sometimes referred to as the “Gold VIX,”
has been calculated and distributed by
CBOE since 2008, the futures exchange
said in a press release. The Gold VIX’s
calculation is based on the methodology
used for the CBOE Volatility Index
and applied to options on GLD.
The Gold VIX is an up-to-the-minute
market estimate of the expected
30-day volatility of GLD, calculated
using real-time bid/ask quotes of
GLD options listed on CBOE. GLD,
which had $55.87 billion in assets as
of April 5, is the second-biggest ETF
in the world. It is also the fifth-mosttraded
U.S. ETF.
CBOE Volumes Fall
From April 2010
CBOE Holdings Inc. saw its average
daily volume for April fall 19 percent
year-over-year. Index and ETF
options, however, did not fall quite as
dramatically.
Index options, at about 23 percent
of the total options volume, saw their
average daily volume fall 13 percent,
while ETF options—about 28 percent
of the total options volume experienced
a 1 percent increase in average
daily volume. The real drop-off was
in equity options, which represented
about 49 percent of the exchange’s
volume in April and saw their average
daily volumes fall by 29 percent.
The most actively traded options
contracts in the index and ETF product
groups included the contracts on
the S&P 500 Index, the SPDR S&P 500
(NYSE Arca: SPY), the CBOE Volatility
Index, the iShares Silver Trust (NYSE
Arca: SLV) and the PowerShares QQQ
Trust (Nasdaq: QQQ).
FROM THE EXCHANGES
Nasdaq Optimizes Nasdaq-100
In early May, Nasdaq OMX Group,
the company behind the Nasdaq
exchange, launched a new “optimized”
version of its popular Nasdaq-100
Index that should offer better liquidity
than the original benchmark, all
while preserving return and volatility
characteristics.
The Nasdaq-100 Data Explorers
Optimized Index is essentially a subset
of the securities included in the
Nasdaq-100 Index—a basket of the
largest nonfinancial companies globally—but
the new benchmark screens
out stocks with low liquidity or those
that are relatively expensive to borrow
in the share-lending market.
At launch, the new index—which
relies on data provided by global stock
loan data provider Data Explorers—
excluded 18 securities from the original
index, the company said in a
press release.
Russell And Chi-X
Create Index Family
In late March, an announcement
from Chi-X Europe and Russell
Investments heralded the two companies’
joint plans to create a European
index series, with Russell providing
the methodology and Chi-X providing
pricing. The press release said that
this would be the first index family to
use single-source pricing for the pan-
European region.
According to the press release,
the indexes will target Europe’s largest
and most liquid stocks. They are
intended to be investable and offer
comprehensive coverage of the geographic
region, with attention paid to
currency exposure and tracking error.
The announcement said that Chi-X
Europe plans to introduce futures and
options tied to the indexes.
www.journalofindexes.com July / August 2011
57

Blanchett continued from page 31
methodology employed in this research materially reduces
the potential impact of survivorship bias on the results.
For the combination analysis, quartile groupings are
used (versus deciles previously) to ensure that the population
of funds in each group is reasonable for each category
(defined as being 10 funds at a minimum for each quartile
capitalization combination). This approach creates a 4x4
matrix. Note the 4x4 matrix was not created using any type
of re-sorts. Instead, each fund is assigned its quartile group
based on its actual past-performance quartile group and
expense ratio quartile group. Not surprisingly, this leads to
certain quartile combinations having more funds in a given
period than others (e.g., the high-flow and low-expenseratio
combination group has materially more funds than
the low-flow and high-expense-ratio group). Not performing
re-sorts better matches the information available to
investors when making purchase decisions (note, though,
re-sorted tests yielded virtually identical results).
tended to underperform their peers in the year following
receiving the new monies.
The ‘Fixed-Income Flow Factor’
By subtracting the respective past performance for a given
quartile combination group, it is possible to determine the
return “cost” associated with fund flows for intermediateterm
bond mutual funds. This calculation approach is similar
to the way other market-neutral factors are created, such
as HML and SMB factors in the Fama and French [1993]
three-factor model. SMB, or small minus big, is the difference
in the performance of small-caps over large-caps.
Since the funds with lower expense ratios tend to get
more inflows than funds with higher expense ratios, the
way to determine the “cost” of flows is to look at the difference
in the future gross performance and future net performance
independently. This ensures that management fees
are not driving the potential difference in performance.
There does appear to be a strong relationship for fund flows.
Those funds that received the majority of the flows tended to
underperform their peers in the year following receiving the new monies.
Results
The results of the combination test are included in
Figure 6. As the reader can see from Figure 1, the bestperforming
combination groups tended to be those that
were the cheapest (especially when looking at net returns)
as well as those that had the least flows. The relative importance
of expense ratios dissipates when viewing the outperformance
on a gross basis (where funds are sorted by
expense ratios but the subsequent performance excludes
all investment management and fund administration fees)
versus a net basis. In theory, if more expensive fixedincome
managers were “worth” the additional cost, they
should have higher gross performance (at minimum), but
the analysis suggests there is no relationship between the
cost of money management and subsequent performance.
There does appear to be a strong relationship, either
viewed on a net return or gross return basis, for fund
flows. Those funds that received the majority of the flows
However, whether viewed on a net return or gross return
basis, the “flow factor” cost is approximately 40 bps. The
cost for gross returns is 42 bps with a t statistic of 2.45, and
the cost for net returns is 40 bps with a t statistic of 2.38.
Conclusion
The results of this analysis suggest there is definitely a
cost associated with new flows for fixed-income mutual
funds. Funds that receive substantial inflows are likely to
underperform those funds that receive the least amount
of flows by approximately 40 bps after accounting for
any differences in expense ratios. This underperformance
has substantial implications for investors, especially
given the recent growth in fixed-income funds.
Expense ratio is also noted as a significant driver of
relative performance, suggesting that a bond investor
is better served by buying a low-cost option, which will
typically be a passively managed portfolio.
References
Chevalier, Judith, and Glenn Ellison. 1997. “Risk Taking by Mutual Funds as a Response to Incentives.” Journal of Political Economy, vol. 105, No. 6: 1167-1200.
Fama, Eugene F., and Kenneth R. French 1993. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics, vol. 33, No. 1: 3-56.
Frazzini, Andrea, and Owen Lamont. 2008. “Dumb Money: Mutual Fund Flows and the Cross-Section of Stock Returns.” Journal of Financial Economics, vol. 88, No. 2 (May): 299-322.
Gruber, Martin. 1996. “Another Puzzle: The Growth in Actively Managed Mutual Funds.” Journal of Finance, vol. 51, No. 3: 783-810.
ICI Factbook 2010. www.ici.org/pdf/2010_factbook.pdf
Ippolito, Richard A. 1992. “Consumer Reaction to Measures of Poor Quality: Evidence from the Mutual Fund Industry.” Journal of Law and Economics, vol. 35 (April 1992): 45-70.
Jegadeesh, N. and S. Titman. 1993. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance, vol. 48: 65-91.
Sirri, Erik R., and Peter Tufano. 1998. “Costly Search and Mutual Fund Flows.” Journal of Finance, vol. 53, No. 5: 1589-1622.
Zheng, Lu. 1999. “Is Money Smart? A Study of Mutual Fund Investors’ Fund Selection Ability.” Journal of Finance, vol. 54: 901-933.
58
July / August 2011

Global Index Data
Selected Major Indexes Sorted By YTD Returns
July/August 2011
Total Return % Annualized Return %
Index Name YTD 2010 2009 2008 2007 2006 2005 2004 3-Yr 5-Yr 10-Yr 15-Yr Sharpe Std Dev
MSCI Hungary* 34.44 -10.70 73.88 -62.45 13.40 31.11 15.60 87.51 -4.92 -0.53 16.84 14.37 0.17 51.52
Oil Price Brent Crude* 32.87 20.86 79.30 -53.86 58.26 3.78 42.37 34.89 3.75 11.85 16.50 13.03 0.29 39.07
MSCI Czech Republic* 27.70 -7.40 19.56 -45.05 51.67 29.64 43.46 76.59 -7.65 6.55 25.21 13.37 -0.04 36.94
MSCI Italy 23.28 -15.01 26.57 -49.98 6.06 32.49 1.90 32.49 -10.86 -3.85 2.70 5.98 -0.16 35.39
MSCI Spain 22.67 -21.95 43.48 -40.60 23.95 49.36 4.41 28.93 -5.70 5.09 8.99 11.48 0.02 37.56
MSCI Ireland 20.82 -18.12 12.28 -71.92 -20.09 46.81 -2.29 43.07 -32.21 -20.98 -5.90 -1.88 -0.82 37.86
DJ UBS Precious Metals 20.59 42.66 29.20 -4.06 25.96 27.11 20.44 7.40 26.75 20.90 20.90 11.48 1.06 25.11
EURO STOXX TMI 18.82 -3.46 32.77 -47.59 18.26 37.82 9.35 21.58 -5.56 1.85 5.46 7.76 -0.02 33.10
S&P MidCap 400/Citi Pure Growth 14.35 35.16 60.34 -35.17 10.30 4.98 12.06 21.44 18.11 11.95 10.21 14.23 0.73 27.38
S&P 500/Citi Pure Value 13.43 23.06 55.21 -47.87 -3.69 20.04 13.43 26.13 7.31 3.83 8.49 10.27 0.36 37.80
S&P SmallCap 600/Citi Pure Growth 13.37 28.74 37.70 -33.10 1.49 9.79 7.10 28.72 12.61 6.24 10.60 10.31 0.53 29.76
Russell 2000 Growth 13.17 29.09 34.47 -38.54 7.05 13.35 4.15 14.31 9.62 5.14 5.59 4.85 0.46 27.51
S&P MidCap 400 12.33 26.64 37.38 -36.23 7.98 10.32 12.56 16.48 8.28 6.35 8.51 11.60 0.42 25.62
DJ Industrial Average 11.49 14.06 22.68 -31.93 8.88 19.05 1.72 5.31 2.94 5.20 4.28 8.04 0.22 19.97
S&P 500/Citi Pure Growth 11.36 27.65 50.85 -38.99 6.64 7.43 7.31 16.26 10.57 7.96 4.64 10.36 0.51 25.17
Wilshire 4500 Completion 10.91 28.43 36.99 -39.03 5.39 15.28 10.03 18.10 7.75 5.62 8.03 8.32 0.40 25.95
MSCI Kokusai (World Ex Japan) 10.80 11.37 33.14 -41.96 10.66 21.95 7.67 14.62 -0.01 3.22 4.27 7.01 0.11 24.37
Russell 2000 10.79 26.85 27.17 -33.79 -1.57 18.37 4.55 18.33 8.03 3.89 7.34 7.65 0.40 27.73
S&P 500 Equal Weighted 10.67 21.91 46.31 -39.72 1.53 15.80 8.06 16.95 7.34 5.43 7.03 9.57 0.38 26.75
MSCI EAFE Value 10.66 3.25 34.23 -44.09 5.96 30.38 13.80 24.33 -3.60 0.55 5.76 6.15 0.00 28.15
S&P SmallCap 600 10.51 26.31 25.57 -31.07 -0.30 15.12 7.68 22.65 7.87 4.21 8.68 9.51 0.40 27.48
Russell 3000 Growth 9.88 17.64 37.01 -38.44 11.40 9.46 5.17 6.93 4.95 5.05 2.38 5.68 0.31 22.17
Dow Jones Composite Average 9.81 16.22 19.35 -27.94 8.88 15.71 9.49 15.58 2.49 5.31 5.57 8.46 0.20 20.29
Russell 1000 Growth 9.58 16.71 37.21 -38.44 11.81 9.07 5.26 6.30 4.55 5.06 2.11 5.82 0.30 21.84
Russell 3000 9.55 16.93 28.34 -37.31 5.14 15.72 6.12 11.95 2.75 3.33 3.64 7.14 0.22 22.56
MSCI EAFE 9.54 7.75 31.78 -43.38 11.17 26.34 13.54 20.25 -2.85 1.54 5.29 4.94 0.01 26.23
Alerian MLP 9.50 35.85 76.41 -36.91 12.72 26.07 6.32 16.67 18.51 16.94 16.43 17.09 0.84 23.03
Russell 1000 9.44 16.10 28.43 -37.60 5.77 15.46 6.27 11.40 2.30 3.30 3.34 7.16 0.20 22.22
Russell 1000 Value 9.29 15.51 19.69 -36.85 -0.17 22.25 7.05 16.49 -0.11 1.40 4.31 7.84 0.10 23.27
Russell 3000 Value 9.21 16.23 19.76 -36.25 -1.01 22.34 6.85 16.94 0.39 1.47 4.63 7.95 0.12 23.59
S&P 500 9.06 15.06 26.46 -37.00 5.49 15.79 4.91 10.88 1.73 2.95 2.82 6.91 0.17 21.78
MSCI AC World 8.69 12.67 34.63 -42.20 11.66 20.95 10.84 15.23 -0.17 3.09 4.72 - 0.10 24.32
NASDAQ 100 8.59 20.14 54.61 -41.57 19.24 7.28 1.89 10.75 8.56 7.80 3.05 - 0.44 24.71
MSCI EAFE Growth 8.47 12.25 29.36 -42.70 16.45 22.33 13.28 16.12 -2.16 2.44 4.73 3.58 0.02 24.91
Russell Micro Cap 8.42 28.89 27.48 -39.78 -8.00 16.54 2.57 14.14 6.25 0.27 7.48 - 0.34 29.05
Dow Jones Transportation Avg 8.42 26.74 18.58 -21.41 1.43 9.81 11.65 27.73 4.11 5.06 8.38 7.75 0.27 27.74
MSCI EAFE Small Cap 8.39 22.04 46.78 -47.01 1.45 19.31 26.19 30.78 2.36 1.54 10.21 - 0.21 28.71
Russell 2000 Value 8.33 24.50 20.58 -28.92 -9.78 23.48 4.71 22.25 6.23 2.50 8.69 9.87 0.34 28.59
DJ UBS Commodity 8.06 16.83 18.91 -35.65 16.23 2.07 21.36 9.15 -5.23 1.92 7.06 6.01 -0.13 23.39
S&P MidCap 400/Citi Pure Value 7.79 23.19 59.18 -42.58 -3.20 19.31 9.37 20.85 7.42 5.25 10.46 11.26 0.37 38.23
Dow Jones Utilities Average 7.24 6.46 12.47 -27.84 20.11 16.63 25.14 30.24 -1.40 5.55 4.79 9.09 -0.03 16.23
Barclays Global High Yield 6.83 14.82 59.40 -26.89 3.18 13.69 3.59 13.17 12.16 9.93 10.36 9.18 0.71 17.91
Barclays US Corporate High Yield 5.49 15.12 58.21 -26.16 1.87 11.85 2.74 11.13 11.93 9.32 8.93 7.57 0.72 17.06
S&P/IFCI Composite 5.25 20.64 81.03 -53.74 40.28 35.11 35.19 28.11 3.59 10.63 18.19 9.64 0.26 31.94
MSCI EM 5.21 18.88 78.51 -53.33 39.39 32.17 34.00 25.55 2.69 9.85 16.58 - 0.23 31.66
Barclays US Treasury US TIPS 4.65 6.31 11.41 -2.35 11.64 0.41 2.84 8.46 5.54 6.79 6.95 - 0.62 8.57
S&P SmallCap 600/Citi Pure Value 4.51 29.18 63.58 -41.73 -18.61 21.44 11.58 22.72 10.58 2.18 10.98 10.91 0.42 48.78
Barclays Global Aggregate 4.38 5.54 6.93 4.79 9.48 6.64 -4.49 9.27 5.68 7.20 7.36 6.23 0.68 7.90
MSCI BRIC 3.50 9.57 93.12 -59.40 58.87 56.36 44.19 16.89 -1.66 10.83 18.97 - 0.11 33.91
JPM EMBI Global 2.42 12.04 28.18 -10.91 6.28 9.88 10.73 11.73 8.83 8.58 10.36 10.91 0.70 12.77
Barclays Municipal 2.31 2.38 12.91 -2.47 3.36 4.84 3.51 4.48 4.68 4.52 4.96 5.43 0.77 5.57
Barclays US Aggregate Bond 1.70 6.54 5.93 5.24 6.97 4.33 2.43 4.34 5.81 6.33 5.74 6.33 1.27 4.18
MSCI EM Small 1.66 27.17 113.79 -58.23 42.26 32.35 29.17 24.74 8.50 12.77 18.62 6.31 0.40 36.05
Barclays US Government 1.00 5.52 -2.20 12.39 8.66 3.48 2.65 3.48 4.52 5.92 5.37 6.05 0.85 4.87
Barclays US Treasury 1-3 Yr 0.46 2.40 0.80 6.67 7.31 3.92 1.62 0.91 2.69 4.15 3.68 4.60 1.66 1.39
Barclays US Treasury 20+ Yr 0.36 9.38 -21.40 33.72 10.15 0.93 8.57 8.99 4.49 6.73 6.72 7.47 0.31 17.80
S&P/TOPIX 150 -5.24 13.71 7.37 -29.18 -5.23 8.80 26.44 12.53 -6.97 -5.33 0.43 -0.56 -0.25 21.07
Citigroup Greek GBI Hedged* -10.99 -20.03 3.77 0.26 3.52 2.22 6.06 6.75 -9.85 -4.40 0.50 - -0.59 15.89
MSCI Peru* -19.12 49.24 69.30 -42.40 86.00 52.13 28.51 -0.22 2.51 21.24 27.85 12.81 0.27 42.41
MSCI Egypt* -29.89 9.47 32.77 -53.92 54.85 14.84 154.49 118.78 -25.38 -4.72 17.77 12.73 -0.54 39.30
Source: Morningstar. (Nasdaq-100 index data provided by Morningstar and Nasdaq OMX.) Data as of April 30, 2011. All returns are in US dollars, unless noted. YTD is year-to-date. 3-, 5-, 10- and 15-year
returns are annualized. Sharpe is 12-month Sharpe ratio. Std Dev is 3-year standard deviation. *Indicates price returns. All other indexes are total return.
www.journalofindexes.com
July / August 2011 59

Index Funds
Largest U.S. Index Mutual Funds Sorted By Total Net Assets In $US Millions
July/August 2011
Total Return % Annualized Return %
Fund Name Ticker Assets Exp Ratio 3-Mo YTD 2010 2009 3-Yr 5-Yr 10-Yr 15-Yr P/E Std Dev Yield
Vanguard Total Stock Mkt, Inv Shrs VTSMX 63,493.9 0.18 7.18 9.52 17.09 28.70 3.02 3.51 3.93 7.09 14.7 22.49 1.60
Vanguard Institutional, Inst Shrs VINIX 60,369.0 0.05 6.52 9.04 15.05 26.63 1.79 2.98 2.84 6.95 15.5 21.77 1.76
Vanguard 500 Admiral Class VFIAX 56,098.0 0.07 6.52 9.04 15.05 26.62 1.78 2.97 2.81 6.89 15.5 21.78 1.72
Vanguard Total Stock Mkt, Adm Shrs VTSAX 53,201.7 0.07 7.20 9.55 17.26 28.83 3.13 3.62 4.02 7.15 14.7 22.52 1.69
Vanguard Institutional, Inst+ Shrs VIIIX 38,581.5 0.02 6.53 9.06 15.07 26.66 1.82 3.01 2.87 6.98 15.5 21.78 1.78
Vanguard Total Intl Stock, Inv Shrs VGTSX 35,783.0 0.26 7.62 8.38 11.12 36.73 -1.54 3.19 6.70 5.60 14.4 28.04 1.46
Vanguard 500 Investor Class VFINX 33,007.1 0.18 6.49 9.00 14.91 26.49 1.68 2.87 2.72 6.83 15.5 21.78 1.62
Vanguard Total Bond Mkt II, Inv Shrs VTBIX 31,474.0 0.12 1.52 1.58 6.41 - - - - - - - 3.12
Fidelity Spartan 500 Investor Class FUSEX 28,457.6 0.10 6.50 9.04 14.98 26.51 1.70 2.90 2.74 6.78 16.1 21.79 1.67
Vanguard Total Bond Mkt, Adm Shrs VBTLX 27,885.8 0.11 1.50 1.60 6.54 6.04 5.83 6.35 5.54 6.17 - 4.21 3.39
Vanguard Total Stock Mkt, Inst Shrs VITSX 26,898.9 0.06 7.17 9.55 17.23 28.83 3.14 3.63 4.05 7.20 14.7 22.50 1.70
Vanguard 500 Signal Class VIFSX 22,225.9 0.07 6.52 9.04 15.05 26.61 1.78 2.96 2.76 6.86 15.5 21.78 1.72
Vanguard Total Bond Mkt, Inst Shrs VBTIX 20,792.0 0.07 1.51 1.61 6.58 6.09 5.88 6.39 5.59 6.24 - 4.22 3.43
Fidelity Spartan 500, Adv Cl FUSVX 16,313.8 0.07 6.51 9.05 15.01 26.55 1.73 2.93 2.75 6.79 16.1 21.78 1.70
Vanguard Total Intl Stock, Adm Shrs VTIAX 15,313.2 0.20 7.65 8.43 11.04 36.73 -1.55 3.19 6.69 5.60 14.4 28.03 -
Vanguard Total Stock Mkt, Inst+ Shrs VITPX 14,366.2 0.02 7.19 9.55 17.25 28.92 3.19 3.69 - - 14.7 22.53 1.66
T. Rowe Price Equity 500 PREIX 13,900.8 0.30 6.48 8.99 14.71 26.33 1.57 2.72 2.57 6.63 16.1 21.75 1.50
Vanguard Total Bond Mkt, Inv Shrs VBMFX 13,083.0 0.22 1.48 1.56 6.42 5.93 5.73 6.24 5.45 6.11 - 4.21 3.28
Schwab S&P 500 SWPPX 11,758.1 0.09 6.49 8.99 14.97 26.25 1.82 2.96 2.76 - 15.7 21.70 1.68
Vanguard Total Bond Mkt II, Inst Shrs VTBNX 11,728.4 0.07 1.54 1.60 6.47 - - - - - - - 3.17
Spartan US Bond, Inv Cl FBIDX 10,547.2 0.22 1.56 1.72 6.29 6.45 5.53 5.74 5.51 6.14 - 3.92 2.91
Vanguard Total Bond Mkt, Sig Shrs VBTSX 9,619.5 0.11 1.50 1.60 6.54 6.04 5.83 6.34 5.50 6.14 - 4.21 3.39
Vanguard Emrg Mkts Stock, Adm Shrs VEMAX 8,124.5 0.22 8.33 5.37 18.99 76.18 2.53 9.54 16.08 8.96 14.8 32.56 1.55
Vanguard Total Bond Mkt, Inst+ Shrs VBMPX 7,782.8 0.05 1.52 1.62 6.57 5.93 5.80 6.29 5.47 6.13 - 4.21 3.45
Vanguard Mid-Cap, Inst Shrs VMCIX 7,713.2 0.08 8.76 11.21 25.67 40.51 6.20 4.92 8.17 - 16.6 25.97 1.10
Vanguard Short-Term Bond, Sig Shrs VBSSX 7,503.0 0.11 0.68 1.05 4.03 4.38 4.25 5.20 4.41 5.18 - 2.32 2.15
Fidelity Spartan Intl, Inv Cl FSIIX 6,950.6 0.10 7.35 9.91 7.70 28.48 -2.70 1.67 5.19 - 13.6 27.43 2.28
Vanguard Mid Cap, Adm Shrs VIMAX 6,915.1 0.14 8.71 11.19 25.59 40.48 6.13 4.87 8.11 - 16.6 25.97 1.03
Fidelity Series 100 FOHIX 6,698.5 0.20 5.59 8.12 12.39 22.14 0.62 - - - 15.3 20.72 1.80
Vanguard Total Stock Mkt, Sig Shrs VTSSX 6,496.0 0.07 7.19 9.55 17.23 28.85 3.13 3.61 3.98 7.12 14.7 22.49 1.69
Vanguard Extended Mkt, Inst Shrs VIEIX 6,453.9 0.08 9.99 11.56 27.59 37.69 8.01 5.49 8.08 8.54 18.3 26.92 0.93
Vanguard Small-Cap, Adm Shrs VSMAX 6,411.8 0.14 11.10 12.06 27.89 36.33 9.27 5.48 8.49 8.73 17.8 28.49 1.00
Vanguard Small-Cap, Inst Shrs VSCIX 6,297.8 0.08 11.10 12.09 27.95 36.40 9.33 5.53 8.55 8.80 17.8 28.50 1.06
Vanguard Total Intl Stock, Inst Shrs VTSNX 6,072.2 0.15 7.67 8.43 11.09 36.73 -1.53 3.20 6.70 5.60 14.4 28.04 -
Vanguard Extended Mkt, Adm Shrs VEXAX 5,871.3 0.13 9.96 11.53 27.57 37.65 7.96 5.45 8.02 8.46 18.3 26.91 0.86
Fidelity Spartan Total Mkt, Inv Cl FSTMX 5,833.0 0.10 7.14 9.47 17.41 28.39 2.95 3.50 3.94 - 16.5 22.43 1.52
Vanguard Mid Capitalization, Inv Shrs VIMSX 5,705.0 0.27 8.68 11.14 25.46 40.22 6.01 4.75 8.01 - 16.6 25.96 0.95
Vanguard Small Capitalization, Inv Shrs NAESX 5,552.1 0.28 11.05 12.01 27.72 36.12 9.12 5.35 8.37 8.65 17.8 28.49 0.92
Vanguard Small Cap Growth, Inv Shrs VISGX 5,351.8 0.28 13.33 14.52 30.69 41.85 10.63 6.65 9.48 - 20.6 28.51 0.31
Vanguard Developed Mkts, Inst Shrs VIDMX 5,289.0 0.07 7.35 9.72 8.73 28.17 -2.53 1.76 5.27 - 13.8 27.42 2.66
Fidelity Spartan Total Mkt, Adv Cl FSTVX 5,288.5 0.07 7.15 9.48 17.44 28.43 2.98 3.54 3.96 - 16.5 22.42 1.55
Vanguard REIT, Adm Shrs VGSLX 5,279.0 0.13 8.97 12.57 28.49 29.76 3.01 3.85 11.78 - 41.8 39.84 3.12
Schwab 1000 SNXFX 5,119.1 0.29 6.81 9.31 15.96 27.68 2.25 3.19 3.19 6.93 16.0 21.92 1.40
Vanguard Growth, Adm Shrs VIGAX 5,107.9 0.14 6.22 8.23 17.12 36.42 3.89 4.93 3.30 7.14 18.5 21.85 1.09
Fidelity Spartan Extd Mkt, Inv Cl FSEMX 4,822.1 0.10 9.76 11.08 28.58 36.65 8.04 5.84 8.07 - 18.4 26.03 0.95
Vanguard Small Cap Value, Inv Shrs VISVX 4,726.7 0.28 8.77 9.44 24.82 30.34 7.41 3.82 8.38 - 15.7 29.21 1.64
)LGHOLW\6HULHV,QüDWLRQ3URWHFWHG%RQG FSIPX 4,646.0 0.20 3.25 4.35 5.06 - - - - - - - 0.32
Vanguard Intermediate Bond, Adm Shrs VBILX 4,565.2 0.11 1.79 2.13 9.49 6.89 7.03 7.44 6.50 6.85 - 7.06 3.97
Vanguard FTSE All-World ex-US, Inst Shrs VFWSX 4,562.3 0.15 7.79 8.65 11.93 39.01 -0.74 - - - 14.3 28.39 2.03
Vanguard Growth, Inst Shrs VIGIX 4,456.6 0.08 6.23 8.24 17.17 36.50 3.94 4.97 3.34 7.19 18.5 21.84 1.13
Vanguard Balanced, Adm Shrs VBIAX 4,228.9 0.12 4.95 6.37 13.29 20.11 4.82 5.14 5.04 7.19 14.7 13.95 2.26
Vanguard Short-Term Bond, Inv Shrs VBISX 3,932.1 0.22 0.65 1.01 3.92 4.28 4.14 5.12 4.37 5.16 - 2.32 2.04
Vanguard Growth, Inv Shrs VIGRX 3,855.4 0.28 6.17 8.16 16.96 36.29 3.74 4.79 3.19 7.06 18.5 21.82 0.96
Vanguard Balanced, Inst Shrs VBAIX 3,829.3 0.08 4.95 6.38 13.34 20.18 4.87 5.19 5.08 7.22 14.7 13.96 2.29
Vanguard Short-Term Bond, Adm Shrs VBIRX 3,811.7 0.11 0.68 1.05 4.03 4.38 4.25 5.22 4.44 5.21 - 2.32 2.15
ING U.S. Stock Class I INGIX 3,790.4 0.26 6.54 8.97 14.74 26.22 1.53 2.72 - - 15.5 21.85 1.36
Vanguard Value, Inst Shrs VIVIX 3,788.7 0.08 7.11 10.20 14.49 19.79 0.75 1.90 3.15 6.97 11.8 22.72 2.27
Vanguard Mid-Cap, Sig Shrs VMISX 3,782.3 0.14 8.72 11.19 25.62 40.43 6.14 4.87 8.12 - 16.6 25.98 1.06
ING U.S. Bond Class I ILBAX 3,758.2 0.46 1.46 1.46 6.14 5.88 5.47 - - - - 3.90 2.56
Vanguard Extended Mkt, Inv Shrs VEXMX 3,710.5 0.30 9.94 11.49 27.37 37.43 7.79 5.29 7.88 8.38 18.3 26.91 0.78
Source: Morningstar. Data as of April 30, 2011. Exp Ratio is expense ratio. 3-Mo is 3-month. YTD is year-to-date. 3-, 5-, 10- and 15-yr returns are annualized. P/E is price-to-earnings ratio.
Std Dev is 3-year standard deviation. Yield is 12-month dividend yield.
60
July / August 2011

Morningstar U.S. Style Overview Jan. 1 − April 30, 2011
Trailing Returns %
3-Month YTD 1-Yr 3-Yr 5-Yr 10-Yr
Morningstar Indexes
US Market 7.88 9.57 18.53 2.85 3.56 3.70
Large Cap 6.98 8.74 16.45 1.15 2.91 2.18
Mid Cap 9.91 11.84 24.02 6.30 5.04 7.43
Small Cap 11.33 11.54 24.21 10.04 5.25 8.54
Morningstar Market Barometer YTD Return %
US Market
9.57
Value
10.74
Core
9.45
Growth
8.53
US Value 8.45 10.74 18.61 0.78 1.78 5.08
US Core 7.82 9.45 17.42 4.02 4.57 4.69
Large Cap
8.74
11.13 8.35 6.73
US Growth 7.38 8.53 19.84 3.48 4.01 0.61
Large Value 8.68 11.13 19.32 –1.74 0.81 3.62
Large Core 6.68 8.35 14.38 2.41 4.07 3.06
Mid Cap
11.84
10.01 12.38 12.97
Large Growth 5.55 6.73 16.02 2.40 3.46 –1.01
Mid Value 7.80 10.01 16.59 6.86 3.71 8.33
Mid Core 10.38 12.38 26.45 7.08 5.63 8.94
Mid Growth 11.41 12.97 29.05 4.86 5.49 4.50
Small Cap
11.54
8.80 12.56 13.09
Small Value 7.91 8.80 17.13 10.34 5.53 11.04
Small Core 12.35 12.56 23.90 9.66 4.94 9.74
Small Growth 13.62 13.09 31.90 9.90 4.90 4.65
–8.00 –4.00 0.00 +4.00 +8.00
Sector Index YTD Return %
Energy 19.31
Healthcare 13.05
Industry Leaders & Laggards YTD Return %
Rubber & Plastics 34.86
Broadcasting - TV 32.66
Biggest Influence on Style Index Performance
Best Performing Index
YTD
Return %
Small Growth 13.09
Constituent
Weight %
Real Estate 13.05
Industrials 11.55
Communication 9.61
Basic Materials 9.51
Consumer Cyclical 9.07
Consumer 7.77
Utilities 7.56
Technology 6.97
Financial Services 2.31
1-Year
Personal Services 27.44
Real Estate Services 26.29
Utilities - Independent Power 25.56
Oil & Gas Refining & 25.49
–7.55 Copper
–7.78 Gambling
–8.15 Insurance - Diversified
–8.42 Pollution & Treatment Controls
–9.15 Auto Manufacturers
–9.84 Airlines
3-Year
Acme Packet Inc. 55.40 0.94
CARBO Ceramics Inc. 55.90 0.72
Aruba Networks Inc. 72.03 0.53
Ariba Inc. 48.02 0.73
IPG Photonics Corp. 119.67 0.29
Worst Performing Index
Large Growth 6.73
Apple Inc. 8.55 10.07
Oracle Corp. 15.28 4.08
Qualcomm Inc. 15.74 2.70
EMC Corp. 23.76 1.59
Comcast Corp. Cl A 20.34 1.54
5-Year
Value
Core
Growth
Value
Core
Growth
Value
Core
Growth
Large Cap
19.32
14.38
16.02
Large Cap
–1.74
2.41
2.40
Large Cap
0.81
4.07
3.46
Mid Cap
16.59
26.45 29.05
Mid Cap
6.86
7.08 4.86
Mid Cap
3.71
5.63 5.49
Small Cap
17.13
23.90 31.90
Small Cap
10.34
9.66 9.90
Small Cap
5.53
4.94 4.90
–20 –10 0 +10 +20
–20 –10 0 +10 +20
–20 –10 0 +10 +20
Source: Morningstar. Data as of April 30, 2011.
Notes and Disclaimer: ©2011 Morningstar, Inc. All Rights Reserved. Unless otherwise noted, all data is as of most recent month end. Multi-year returns are annualized. NA: Not Available. Biggest Influence on Index Performance lists
are calculated by multiplying stock returns for the period by their respective weights in the index as of the start of the period. Sector and Industry Indexes are based on Morningstar's proprietary sector classifications. The information ?
contained herein is not warranted to be accurate, complete or timely. Neither Morningstar nor its content providers are responsible for any damages or losses arising from any use of this information.
www.journalofindexes.com
July / August 2011
61

Dow Jones U.S. Industry Review
Dow Jones U.S. Industry Review
Performance
Index Name Weight 1-Month 3-Month YTD 1-Year 3-Year 5-Year 10-Year
Dow Jones U.S. Index 100.00% 3.00% 6.96% 9.46% 18.40% 2.79% 3.56% 3.64%
Dow Jones U.S. Basic Materials Index 3.93% 2.87% 9.17% 8.95% 33.76% 3.86% 9.75% 10.34%
Dow Jones U.S. Consumer Goods Index 10.05% 4.55% 9.67% 7.87% 20.66% 7.70% 7.81% 7.80%
Dow Jones U.S. Consumer Services Index 11.84% 4.24% 9.13% 9.19% 18.11% 8.66% 5.05% 3.01%
Dow Jones U.S. Financials Index 16.04% 0.77% 1.54% 4.07% 3.84% -9.70% -9.10% -0.73%
Dow Jones U.S. Health Care Index 10.59% 6.56% 12.56% 13.22% 17.08% 7.17% 5.52% 3.35%
Dow Jones U.S. Industrials Index 13.14% 2.68% 7.51% 12.12% 22.40% 3.48% 4.68% 4.70%
Dow Jones U.S. Oil & Gas Index 12.20% 1.21% 10.30% 18.59% 35.17% 0.92% 9.11% 11.19%
Dow Jones U.S. Technology Index 15.87% 2.82% 2.26% 6.39% 15.19% 7.56% 6.53% 1.62%
Dow Jones U.S. Telecommunications Index 2.86% 1.90% 9.65% 6.86% 30.34% 0.95% 4.35% -0.51%
Dow Jones U.S. Utilities Index 3.49% 3.89% 6.39% 8.02% 15.68% -1.48% 5.22% 3.37%
Risk-Return
15%
3-Year Annualized Return
10%
5%
0%
-5%
-10%
Consumer Goods
Health Care
Telecommunications
Utilities
Composite
Consumer Services
Technology
Oil & Gas
Industrials
Basic Materials
Financials
-15%
14% 16% 18% 20% 22% 24% 26% 28% 30% 32% 34% 36%
3-Year Annualized Risk
Industry Weights Relative to Global ex-U.S.
Basic Materials
-8.82%
Asset Class Performance
U.S. [108.61] Global ex-U.S. [98.78] Commodities [85.11]
REITs [104.26] Infrastructure [112.95]
Consumer Goods
-2.31%
120
Consumer Services
4.83%
110
Financials
-8.05%
100
Health Care
5.17%
90
Industrials
-0.54%
80
Oil & Gas
Technology
Telecommunications
-2.05%
1.36%
10.97%
70
60
50
40
Utilities
-0.57%
30
-15% -10% -5% 0% 5% 10% 15%
Underweight Overweight
20
4/08 7/08 10/08 1/09 4/09 7/09 10/09 1/10 4/10 7/10 10/10 1/11 4/11
Chart compares industry weights within the Dow Jones U.S. Index to industry weights within the Dow Jones U.S. = Dow Jones U.S. Index | Global ex-U.S. = Dow Jones Global ex-U.S. Index
Global ex-U.S. Index
Commodities = Dow Jones-UBS Commodity Index | REITs = Dow Jones U.S. Select REIT Index
Infrastructure = Dow Jones Brookfield Global Infrastructure Index
© CME Group Index Services LLC 2011. All rights reserved. The "Dow Jones U.S. Index" and "Dow Jones U.S. Industry Indexes" referenced in this piece are products of Dow Jones Indexes, the marketing name and a licensed trademark of CME Group Index Services LLC (“CME Indexes”). “Dow
Jones®”, “Dow Jones Indexes” and the names identifying the Dow Jones Indexes referenced herein are service marks of Dow Jones Trademark Holdings, LLC (“Dow Jones”), and have been licensed for use by CME Indexes. “CME” is a trademark of Chicago Mercantile Exchange Inc.
The Dow Jones U.S. Index and the Dow Jones U.S. Industry Indexes were first published in February 2000. To the extent this document includes information for the index for the period prior to its initial publication date, such information is back-tested (i.e., calculations of how the index might have
performed during that time period if the index had existed). Any comparisons, assertions and conclusions regarding the performance of the Index during the time period prior to launch will be based on back-testing. Back-tested information is purely hypotheticaland is provided solely for informational
purposes. Back-tested performance does not represent actual performance and should not be interpreted as an indication of actual performance. Past performance is also not indicative of future results.
All information in these materials is provided “as is”. CME Indexes and its affiliates do not make any representationregarding the accuracy or completeness of these materials, the content of which may change without notice, and each of CME Indexes and its affiliates disclaim liability related to these
materials. All information provided by CME Indexes is impersonal and not tailored to the needs of any person, entity or group of persons. Dow Jones, its affiliates and CME Indexes do not sponsor, endorse, sell, promote or manage any investment fund or other vehicle that is offered by third parties
and that seeks to providean investmentreturn based on the returns of any index. CME Indexes is not an investmentadvisor, and CME Indexes makes no representationregarding the advisabilityof investing in any investment fund or other vehicle. Inclusion of a security or instrument in an index is not a
recommendationby Dow Jones, CME Indexes or their affiliates to buy, sell, or hold such security or instrument, nor is it considered to be investmentadvice. Exposure to an asset class is availablethrough investableinstruments based on an index. It is not possible to invest directly in an index. There is
no assurance that investment products based on the index will accurately track index performance or provide positive investment returns.
Data as of April 30, 2011
Source: Dow Jones Indexes Analytics & Research
For more information, please visit the Dow Jones Indexes Web site at www.djindexes.com.
62
July / August 2011

Exchange-Traded Funds Corner
Largest New ETFs Sorted By Total Net Assets In $US Millions
Covers ETFs and ETNs launched during the 12-month period ended April 30, 2011.
Fund Name Ticker ER 1-Mo 3-Mo YTD Inception Assets
Vanguard S&P 500 VOO 0.06 2.94 6.50 8.87 9/7/2010 1,233.7
Alerian MLP AMLP 0.85 2.14 4.04 5.53 8/25/2010 1,075.0
WisdomTree Emrg Mkts Local Debt ELD 0.55 4.52 8.16 5.35 8/9/2010 952.7
Market Vectors Rare Earth REMX 0.57 5.25 18.49 15.33 10/27/2010 525.4
United States Commodity USCI 1.24 1.42 6.58 10.98 8/10/2010 509.2
Market Vectors EM Lcl Currency Bond EMLC 0.49 4.29 8.04 6.11 7/22/2010 349.5
ETFS Physical Precious Metal GLTR 0.6 16.50 35.03 26.33 10/22/2010 289.3
Global X Uranium URA 0.69 -3.70 -31.48 -30.14 11/4/2010 267.2
iShares MSCI Poland EPOL 0.61 10.67 16.43 17.95 5/25/2010 255.9
WisdomTree Asia Local Debt ALD 0.55 2.93 - - 3/16/2011 240.2
EGShares DJ EM Consumer Titans ECON 0.85 6.04 13.82 3.91 9/14/2010 205.9
iShares MSCI Indonesia EIDO 0.61 3.35 18.97 6.01 5/5/2010 197.0
Global X Lithium LIT 0.75 4.16 2.77 -1.41 7/23/2010 187.9
SPDR Global Natural Resources GNR 0.4 2.01 6.48 8.22 9/13/2010 175.4
Schwab U.S. TIPS SCHP 0.14 2.49 4.36 4.36 8/5/2010 167.9
Cambria Global Tactical GTAA 0.99 3.59 5.93 6.26 10/25/2010 164.0
Vanguard Global ex-US Real Estate VNQI 0.35 4.47 5.53 4.45 11/1/2010 152.5
WisdomTree Commodity Currency CCX 0.55 4.54 8.34 6.93 9/24/2010 142.8
iShares MSCI Russia ERUS 0.65 1.14 12.32 17.28 11/9/2010 129.5
Vanguard Total Intl Stock VXUS 0.2 1.41 3.51 - 1/26/2011 128.1
Source: Morningstar. Data as of April 30, 2011. ER is expense ratio. 1-Mo is 1-month. 3-Mo is 3-month. YTD is year-to-date.
Selected ETFs In Registration
Accuvest Global Opportunities
Alerian Plus MLP Infrastructure
DBX MSCI EAFE Currency-Hedged Eq
EG Shares EM Food/Agriculture
ETS Offshore RMB Bond
First Trust NA Energy Infrastructure
FlexShares US TIPS Portfolio
Global X Fertilizers/Potash
Grail Western Asset Enh Liquidity
Guggenheim Small-Mid Cap BRIC
Huntington Ecological Strategy
IndiaShares Financial Shares
IQ Canada Mid Cap
iShares FTSE China A50 Index
Market Vectors Mortgage REIT
Pimco Total Return
PowerShares Convertible
Russell 1000 Low Beta
Schwab U.S. Aggregate Bond
WisdomTree EMEA Bond
Source: IndexUniverse.com’s ETF Watch
Largest U.S.-listed ETFs Sorted By Total Net Assets In $US Millions
Total Return % Annualized Return %
Fund Name Ticker Exp Ratio Assets 3-Mo YTD 2010 2009 3-Yr 5-Yr Mkt Cap P/E Std Dev Yield
SPDR S&P 500 SPY 0.09 95,309.4 6.45 8.92 15.02 26.31 1.77 2.84 49,839 16.1 21.68 1.71
SPDR Gold GLD 0.40 60,684.0 17.33 9.84 29.27 24.03 20.70 18.54 - - 20.88 -
Vanguard MSCI Emerging Mkts VWO 0.22 49,347.5 8.84 5.10 19.45 76.26 2.41 9.38 20,507 14.8 32.13 1.61
iShares MSCI Emerging Mkts EEM 0.69 41,670.3 9.15 4.95 16.54 68.82 2.64 9.09 20,489 14.2 32.41 1.30
iShares MSCI EAFE EFA 0.35 41,435.7 6.76 9.00 8.25 26.88 -2.95 1.31 31,579 13.8 27.70 2.20
iShares S&P 500 IVV 0.09 28,473.6 6.51 8.96 15.11 26.61 1.75 2.87 49,836 16.1 21.71 1.71
PowerShares QQQ QQQ 0.20 27,202.8 5.65 8.64 19.89 54.67 8.37 7.64 50,067 19.2 24.77 0.65
iShares Barclays TIPS Bond TIP 0.20 20,935.5 4.35 4.36 6.13 8.95 5.29 6.65 - - 8.71 2.75
Vanguard Total Stock Market VTI 0.07 20,299.8 7.14 9.34 17.45 28.87 3.13 3.59 26,218 14.7 22.48 1.69
iShares Russell 2000 IWM 0.28 18,697.5 11.05 10.64 26.9 28.53 8.05 3.82 1,130 18.4 27.26 1.03
iShares Silver SLV 0.50 17,302.0 71.14 55.33 82.48 47.67 41.01 27.69 - - 39.15 -
iShares Russell 1000 Growth IWF 0.20 13,850.8 6.83 9.42 16.48 36.73 4.33 4.82 40,426 17.9 21.84 1.21
iShares iBoxx $ Inv Gr Corp Bond LQD 0.15 13,387.5 3.06 3.10 9.33 8.58 6.94 6.63 - - 12.31 4.74
iShares MSCI Brazil EWZ 0.61 13,190.2 6.17 0.42 7.69 121.5 -0.81 15.59 30,763 11.1 39.06 3.66
iShares Russell 1000 Value IWD 0.20 12,102.6 6.77 9.09 15.44 19.23 -0.20 1.27 34,793 14.9 23.20 1.88
SPDR S&P MidCap 400 MDY 0.25 12,100.0 10.05 12.17 26.26 37.52 7.94 5.98 3,584 20.1 25.26 0.84
iShares S&P 400 MidCap IJH 0.22 12,034.9 10.06 12.05 26.73 37.81 8.20 6.16 3,559 20.1 25.27 0.97
iShares Barclays Aggregate Bond AGG 0.24 11,264.6 1.64 1.55 6.37 3.01 5.37 6.06 - - 5.47 3.41
Energy Select SPDR XLE 0.20 10,449.2 10.37 18.29 21.81 21.81 1.22 8.72 62,741 16.9 26.70 1.30
SPDR DJIA DIA 0.18 10,357.5 8.42 11.34 13.97 22.72 2.79 5.01 109,422 14.9 19.80 2.33
Vanguard Total Bond Market BND 0.11 9,547.0 1.62 1.70 6.2 3.67 5.67 - - - 4.99 3.36
Vanguard REIT VNQ 0.13 9,295.8 8.91 12.45 28.43 30.07 2.80 3.65 5,584 41.8 39.62 3.12
iShares iBoxx $ HiYld Corp Bond HYG 0.50 8,808.2 3.10 4.81 11.96 28.86 7.48 - - - 19.25 7.84
iShares Barclays 1-3 Yr Treasury SHY 0.15 8,345.5 0.28 0.41 2.28 0.36 2.48 4.03 - - 1.43 0.98
iShares FTSE/Xinhua China 25 FXI 0.72 8,235.1 6.25 4.92 3.51 47.28 -3.56 13.17 84,089 11.6 31.49 1.40
Source: Morningstar. Data as of April 30, 2011. Exp Ratio is expense ratio. 3-Mo is 3-month. YTD is year-to-date. 3-Yr and 5-Yr are 3-year and 5-year annualized returns, respectively.
Mkt Cap is geometric average market capitalization. P/E is price-to-earnings ratio. Std Dev is 3-year standard deviation. Yield is 12-month.
www.journalofindexes.com July / August 2011
63

Test Your Skills
A History Of Money
How much do
you know about
money matters?
ACROSS
7. Sea snail shell, used for
centuries as commodity
money in Africa
8. Old Spanish coin, worth a
quarter of a peseta in 1868
9. Currency of monetary
union currently under
strain
11. Ancient unit of mass and
value, mentioned in the
New Testament
12. Natural gold and silver
alloy used by the ancient
Greeks to make coins
13. Leading index provider
15. 100 stotinki make one
of these, in Bulgaria
16. Country that was one
of the earliest issuers of
coins, circa 6th
century BC
19. English gold coins
minted from 1663
to 1813
20. & 3 Down Central banking
system of the United
States, created in 1813
23. ___ Sea Bubble,
economic catastrophe
of 1720
25. ___ stones, thought to be
used as currency on the
island of Yap
26. Money in feudal Japan
was based on this
commodity
28. Bill ___ ___, banknotelike
document,
referred to in the U.S.
Constitution
30. Metal often alloyed with
nickel to coat coins
32. Financial district of New
York City, _ Street
1
2 3 4 5
7 8 9
10
11 12
13 14 15 16
19
23
28 29
24
27
32 33
33. Coin material with
atomic number 26
34. ___ sticks, measuring rods
used in medieval Europe for
tax collection
DOWN
1. Concluding passage of music
2. Nationality of those using the
dram as currency
3. See 20 Across
4. Woody ___, director of “Take
the Money and Run”
5. See 17 Down
6. Common language spoken by
some rupee users
10. Main nationality of 14 Down
14. Silver coin whose name
derives from the Latin
scutum, meaning “shield”
22
25
20
18
30
34
21
26
17
31
17. & 5 Down Scientist who
became warden of the Royal
Mint in 1696
18. Enchant, cast a spell over
21. ___ Central Bank, launched
9 Across in 1999
22. ___ Woods, location of the
1944 conference that
established the IMF
24. Creature stamped on the
oldest example of a coin
made from 12 Across
27. ___ Izzard, comedian
who starred in U.S. series
“The Riches”
29. ___ money, has value only
because of government
regulation or law
31. Ms. Fitzgerald, recorded the
song “I’ve Got Five Dollars”
6
Solutions
ACROSS: 7. Cowry; 8. Real; 9. Euro; 11. Talent; 12. Electrum; 13. MSCI; 15. Lev; 16. India; 19. Guineas;
20. Federal; 23. South; 25. Rai; 26. Rice; 28. Of Credit; 30. Copper; 32. Wall; 33. Iron; 34. Tally
DOWN: 1. Coda; 2. Armenian; 3. Reserve; 4. Allen; 5. Newton; 6. Urdu; 10. Italian; 14. Scudo; 17. Isaac;
18. Bewitch; 21. European; 22. Bretton; 24. Turtle; 27. Admit; 29. Fiat; 31. Ella
64
July / August 2011

InsideIndexing
inaugural
conference
BUIlDIng Better BetA 2011
For more InFormAtIon:
www.InsideIndexingConference.com/JOI
From the producers of: InsideETFs InsideETFsEurope InsideCommodities
October 17-18, 2011
the ritz-carlton • philadelphia, pa
Designed specifically for InstItutIonal Investors
Featured speakers:
John C. Bogle
Founder of The Vanguard Group, Inc.,
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george F. Will
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} For speaking opportunities, please contact:
Allison Jones at 415-659-9012 or ajones@IndexUniverse.com
Presented by:
} For sponsorship opportunities, please contact:
Don Friedman at 415-659-9009 or dfriedman@IndexUniverse.com

VXUS
Vanguard Total International Stock ETF
Covers 98% of the international markets for the
broadest coverage in the industry.*
It’s the newest way to Vanguard.
Our new Total International Stock ETF contains large-, mid-, and
small-capitalization securities in developed and emerging international
markets. And with a lower expense ratio than the industry average,**
it can have a real impact on your clients’ portfolios. Take a closer look
at the Vanguard Total International Stock ETF.
Vanguard your clients’ portfolios at
advisors.vanguard.com/VXUS
All investments are subject to risk. Vanguard funds are not insured or guaranteed.
To buy or sell Vanguard ETF Shares, contact your financial advisor. Usual commissions apply. Not redeemable.
Market price may be more or less than NAV.
For more information about Vanguard ETF Shares, visit advisors.vanguard.com/VXUS, call
800-523-7895, or contact your broker to obtain a prospectus. Investment objectives, risks, charges,
expenses, and other important information are contained in the prospectus; read and consider it
carefully before investing.
Prices of mid- and small-cap stocks often fluctuate more than those of large-company stocks. Foreign investing
involves additional risks including currency fluctuations and political uncertainty. Stocks of companies in
emerging markets are generally more risky than stocks of companies in developed countries.
* Sources: Morningstar and MSCI based on holdings as of 11/30/2010. The index tracked by Vanguard Total
International Stock ETF covers 98% of the investable international stock market (by market capitalization)
and the ETF tracking an index with the next highest international stock market exposure covers 90% of the
investable international market.
** Source: Morningstar as of 9/22/2010. Based on 2010 industry average expense ratio of 0.56% for Total
International Stock ETF and expected estimated expense ratio of 0.20% for Vanguard Total International Stock ETF.
© 2011 The Vanguard Group, Inc. All rights reserved. U.S. Pat. No. 6,879,964 B2; 7,337,138. Vanguard Marketing Corporation, Distributor.

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visit www.spdrs.com. Read it carefully.
ETFs trade like stocks, fl uctuate in market value and may trade at prices above or below the ETFs net asset value. Brokerage commissions and ETF expenses
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The SPDR S&P 500 ® ETF Trust, SPDR S&P MidCap 400 ® ETF Trust and the SPDR Dow Jones Industrial Average ETF Trust are all unit investment trusts and
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“SPDR,” S&P, S&P 500 and S&P MidCap 400 are registered trademarks of Standard & Poor’s Financial Services, LLC (“S&P”) and have been licensed for use by State Street
Corporation. No fi nancial product offered by State Street or its affi liates is sponsored, endorsed, sold or promoted by S&P.
Distributor: State Street Global Markets, LLC, member FINRA, SIPC, a wholly owned subsidiary of State Street Corporation. References to State Street may include State Street
Corporation and its affiliates. Certain State Street affiliates provide services and receive fees from the SPDR ETFs. ALPS Distributors, Inc., a registered broker-dealer, is distributor
for SPDR S&P 500 ETF Trust, SPDR S&P MidCap 400 ETF Trust and SPDR Dow Jones Industrial Average ETF Trust, all unit investment trusts and the Select Sector SPDRs Trust.
IBG-3345