Redefining Credit Risk - ETF · Redefining Credit Risk By William Mast .....10 Are CDS better than...

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

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V o l . 1 4 N o . 4

1July / August 2011

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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

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

Redefining Credit RiskBy William Mast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Are CDS better than ratings when measuring bond risk?

Credit Derivatives Indexes: Methodology And UseBy Gavan Nolan and Tobias Sproehnle . . . . . . . . . . . . . . . 14How to build a credit derivatives index.

A Fixed-Income RoundtableWaqas Samad, Larry Swedroe, Ken Volpert and more . . . 20Our panel of experts digs into the bond market.

The Impact Of Fund Flows On Fixed-Income Mutual Fund Performance By David Blanchett . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Are bond fund inflows costing mutual fund investors?

Bubble Bubble, Toil And Trouble By David Blitzer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Bubbles aren’t as aberrant as you’d think.

The Importance Of Dividends And Buybacks Ratios For Gauging Equity ValuesBy Jeremy Schwartz. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Two measures speak volumes about the market.

Developed, Emerging Or Frontier Markets? By Francis Gupta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38A new perspective on classifying markets.

‘The Devil’s Invention’By Lewis Braham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44How the index fund industry began.

A History Of Money . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64How much do you think you know?

Contributors

2 July / August 2011

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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 is managing director and chairman of the Standard & Poor’s Index Committee. He has overall responsibility for security selec-tion for S&P’s indexes and index analysis and management. Blitzer previ-ously 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 econom-ics from George Washington University and his Ph.D. in economics from Columbia University.

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 is director of fixed-income indexes for Morningstar’s Index business, responsible for Morningstar’s bond-index efforts, including busi-ness 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 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, 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, 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 respon-sible for product development and strategy for fixed income and credit derivatives at Eurex. Sproehnle holds a diploma in economics and informa-tion management from the University of Würzburg, Germany.

The fund is not a mutual fund or an y o ther t ype of Inves tment C ompany wi thin the me aning o f the In ves tment

Company Act of 1940 and is not subject to its r egulation.

DB Commodity Services LLC, a wholly owned subsidiary of Deutsche Bank AG, is the managing owner of the fund. Certai n

mark eting services may be provided to the fund by Invesco Distributors, Inc. or its affiliate, Invesco PowerShares Capital

Management LL C (together, “Invesco”). Invesco will be compensated by Deutsche Bank or its affiliates. ALPS Distributors,

Inc. is the distribut or of the fund. In vesco, Deu t sche Bank and ALPS Distribut ors, Inc. are no t affiliated.

Commodity futures contracts generally are volatile and are not suitable for all investors .

An in vestor may lose all or substantially all of an investment in the fund.

To download a copy of a prospectus, visit PowerShares.com/DBApro

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Copyright © 2011 by Index Publications LLC and Charter Financial Publishing Network Inc. All rights reserved.

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Editorial BoardRolf Agather: Russell InvestmentsDavid Blitzer: Standard & Poor’s

Lisa Dallmer: NYSE EuronextHenry Fernandez: MSCI

Deborah Fuhr: BlackRockGary Gastineau: ETF Consultants

Joanne Hill: ProShare and ProFund Advisors LLCJohn Jacobs: The Nasdaq Stock Market

Mark Makepeace: FTSEKathleen Moriarty: Katten Muchin Rosenman

Don Phillips: MorningstarJohn Prestbo: Dow Jones Indexes

James Ross: State Street Global AdvisorsGus Sauter: The Vanguard Group

Steven Schoenfeld: Global Index StrategiesCliff Weber: NYSE Euronext

Review BoardJan Altmann, Sanjay Arya, Jay Baker, William

Bernstein, Herb Blank, Srikant Dash, Fred Delva, Gary Eisenreich, Richard Evans, Gus Fleites, Bill Fouse, Christian Gast,

Thomas Jardine, Paul Kaplan, Joe Keenan, Steve Kim, David Krein, Ananth Madhavan,

Brian Mattes, Daniel McCabe, Kris Monaco, Matthew Moran, Ranga Nathan,

Jim Novakoff, Rick Redding, Anthony Scamardella, Larry Swedroe, Jason Toussaint,

Mike Traynor, Jeff Troutner, Peter Vann, Wayne Wagner, Peter Wall, Brad Zigler


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What’s really in your ETF index?Market Vectors Index MethodologyFor Emerging Markets ETF Investors.

➤ Liquid. Each stock must meet minimum requirements for market capitalization and daily trading volume.1

Improves ability to track index.

➤ Inclusive. Includes publicly traded companies deriving at least 50% of their revenues from a country, even if thecompany is listed, domiciled or headquartered elsewhere. Many emerging market companies list in New York, Hong Kong, London and Toronto.

➤ Diversified. Stock weightings are capped at 8%, often resulting in greater diversification by holding and by sector.

➤ Transparent. Constituents and weights are updated and published daily, and are accessible for free at vaneck.com.

Market Vectors Indonesia Index ETF (IDX)2

1 To be “liquid,” a stock must have: a market cap over USD $150 million, a three-month average daily trading volume over USD $1 million, and tradedat least 250,000 shares per month over the last six months.

2 The Fund is classified as a “non-diversified” investment company under the 1940 Act.3 Factors identified refer to the index.

The Fund is subject to elevated risks, including those associated with investing in foreign securities, in particular in Indonesian issuers, which include, among others, expropriation, confiscatory taxation, political instability, armed conflict and social instability. Investors should be willing to accept a high degree of volatility and the potential of significant loss. The Fund may loan its securities, which maysubject it to additional credit and counterparty risk. Please refer to the prospectus for complete risk information. ➤Fund shares are not individuallyredeemable and will be issued and redeemed at their NAV only through certain authorized broker-dealers in large, specified blocks of sharescalled “creation units” and otherwise can be bought and sold only through exchange trading.Creation units are issued and redeemed principallyin kind. Shares may trade at a premium or discount to their NAV in the secondary market. ➤The Market Vectors Indonesia Index (the “Index”)is the exclusive property of 4asset-management GmbH, which has contracted with Structured Solutions AG to maintain and calculate the Index. Structured Solutions AG uses its best efforts to ensure that the Index is calculated correctly. Irrespective of its obligations toward4asset-management GmbH, Structured Solutions AG has no obligation to point out errors in the Index to third parties. Market Vectors IndonesiaIndex ETF (the “Fund”) is not sponsored, endorsed, sold or promoted by 4asset-management GmbH, and 4asset-management GmbH makes norepresentation regarding the advisability of investing in the Fund. ➤Investing involves risk, including possible loss of principal. An investorshould consider investment objectives, risks, charges and expenses of the investment company carefully before investing. To obtaina prospectus or summary prospectus, which contains this and other information, call 888.MKT.VCTR or visit vaneck.com/idx. Pleaseread the prospectus or summary prospectus carefully before investing.

Van Eck Securities Corporation, Distributor | 335 Madison Avenue | New York, NY 10017

Based on the Market Vectors Indonesia Index (MVIDXTR)3

➤ Inclusive and diversified Indonesia exposure.

➤ Constituents must meet minimum liquidity requirements.

➤ See the latest fund performance and get the full

list of index constituents and weights, updated

daily, at vaneck.com/idx.

Project1 4/14/11 12:43 PM Page 1

8

Editor’s Note

Jim Wiandt

Editor

July / August 2011

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 index-es 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,

Risky Business

Jim Wiandt

Editor

For more complete information regarding RydexShares,® call 800.820.0888 or visit www.rydex-sgi.com for a prospectus and a summary prospectus(if available). Investors should carefully consider the investment objectives, risks, charges and expenses of a fund before investing. The fund’sprospectus and its summary prospectus (if available) contain this and other information about the fund. Please read the prospectus and summaryprospectus (if available) carefully before you invest or send money.

Rydex Equal Weight ETFs may not be suitable for all investors. • Investment returns and principal value will fl uctuate so that when shares are redeemed, theymay be worth more or less than original cost. Most investors will also incur customary brokerage commissions when buying or selling shares of an ETF. • Investmentsin securities are subject to market risks that may cause their prices to fl uctuate over time. • ETF Shares may trade below their net asset value (“NAV”). The NAVof shares will fl uctuate with changes in the market value of an ETF’s holdings. In addition, there can be no assurance that an active trading market for shareswill develop or be maintained. Sector funds may not be suitable for all investors. Investing in sector funds is more volatile than investing in broadly diversifi ed funds, as there isa greater risk due to the concentration of the fund’s holdings in issuers of the same or similar offerings. • Please review a prospectus carefully for more information of the risksassociated with each ETF.

“Standard & Poor’s®,” “S&P®” and “S&P 500®,” are trademarks of Standard and Poor’s Financial Services, LLC and have been licensed for use by Rydex Investments and its affi liates. Rydex S&P ETFs are not sponsored,endorsed, sold nor promoted by Standard & Poor’s and Standard & Poor’s makes no representation regarding the advisability of investing in Rydex S&P ETFs.

Rydex|SGI funds are distributed by Rydex Distributors, LLC (RDL). Security Investors, LLC (SI) is a registered investment advisor, and does business as Security Global Investors® and Rydex Investments. SI and RDL are affi liates and are subsidiaries of Security Benefi t Corporation, which is wholly owned by Guggenheim SBC Holdings, LLC, a special purpose entity managed by an affi liate of Guggenheim Partners, LLC, a diversifi ed fi nancial services fi rm with more than $100 billion in assets under supervision.

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The intelligent pursuit of wealth.


By William Mast

Are credit default swaps a viable alternative to credit ratings?

Redefining Credit Risk

www.journalofindexes.com 11July / 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 cor-

porate 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 mate-rial 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 alterna-tive 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 HistoryToday 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 require-ment for bond issuers to attain a rating. Around this time, the business model changed from investor-pay to issuer-pay. Subsequently, and to this day, regulators have increas-ingly 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 pro-

cess; namely, procedures and methodologies.There is a widely perceived notion that the agencies

and their flawed models contributed to the global finan-cial 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 asso-ciated with the issuer-paid model, improving the quality and timeliness of the agencies’ ratings, increasing trans-parency and replacing self-regulation with more stringent government oversight.

Market Indexes And RatingsThe potential for disconnect between the ratings agen-

cies 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 mea-sure regardless of the industry or issuer, one would logi-cally 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 rat-ing agencies, we should also consider other options to the current offering of bond market indexes. The main-stream 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 small-er 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.

100

2 3 4 5 6 7

1

2

3

4

5

6

7

8 9 10 11 12

Composite Rating

Source: Morningstar

US Corporate Bond Yield Spread Vs. Ratings

Sp

rea

d (

%)

Figure 1

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 rat-ings. A better model for determining an issuer’s creditwor-thiness could be derived from real-time information.

For starters, a security’s market price reflects the expected performance of the entity, the potential for per-formance to exceed or fall short of expectations, sector outlooks, geographic performances, the potential for sur-prises and the security’s liquidity. Market activity (includ-ing 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 struc-ture 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 institu-

tions, 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 pur-est 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) pre-sented 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 cat-egories 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 spe-cific to the entity in question.

Fitch Solutions (2008) used CDS pricing to build mar-ket-implied ratings and concluded there is a clear ability

($B

)

80,000

40,000

20,000

60,000

02001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Credit Default SwapNotional Amount Outstanding

Source: ISDA Market Survey

Figure 2


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 insti-tutions. 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.

GrowthGrowth 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 counterpar-ty risk—and implemented international standards for contract terms.

to forecast future rating actions by examining CDS premi-ums. 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 pro-vide all of the answers. Concern over a perceived lack of transparency and regulation in the CDS markets was heightened during the financial crisis. In particu-lar, 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 cred-itworthiness. No credit rating model is perfect, but when appropriately harnessed and interpreted, the signals pro-vided 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; port-folio 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?

JOURNAL OF INDEXES ADVERTISING INFORMATION AT WWW.JOURNALOFINDEXES.COM/ADVERTISE

*OEFY�1VCMJDBUJPOT�--$ ��4BDSBNFOUP�4U� �4VJUF�� 4BO�'SBODJTDP �$"��t�"EWFSUJTJOH�BOE�3FQSJOUT�*ORVJSJFT��


July / August 201114

By Gavan Nolan and Tobias Sproehnle

Innovation in CDS indexes

Credit Derivatives Indexes:Methodology And Use


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 commodi-ties indexes. They originated in 2001, when J.P. Morgan launched the JECI and HYDI indexes. Morgan Stanley fol-lowed 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 liq-uid part of the relevant single-name CDS market. The Markit CDX North American Investment Grade Index, for example, consists of 125 North American investment-grade names, selected according to a number of criteria, including liquidity, ratings and underlying asset avail-ability. With this index, an investor interested in taking a broad exposure to U.S. corporate investment-grade risk

Global Tradable Credit Indexes

Figure 1

Synthetic

Fixed Income

Europe Markit iTraxx LevX

Europe Markit iTraxx Europe

Asia Markit iTraxx Asia

US Markit LCDX

North America Markit CDX NAInvestment Grade (IG, HiVol)Crossover

High Yield (HY, HY.B, HY.BB)Sectors

Europe (Europe, HiVol)Non-FinancialsFinancials (Senior, Sub)Crossover

Japan (Main, HiVol)Asia ex-Japan (IG, HY)Australia

Emerging

MarketsMarkit CDX EM

Emerging Markets

EM Diversified

LCDX

Tranches

Senior

Cash

Source: Markit

Fixed IncomeiBoxx

Europe

Asia

US

Emerging Markets

Fixed

Income

Structured

FinanceUS Markit ABX, CMBX, TABX

US Markit MCDX

Corporate

Bonds

Loans

Bonds

Municipal

Bonds

Sovereigns Markit iTraxx SovX

Western Europe

CEEMEAAsia Pacifi c

Latin America

Global Liquid Investment Grade

G7


can execute this strategy with a single CDS trade rather than by purchasing 125 contracts simultaneously to make up a diverse portfolio.

Credit Indexes: StructureThe 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 driv-ing 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 reflec-tion 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-the-run” 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 OverviewMarkit’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 quar-terly (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 initia-tion 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 IndexesCDS indexes are traded either in spread or in price

terms (see Figure 4). This convention mimics the bond

Credit Index Construction

Figure 2

CDS trading

volumes

observed

from DTCC TIW

Rules

applied

Provisional

membershipProvisional

membership

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20

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applied to each

index family

Source: Markit

Trading Example

Figure 3

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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

underlying index components. These theoretical index lev-els are calculated using the following methodology:r�5IF�TVSWJWBM�QSPCBCJMJUZ�PG�FBDI�DPOTUJUVFOU�BU�FBDI�

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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 haz-ard rate model will give better results for large movements in the spread. In the simple valuation methodology, the

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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 avail-able 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 (trans-acting at mid means transaction costs are not included).

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 every-thing 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 govern-ments with enormous budget deficits. Despite previous-ly 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-

Trading Parameters

SpreadCDX (IG, XO, HVOL), iTraxx (Europe, Japan,

Asia ex-Japan, Australia), SovX, MCDX

Price CDX (HY, EM, EM.Div), LCDX, LevX

Figure 4

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.


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 sover-eign 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

class as a whole. As was witnessed after the introduc-tion of the Markit iTraxx Europe Index, as well as sec-toral indexes such as the Markit iTraxx Europe Senior Financials, liquidity tends to get concentrated in index-related 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 east-ern Europe, as well as the Middle East and Africa, fol-lowed in January 2010.

So who uses the Markit iTraxx SovX family of index-es? 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 underly-ing 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

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 com-parison. Four of the SovX WE’s 15 equally weighted con-stituents are “peripheral” eurozone countries: Greece, Ireland, Portugal and Spain. In contrast, just eight of the

Markit iTraxx Europe’s 125 constituents are based in these countries. The peripherals have seen a marked deteriora-tion 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 signifi-cantly. The increasing differential will have delivered profits on this strategy.

Figure 5

Deterioration In Western European Sovereign Credit

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continued on page 49

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.

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Looking at an asset class that isn’t always as it seems

A Fixed-Income Roundtable

www.journalofindexes.com July / August 2011 21

In an effort to get a handle on what’s going on in the fixed-

income area, the Journal of Indexes assembled a broad

panel of experts and presented them with some wide-

ranging 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 pay-

ment of principal and interest.

JOI: Are credit default swaps a good alternative or sub-

stitute 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 per-

spective 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 one-

to 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 out-

perform 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 mar-

ket, 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 prob-

lem, 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 mar-

ket but with a low expense ratio, and very low turnover.

A primary argument of indexing presupposes market-

cap 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 aver-

aged 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 buy-

ing 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.

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 empir-

ical evidence suggesting that bond ratings tend to be more

reactive than proactive. That is, you see downgrades follow-

ing a sequence of negative shocks to either the corporation

or to the country. We have seen this with the ratings for sub-

prime mortgages. More recently, ratings for the PIIGs coun-

tries were revised down only after they started to experience

problems refinancing their debt.



Hsu: Often market-based information—information that

one extracts from, say, the credit default swap—may con-

tain 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 creditwor-

thiness information from a credit default swap, versus get-

ting that information from bond rating agencies.

I would support the use of CDS as a potentially more

informative and timely source of information.


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 unman-

ageable, and often you experience high tracking error.

From that perspective, actively managing the fixed-

income 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 evi-

dence 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 fixed-


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 there-

fore higher interest rates.

However, the viewpoint of expecting a price decline has

been in the marketplace for quite a while. To date, we con-

tinue 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.


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 tax-

advantaged investors buying muni bonds for the attractive

yields. That’s not to say that they’re not pricing in the signifi-

cant 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 pos-

sibility, then the yield is quite attractive, rather than a bubble

in the municipal bond arena.


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?


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 dis-tressed 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 port-folio. 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.



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 likeli-hood 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 inadver-tently 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 recom-mendation. 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



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 dif-ferent 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.



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.


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.




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-struc-ture 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.


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 got-ten 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 look-ing 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.



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.


or in some of its subsets?

DeRose: I think it can, but you know there are always trade-offs. 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 manage-ment, 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 val-ues; 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 col-lapsing. There’s been a lot of misunderstanding regarding bonds and the markets, and that’s kind of led to some outra-geous claims by some regarding defaults that may occur in the market down the road. Certainly there’s budget chal-lenges 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 balanc-ing 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 investment-grade 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.




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 arti-ficial 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.


DeRose: Well, I think it should be, but it seems to be mov-ing 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


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 accu-

rate? 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 invest-ment grade or not. I’m looking at it from a benchmarking or measuring-the-market perspective. When we’re iden-tifying 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 perspec-tive, 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 rat-ings. There are ways to look at the bond market that are not necessarily based on the first dollar of default, as rat-ing 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.



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 partici-pants 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.



Rieger: In my role as vice president of fixed-income indi-ces 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 mar-ket, 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 precipi-tously 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 tax-exempt yields equate to taxable equivalent yields that are substantially cheaper than investment-grade corpo-rates, 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 partic-ular, 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 mar-ket, we’ve seen yields come way down and prices have been rising accordingly, so they have only so much more upside potential mathematically.


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 weight-ed or GDP-weighted—those indices also serve important purposes, but are reporting back on a strategy of invest-ing 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 weight-ings 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.




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 mil-lion 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,


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 num-bers 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 qual-ity 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 “mak-ing sense.” Clearly there is a broad set of active manag-ers, and there are supposedly as many active managers as passive managers in the fixed-income space. They’re certainly trying to achieve outperformance … and usu-ally 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 man-ager 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 per-cent 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 market-cap weighting. And it’s very difficult to see the market mov-ing wholesale very rapidly away from such a standard—in this kind of environment especially.

Thinking back to the question about active manage-ment, 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 bench-marks, 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 trans-parent 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 mar-ket—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.




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 indica-tive 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 dis-persion 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 con-trol process and price evaluation routines that thoroughly validate pricing inputs.


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.


Larry Swedroe, Director of Research,

Buckingham Asset Management



Swedroe: I think it’s important to distin-guish 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 hos-pital 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 impor-tant 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 man-ager 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 cer-tainly 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.



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 differ-ently? 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.



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 elim-inate—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 convert-ibles. 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 fed-eral 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.



By David Blanchett

What every bond investor should know

The Impact Of Fund Flows On Fixed-Income Mutual Fund

Performance

July / August 2011www.journalofindexes.com 29

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 par-ticular the Pimco Total Return Fund, received a seem-ingly 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 perfor-mance 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 approxi-mately 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 AssetsThe 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 per-centage 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 allo-cate 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 under-lying bond funds.

Follow The MoneyAccording 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 fixed-income 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 histori-cally, 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

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

Period Ending

Source: Morningstar

Bil

lio

ns

N Total Assets N Rolling 12-Month Net Flow

Dec1995

Dec1997

Dec1999

Dec2001

Dec2003

Dec2005

Dec2007

Dec2009

Figure 1

0%

5%

-5%

10%

-10%

15%

20%

25%

Dec1995

Dec1997

Dec1999

Dec2001

Dec2003

Dec2005

Dec2007

Dec2009

Tota

l A

sse

ts

Period Ending

Monthly Rolling 12-Month Net Flows As A Percentage Of Total Assets In The Morningstar Intermediate-Term Bond Category

December 1995 to September 2010

Source: Morningstar

Figure 2

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] con-firmed this effect. Figure 3 includes information about his-torical 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 docu-mented 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 signifi-cantly better than those that experience outflows, suggest-ing 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 fol-lowing 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 intermediate-term bond funds in the cheapest two deciles received the most net inflows from 1996 to 2008 in all but one year.

AnalysisThere 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 con-sidered the impact of expense ratios and fund flows on the

Intermediate-Term Bond Category PreviousOne-Year Performance Decile Rank

Av

era

ge

An

nu

al

Ne

t F

un

d F

low

s (M

)

Average Annual Net Fund Flows For Intermediate-Term Bond Funds By Expense Ratio Decile

Source: Morningstar

$100

-$100

$0

$200

$300

$400

$500

$600

1 2 3 4 5 6 7 8 9 10

Low High

$400

$350

$300

$250

$200

$150

$100

$50

$0

-$0

-$1001 2 3 4 5 6 7 8 9 10

Intermediate-Term Bond CategoryPrevious One-Year Performance Decile Rank

Av

era

ge

An

nu

al

Ne

t F

un

d F

low

s (M

)

Average Annual Net Fund Flows For Intermediate-Term Bond Funds By Previous One-Year Performance Decile

Source: Morningstar

High Low

Average Future One Year Outperformance Vs. Category Average By Previous One-Year Performance Decile Rank

.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

Source: Morningstar

Fu

ture

1-Y

ea

r O

utp

erf

orm

an

ceV

s. C

ate

go

ry A

ve

rag

e

N Net Performance N Gross

High Low

Figure 5

Figure 3

Figure 4


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 calendar-year-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 intro-duced. 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 inde-pendent 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

Source: Morningstar; author’s calculations.

Figure 6

Gross And Net Intermediate-Term Bond Performance By Flow And Expense Ratio Quartile Groups

Low High

Low High

Low High

Past One-Year Flow Quartile



1

1

1

2

2

2

3

3

3

4

4

4

Avg

Avg

Avg

1 Minus 4

1 Minus 4

Low 1 0.08% 0.11% 0.16% -0.07% 0.07% 0.16%

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%

Low 1 0.44% 0.49% 0.49% 0.29% 0.43% 0.16%

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

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

Future One-Year Gross Performance

Future One-Year Net Performance

Average Number Of Test Funds Per Period

Exp

. Ra

tio

Qu

art

ileE

xp. R

ati

o Q

ua

rtile

Exp

. Ra

tio

Qu

art

ile


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.


July / August 2011

Talking Indexes

By David Blitzer

32

Fire burn, and cauldron bubble1

Bubble Bubble,

Toil And Trouble

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 val-ues. 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 invest-ing with indexes attractive. Besides being lower cost, index investing is attractive because bubbles are hard to recog-nize 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 invest-ment 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 them-selves 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


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 eventu-

ally reached levels where few could afford to buy.

Those comparisons to income and rents provided indi-

cators of bubbles and values for the housing market. For

stocks, indexes provide useful measures. In the technolo-

gy-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 pro-

portions 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 condi-

tions 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.

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.

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Endnote

1 Apologies to William Shakespeare and the witches of Macbeth


By Jeremy Schwartz

Don’t rule out the significance of either one

The Importance Of Dividends And Buybacks1 Ratios

For Gauging Equity Values


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 con-

siderably 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 termi-nal [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 unwit-tingly 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 buy-backs. 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 opera-tions. An increasing number of companies, perhaps driven by a belief that modern equity investors have more appe-tite 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 Cashr�%JWJEFOET� All shareholders of a firm receive dividends

when they are distributed.r�#VZCBDLT��A 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 Benefitr� %JWJEFOET�� The benefit, or the cash received, from

dividends occurs at the time the dividends are paid, and therefore reflect a historical measure. r�#VZCBDLT��The benefit from share buybacks—a reduc-

tion in shares outstanding—is a benefit that applies to future distributions. Even though only a portion of share-holders sell their shares back to the company, the reduc-tion 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 prices5 and one can choose the timing of share sales (and tax consequences) at a point in the future; dividends, by con-trast, 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 imple-ment a share buyback program at the regular quarterly fre-quencies that firms pay cash dividends. On balance, wheth-er 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 distribut-ing cash to shareholders both by dividends and share buy-backs, and one must account for both ways when gauging the historical relative valuation levels of the market.

Historical S&P 500 Buyback DataHoward Silverblatt of Standard & Poor’s publishes histor-

ical 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


2008 to 2010. Still, dividends increased cumulatively 45 per-cent 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 buy-backs 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 moni-toring 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 sharehold-

ers (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 buy-backs. 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�%JWJEFOE�4USFBN� 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 theo-retical 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 calcu-lated in a similar fashion as a dividend yield is calculated.6

Figure 1

S&P 500 — Trailing 12 Month Data

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.

Buybacks

($B)

Dividends

($B)

S&P 500

Index Price

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%


Key data highlights as of Dec. 31, 2010:

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Figure 2

Dividend And Buyback Ratios On WisdomTree U.S. Indexes (As Of Dec. 31, 2010)

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.

Since

Index

Inception

Return

1-Year

Return

Dividend

& Buyback

Ratio

Buyback

Ratio

Dividend

Yield

Trailing

12-Month

Dividends

($B)

Trailing

12-Month

Buybacks

($B)

Inception

Date

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%



By Francis Gupta

Creating a new framework for country classification

Developed, Emerging Or Frontier Markets?


Early in 2011, Dow Jones Indexes introduced a new methodology for classifying global equity markets. This methodology is novel in its approach to catego-

rizing markets in that its classifications are based entirely on market-centric attributes and investor-centric experi-ences 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 method-ology is to use the merits (and the demerits) of the equity markets of the member countries as a key factor in group-ing the countries into categories.

The new methodology is also investor-centric. In addi-tion 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 unfa-miliar to investors, as well as the processes and regula-tions 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 catego-ries 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 com-mon 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 evalua-tion 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 signifi-cantly 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 StatusFigure 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 capi-talization of all companies listed for trading that are domi-ciled 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 com-panies listed in a local market makes it much easier for local investors to assess those companies. In addition, the experi-ence of an investor transacting in the equity of a locally listed foreign company would be similar to the investor’s experi-ence 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 foreign-domiciled 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 mar-ket 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 methodol-ogy 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, clearing-houses) 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 inves-tor experience in the market—both of which in turn influ-ence, in a crucial way, the market’s size and activity.5 The


■ Developed ■ Emerging ■ Frontier

�� Market Capitalization Of All Domestic Equity Listings ($M)

�� Dow Jones Indexes ��See Figure 2 for company counts, market capitalizations and coverage of this universe.

2 4 6 8 10 12 14 160

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

Figure 1


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 FrameworkThis 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 pol-icy 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 frame-work 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 inter-ests 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 follow-ing are the aspects of the market environment and regula-tory 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 monop-olistic 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 inves-tors 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 coun-try 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 fac-tors 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 buy-ers and sellers have to pay to participate in the trade.9 In general, the more active the market, as measured by vol-ume 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 trad-ing 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 dif-ference 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 sup-port investor demand, and vice versa.

Level of access to market depth and trade-reporting infor-

mation – 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-


age their views on prices and by increasing liquidity. Short-sellers need to be able to borrow stock that they can sell.

Derivative products and markets – These allow par-ticipants to not only trade on their current views regard-ing 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 identi-cally 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 inves-tor; that is, owners of equity should be able to transfer own-ership to whomever they please. Rules that don’t allow for, or restrict, transferability of ownership discourage long-term ownership because they work against investor goals.

Operations: Clearing And SettlementThe final factor in the Dow Jones Indexes country clas-

sifications methodology relates to the management of risks that buyers, sellers and other market entities (such as mar-ket 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-

Figure 2

The Dow Jones Country Classification Universe: Counts, Market Capitaliztions And Coverage By Country

Classification Country # Of Components MCAP ($USB) % MCAP COVERAGELISTING #

All Equity Exchanges

As Of Q4 2010 Review

Dow Jones Global Total Stock Market Index As Of 12/31/2010

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


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 pay-ment 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 transac-tion (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 inves-tors—basically, the more the merrier.

Absence of prefunding practices – The presence of pre-funding 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

The Dow Jones Country Classification Universe: Counts, Market Capitaliztions And Coverage By Country

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.


Figure 2 cont’d

Classification Country # Of Components MCAP ($USB) % MCAP COVERAGELISTING #

All Equity Exchanges

As Of Q4 2010 Review

Dow Jones Global Total Stock Market Index As Of 12/31/2010


An excerpt from ‘The House That Bogle Built’

‘The Devil’s Invention’

By Lewis Braham


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 cer-tainly 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 employ-er, 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 manufac-turer. 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 some-one to start an index fund for retail investors. Bogle then read Charles Ellis’ article “The Loser’s Game” the follow-ing 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 sell-ing 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-Ameri-can,” 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.


Once the fund was launched, there were a number of technical challenges to running it. Computing technol-ogy 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 keep-ing 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 sell-ing stocks as perceived relative values change.

Vanguard’s introduction of the First Index Investment Trust represented a complete reversal of this active manage-ment approach—that is, a passive management approach, under which the manager, in effect, buys stocks in percent-ages 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 expens-es 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 fundamen-tal 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 arro-gates 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 expec-tations, 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 mar-ket 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 expens-es) 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 man-aged 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.


Putting numbers to this theory, the cost difference is dramatic. Vanguard was saving its index fund inves-tors 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 pro-vide 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

futile exercise. “Index funds,” he said, “are a result of skep-ticism 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 exis-tence 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

$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 surpass-ing 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 “unman-aged” 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.”

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

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.John Bogle


the principles of indexing would also work in world mar-kets—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 mar-ket, 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 diver-sification to bond fund investors that the Vanguard 500 pro-vided 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 low-margin 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 compet-itors. 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 pub-lished ones. It also developed a proprietary trading system to minimize transaction costs. Although the value ($8.3 bil-

lion) 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 man-agement 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

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 conven-

tions 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.


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 inves-tors 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.

Nolan and Sproehnle continued from page 18

Figure 6

Developed Vs. Emerging Markets

280

260

240

220

200

180

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140

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� Markit iTraxx SovX Western Europe � Markit iTraxx SovX CEEMEA

Source: Markit

Figure 3

Dividend And Buyback Ratios On WisdomTree International And U.S. Indexes (As Of Dec. 31, 2010)

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.

Since

Index

Inception

Return

1-Year

Return

Dividend

& Buyback

Ratio

Buyback

Ratio

Dividend

Yield

Trailing

12-Month

Dividends

($B)

Trailing

12-Month

Buybacks

($B)

Inception

Date

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%

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 remind-er 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 fore-tell for the overall market valuation ratios, we see a fairly attrac-tive 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 divi-dend 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 buy-back 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 alterna-tive asset class of choice: U.S. bonds.

DisclosuresYou 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.

Endnotes1. 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.htm4. 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 per-

share 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

Schwartz continued from page 37


assets of market participants, custodian banks assist with mini-mizing 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.

ConclusionIn the past, from a global investing perspective, it was stan-

dard 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 cor-relations among the three categories are high, the cat-egories 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 cat-egory 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

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.

Gupta continued from page 43

Endnotes1. 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 econo-

mies 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 rela-

tively 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.

Figure 3

2500■ DM ■ EM ■ FM

3/1

8/2

00

5

7/1

8/2

00

5

11

/18

/20

05

3/1

8/2

00

6

7/1

8/2

00

6

11

/18

/20

06

3/1

8/2

00

7

7/1

8/2

00

7

11

/18

/20

07

3/1

8/2

00

8

7/1

8/2

00

8

11

/18

/20

08

3/1

8/2

00

9

7/1

8/2

00

9

11

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/20

09

3/1

8/2

01

0

7/1

8/2

01

0

11

/18

/20

10

2000

1500

1000

500

0

Trade Date

Ind

ex

Va

lue

The DJI Country Classi�cations Approach GeneratesThree Distinct Equity Asset Classes For Global Equity:

Developed Markets (DM), Emerging Markets (EM)And Frontier Markets (FM)

Source: Dow Jones IndexesNote: Uses the Dow Jones Indexes Country Classi�cation 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.

Ann. Return Std. Dev.

Correlation

DM

DM

EM

FM

EM FM

4.4%

15.3%

2.5%

19.3%

23.8%

15.2%

1.00

0.91

0.78

–

1.00

0.79

–

–

1.00


News


Russell Launches First In-House ETFs

In mid-May, Russell Investments, the Seattle-based money manage-ment 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 bil-lion in assets are benchmarked to its various indexes. Moreover, it spon-sors 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 select-ing individual securities. They are all priced at 0.37 percent and include:r��3VTTFMM�"HHSFTTJWF�(SPXUI�&5'�

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own line of both active and passive ETFs for about two years. The pro-cess usually takes anywhere from six to nine months, though sources at Russell disputed the notion that its so-called FYFNQUJWF� SFMJFG� QFUJUJPOT� BU� UIF� 4&$�

were somehow being held up. Industry sources have said the delays for Russell XFSF�SFMBUFE�UP�UIF�4&$�OPU�CFJOH�DPN-

fortable granting exemptive relief to a firm that already has such a large pres-ence 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—OPUBCMZ�7BO�&DL�(MPCBM�XJUI�JUT�.BSLFU�

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but the sources said the sheer size of Russell gave the commission pause.

Each Russell Investment Discipline ETF tracks the performance of a cor-responding Russell Investment Discipline Index, which is indepen-dently screened and constructed in order to reflect the return patterns of a particular investment strategy, accord-ing to the press release. The Russell Investment Discipline indexes are con-structed 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 percent-age 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&�"SDB��222�

The rebalancing was the first since 1998, when the exchange adjusted Microsoft’s and Intel’s outsized posi-tions in the portfolio to address compli-ance issues with the Internal Revenue Service. A one-off occurrence, it reor-ganized the portfolio into a straight market-cap arrangement. But the index’s underlying modified market-cap methodology, which was insti-tuted 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 heavy-weights in the benchmark—includ-JOH� (PPHMF �.JDSPTPGU � 0SBDMF � $JTDP�

and Intel—was to increase.The Nasdaq-100, which features the

100 biggest nonfinancial companies within the broader Nasdaq bench-mark, was rebalanced based on hold-ings 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 econo-mists say has the makings of a poten-tial double-dip in housing, according UP� UIF� MBUFTU� 4�1�$BTF�4IJMMFS� )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 mar-ket as it struggles to stage a sustain-able 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 edg-ing closer to testing their 2009 lows, XJUI� CPUI� UIF� ��$JUZ� BOE� ��$JUZ�

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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

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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 LineupWith fears of a bond-market sell-

off 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 pos-sibilities 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:r��1SP4IBSFT� 4IPSU� )JHI� :JFME� &5'�

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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 DEVELOPMENTSMSCI Debuts Risk-Weighted Index Family

In April, MSCI said that it had launched alternatively weighted ver-sions of its MSCI All Country World Index, MSCI Emerging Markets Index and MSCI World Index.

Rather than weighting by pure market capitalization, MSCI’s risk-weighted 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 JUT�.BSLJU�J5SBYY�4PW9�JOEFY�GBNJMZ��

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America Index covers issues from Argentina, Bolivia, Brazil, Chile, Colombia, Mexico, Panama and Mexico. Components are equal weight-ed and selected based on liquidity. .BSLJU�T�J5SBYY�4PW9�GBNJMZ�BMSFBEZ�

included a variety of regional indexes, including ones covering Asia Pacific, 8FTUFSO�&VSPQF�BOE�UIF�(��DPVOUSJFT �

among others. The index is not yet tradable, but

Markit said that could change depend-ing 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

6�4��IPNF�QSJDFT�JO�TPNF�DJUJFT�BSF�UIF�MPXFTU�they’ve been in more than a decade.


Newsfor 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 repre-sent 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 prod-ucts 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 infrastruc-ture; energy core infrastructure;

transportation core infrastructure; infrastructure-related conveyance services; infrastructure-related com-munications services; and infrastruc-ture-related materials & engineering.

The FIIS methodology further clas-sifies companies into two tiers in terms of infrastructure exposure: Those deriving more than 65 percent of their revenues from infrastructure are desig-nated “core infrastructure” companies, while companies deriving from 20 per-cent up to 65 percent of their revenues from infrastructure are labeled “infra-structure-related opportunities.”

The index series can be customized according to geography, infrastruc-ture 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 securi-ties based on the probability a com-pany has of delivering a performance that would support its current stock price, as measured by a methodol-ogy 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, hold-ing 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 divi-dends 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 repre-sents 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 yuan-denominated bonds issued in Hong Kong. It launched in May.


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 ser-vices 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 emerg-ing 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 geo-graphic diversification.

According to the index’s method-ology, rebalances are triggered by an individual currency position falling below $1,000 (each position represent-ed $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 free-float market capitalization from the remaining pool of all the sectors. Similarly, the infrastructure suppli-ers index selects the top four infra-structure suppliers from each sector, before adding its remaining compo-nents from the remaining pool based on market capitalization alone.

AROUND THE WORLD OF ETFsFirst Trust ExpandsAlphaDex 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�

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Fund (NYSE Arca: FYT)The international funds each charge

an expense ratio of 0.80 percent, while the domestic funds charge 0.70 per-cent. 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, compris-ing 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 gener-ate yield while minimizing risk exposure through a portfolio solely comprising investment-grade notes. The Market Vectors Investment Grade Floating

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 typi-cally attractive in an environment of rising interest rates as a short-term source of income, an investment-grade version goes even further by helping to offset some of the issuer credit risk as well as liquidity con-cerns often associated with below-investment-grade bank loans.

Also, because the notes have vari-able coupons linked to the three-month 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 ReturnsIn the final days of March,

FocusShares—now owned by Scottrade—returned to the ETF mar-ket with the launch of 15 funds tied to Morningstar indexes.

Notably, many of the products are the cheapest, or among the cheap-est, 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 per-cent, 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 seg-ments, 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 compa-nies 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, com-pared 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 sov-ereign debt futures that serve up sin-gle- and triple-long exposure to their respective indexes. The German bank uses Invesco PowerShares for market-ing of the notes.

The ETNs include:r��1PXFS4IBSFT� %#� (FSNBO� #VOE�

Futures ETN (NYSE Arca: BUNL)r��1PXFS4IBSFT� %#� �Y� (FSNBO� #VOE�

Futures ETN (NYSE Arca: BUNT)r��1PXFS4IBSFT�%#�*UBMJBO�5SFBTVSZ�#POE�

Futures ETN (NYSE Arca: ITLY)r��1PXFS4IBSFT� %#� �Y� *UBMJBO� 5SFBTVSZ�

Bond Futures ETN (NYSE Arca: ITLT)r��1PXFS4IBSFT�%#�+BQBOFTF�(PWU�#POE�

Futures ETN (NYSE Arca: JGBL)r��1PXFS4IBSFT� %#� �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 remain-ing notes track subsets of the lat-ter, 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 per-cent 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 .BSDI�� 1PXFS4IBSFT�FNQIB-sized 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 cur-rency 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,


Taiwan, Thailand as well as Australia and New Zealand. The fund deliber-ately 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 FUTURESCME Volume Up 2 Percent In April

April 2011 saw an average daily vol-ume 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 mil-lion 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 OPTIONSCBOE Debuts GLD-Based Volatility Options

The Chicago Board Options Exchange on April 12 launched trad-able 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 methodol-

ogy used for the CBOE Volatility Index and applied to options on GLD.

The Gold VIX is an up-to-the-min-ute 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-most-traded U.S. ETF.

CBOE Volumes Fall From April 2010

CBOE Holdings Inc. saw its aver-age daily volume for April fall 19 per-cent 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 experi-enced 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 prod-uct 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 EXCHANGESNasdaq 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 liquid-ity than the original benchmark, all while preserving return and volatility characteristics.

The Nasdaq-100 Data Explorers Optimized Index is essentially a sub-set of the securities included in the Nasdaq-100 Index—a basket of the largest nonfinancial companies glob-ally—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 origi-nal index, the company said in a press release.

Russell And Chi-X Create Index Family

In late March, an announce-ment from Chi-X Europe and Russell Investments heralded the two compa-nies’ 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 larg-est and most liquid stocks. They are intended to be investable and offer comprehensive coverage of the geo-graphic 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.


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 popula-tion 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-expense-ratio combination group has materially more funds than the low-flow and high-expense-ratio group). Not perform-ing re-sorts better matches the information available to investors when making purchase decisions (note, though, re-sorted tests yielded virtually identical results).

Results

The results of the combination test are included in Figure 6. As the reader can see from Figure 1, the best-performing 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 impor-tance of expense ratios dissipates when viewing the out-performance 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 fixed-income 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

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 intermediate-term bond mutual funds. This calculation approach is simi-lar 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 differ-ence 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 differ-ence in the future gross performance and future net perfor-mance independently. This ensures that management fees are not driving the potential difference in performance.

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 underperfor-mance has substantial implications for investors, espe-cially 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.

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.

Blanchett continued from page 31


Global Index DataJuly/August 2011Selected Major Indexes Sorted By YTD Returns

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 51.52Oil 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 39.07MSCI 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 36.94MSCI 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 35.39MSCI 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 37.56MSCI 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 37.86DJ 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 25.11EURO 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 33.10S&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 27.38S&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 37.80S&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 29.76Russell 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 27.51S&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 25.62DJ 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 19.97S&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 25.17Wilshire 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 25.95MSCI 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 24.37Russell 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 27.73S&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 26.75MSCI 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 28.15S&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 27.48Russell 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 22.17Dow 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 20.29Russell 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 21.84Russell 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 22.56MSCI 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 26.23Alerian 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 23.03Russell 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 22.22Russell 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 23.27Russell 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 23.59S&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 21.78MSCI 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 24.32NASDAQ 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 24.71MSCI 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 24.91Russell 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 29.05Dow 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 27.74MSCI 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 28.71Russell 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 28.59DJ 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 23.39S&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 38.23Dow 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 16.23Barclays 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 17.91Barclays 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 17.06S&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 31.94MSCI 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 31.66Barclays 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 8.57S&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 48.78Barclays 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 7.90MSCI 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 33.91JPM 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 12.77Barclays 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 5.57Barclays 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 4.18MSCI 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 36.05Barclays 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 4.87Barclays 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 1.39Barclays 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 17.80S&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 21.07Citigroup 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 15.89MSCI 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 42.41MSCI 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.

July / August 2011 59

Index FundsJuly/August 2011Largest U.S. Index Mutual Funds Sorted By Total Net Assets In $US Millions


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 1.60Vanguard 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 1.76Vanguard 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 1.72Vanguard 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 1.69Vanguard 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 1.78Vanguard 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 1.46Vanguard 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 1.62Vanguard Total Bond Mkt II, Inv Shrs VTBIX 31,474.0 0.12 1.52 1.58 6.41 - - - - - - - 3.12Fidelity 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 1.67Vanguard 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 3.39Vanguard 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 1.70Vanguard 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 1.72Vanguard 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 3.43Fidelity 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 1.70Vanguard 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 1.66T. 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 1.50Vanguard 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 3.28Schwab 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 1.68Vanguard Total Bond Mkt II, Inst Shrs VTBNX 11,728.4 0.07 1.54 1.60 6.47 - - - - - - - 3.17Spartan 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 2.91Vanguard 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 3.39Vanguard 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 1.55Vanguard 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 3.45Vanguard 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 1.10Vanguard 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 2.15Fidelity 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 2.28Vanguard 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 1.03Fidelity Series 100 FOHIX 6,698.5 0.20 5.59 8.12 12.39 22.14 0.62 - - - 15.3 20.72 1.80Vanguard 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 1.69Vanguard 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 0.93Vanguard 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 1.00Vanguard 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 1.06Vanguard 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 0.86Fidelity 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 1.52Vanguard 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 0.95Vanguard 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 0.92Vanguard 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 0.31Vanguard 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 2.66Fidelity 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 1.55Vanguard 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 3.12Schwab 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 1.40Vanguard 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 1.09Fidelity 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 0.95Vanguard 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�,QüDWLRQ�3URWHFWHG�%RQG FSIPX 4,646.0 0.20 3.25 4.35 5.06 - - - - - - - 0.32Vanguard 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 3.97Vanguard 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 2.03Vanguard 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 1.13Vanguard 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 2.26Vanguard 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 2.04Vanguard 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 0.96Vanguard 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 2.29Vanguard 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 2.15ING 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 1.36Vanguard 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 2.27Vanguard 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 1.06ING U.S. Bond Class I ILBAX 3,758.2 0.46 1.46 1.46 6.14 5.88 5.47 - - - - 3.90 2.56Vanguard 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.



Morningstar U.S. Style Overview Jan. 1 − April 30, 2011

Trailing Returns %

3-Month YTD 1-Yr 3-Yr 5-Yr 10-YrMorningstar 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

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

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

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 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

Morningstar Market Barometer YTD Return %

US Market9.57

10.74

Value

9.45

Core

8.53

Growth

8.74Larg

e C

ap

11.84Mid

Cap

11.54Sm

all C

ap

11.13 8.35 6.73

10.01 12.38 12.97

8.80 12.56 13.09

–8.00 –4.00 0.00 +4.00 +8.00

Sector Index YTD Return %

Energy 19.31

Healthcare 13.05

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

Industry Leaders & Laggards YTD Return %

Rubber & Plastics 34.86

Broadcasting - TV 32.66

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

Biggest Influence on Style Index Performance

YTDReturn %

ConstituentWeight %

Best Performing Index

Small Growth 13.09

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

1-Year

19.32

Value

Larg

e C

ap

14.38

Core

16.02

Growth

16.59

Mid

Cap 26.45 29.05

17.13

Sm

all C

ap

23.90 31.90

–20 –10 0 +10 +20

3-Year

–1.74

Value

Larg

e C

ap

2.41

Core

2.40

Growth

6.86

Mid

Cap 7.08 4.86

10.34

Sm

all C

ap

9.66 9.90

–20 –10 0 +10 +20

5-Year

0.81

Value

Larg

e C

ap

4.07

Core

3.46

Growth

3.71

Mid

Cap 5.63 5.49

5.53

Sm

all C

ap

4.94 4.90

–20 –10 0 +10 +20

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 listsare 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 informationcontained 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.

?

61July / August 2011

Source: Morningstar. Data as of April 30, 2011.


Dow Jones U.S. Industry Review

PerformanceIndex 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

Industry Weights Relative to Global ex-U.S. Asset Class Performance

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.

All information in these materials is provided “as is”. CME Indexes and its affiliates do not make any representationregarding the accuracy or completenessof 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 providedby CME Indexes is impersonaland 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 Indexesmakes 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 Indexesor 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.

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 providedsolely 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.

© 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 trademarkof 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.

Chart compares industry weights within the Dow Jones U.S. Index to industry weights within the Dow Jones

Global ex-U.S. Index

U.S. = Dow Jones U.S. Index | Global ex-U.S. = Dow Jones 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

CompositeBasic Materials

Consumer GoodsConsumer Services

Financials

Health Care

Industrials

Oil & Gas

Technology

Telecommunications

Utilities

-15%

-10%

-5%

0%

5%

10%

15%

14% 16% 18% 20% 22% 24% 26% 28% 30% 32% 34% 36%

3-Year Annualized Risk

3-Y

ea

r A

nn

ua

lize

d R

etu

rn

-0.57%

-2.05%

10.97%

1.36%

-0.54%

5.17%

-8.05%

4.83%

-2.31%

-8.82%

-15% -10% -5% 0% 5% 10% 15%

Utilities

Telecommunications

Technology

Oil & Gas

Industrials

Health Care

Financials

Consumer Services

Consumer Goods

Basic Materials

Underweight <= U.S. vs. Global ex-U.S. => Overweight

20

30

40

50

60

70

80

90

100

110

120

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

U.S. [108.61] Global ex-U.S. [98.78] Commodities [85.11]

REITs [104.26] Infrastructure [112.95]

Dow Jones U.S. Industry Review


Largest New ETFs Sorted By Total Net Assets In $US Millions Selected ETFs In Registration

Largest U.S.-listed 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

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.

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 WatchSource: 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.

Exchange-Traded Funds Corner

Test Your Skills


A History Of Money

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

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 Bulgaria16. 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 bank-ing 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 ___ ___, banknote-like 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

How much do

you know about

money matters?

2 3 4 5

7 8 9

1

10

11 12

13 14 15 16

23

19

24

27

28 29

32 33

20

22

25

30

18

17

21

26

31

34

6

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”

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”

Designed specifically for InstItutIonal Investors

Presented by:

} For sponsorship opportunities, please contact:

Don Friedman at 415-659-9009 or [email protected]

} For speaking opportunities, please contact:

Allison Jones at 415-659-9012 or [email protected]

October 17-18, 2011the ritz-carlton • philadelphia, pa

From the producers of: InsideETFsEurope InsideCommoditiesInsideETFs

InsideIndexingBUIlDIng Better BetA 2011

inauguralconference

For more InFormAtIon:

george F. Will

Pulitzer Prize-Winning Columnist,

Journalist & Author

John C. Bogle

Founder of The Vanguard Group, Inc.,

President, Vanguard’s Bogle Financial

Markets Research Center

Featured speakers:

www.InsideIndexingConference.com/JOI

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.

YOU CAN’T FORCE A ROUND INVESTMENT INTO A SQUARE STRATEGY.

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 will reduce returns.

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 issue shares intended to track performance of their respective benchmark indices.

“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 affi liates. Certain State Street affi liates 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

Before investing, consider the funds’ investment objectives, risks, charges and expenses. To obtain a prospectus or summary prospectus, which contains this and other information, call 1.866.787.2257 or visit www.spdrs.com. Read it carefully.

Some people think it takes dog years to

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At State Street, we believe precision is an

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If you’re tired of barking up the wrong tree,

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