IN THIS LIST

Income in Indexing: How the iBoxx Liquidity Ecosystem Lends Well to Credit Markets – Part 2

Income in Indexing: How the iBoxx Liquidity Ecosystem Impacts Credit Markets – Part 1

Defense Beyond Bonds: Defensive Strategy Indices

The Hidden Costs of Retail Purchases in Municipal Bonds

An Index Approach to Factor Investing in India

Income in Indexing: How the iBoxx Liquidity Ecosystem Lends Well to Credit Markets – Part 2

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Frans Scheepers, CFA

Global Head of Fixed Income Products

S&P Dow Jones Indices

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Nicholas Godec

Head of Fixed Income Tradables

S&P Dow Jones Indices

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Brian D. Luke

Senior Director, Head of Fixed Income Indices - Americas

Part 2: Derivatives and Lending Markets

The iBoxx USD Liquid High Yield Index has served as the leading benchmark for the high yield market since its debut in 2006. Designed to track the most liquid instruments in the high yield market, the index supports a broad trading ecosystem via ETFs and derivatives. In Part 1, “Income in Indexing: How the iBoxx Liquidity Ecosystem Impacts Credit Markets,” we highlighted the growth of the high yield bond market and the index construction attributes that contribute to the iBoxx USD Liquid High Yield Index liquidity ecosystem. We measured the effectiveness of the index methodology in current markets through bond liquidity analysis. In Part 2 of this paper, we continue to analyze liquidity in different forms by exploring the fund, derivative and securities lending markets that propagate liquidity in various forms.

The iBoxx Liquidity Ecosystem

The iBoxx indices act as a central hub to a diverse and active tradable ecosystem, spanning active funds, ETFs, total return swaps and futures. Other instrument types, such as credit default swap indices, are complemented by the iBoxx ecosystem, which has also expanded to include ETF options, securities lending and portfolio trading as derivatives tracking the index have become more liquid.

Income in Indexing: How the iBoxx Liquidity Ecosystem Impacts Credit Markets – Part 2 - Exhibit 1

ETFs have been used to access high yield markets since the first ETF tracking the iBoxx USD Liquid High Yield Index launched in 2007. Beyond ETFs, total return swaps on the iBoxx USD Liquid High Yield Index are often used to express short positions, or to hedge a long position. In 2021, iBoxx Standardized Total Return Swaps and futures volumes linked to the iBoxx USD Liquid High Yield Index were USD 57.3 billion and USD 40.6 billion, respectively. Given the USD 21.4 billion in ETF AUM tracking the iBoxx USD Liquid High Yield Index at year-end 2021, derivative trading volume (iBoxx TRS and iBoxx Futures)-to-ETF AUM was 4.6x. Lastly, holders of funds tracking the iBoxx USD Liquid High Yield Index are seeing increased demand for their shares in the securities lending market.

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Income in Indexing: How the iBoxx Liquidity Ecosystem Impacts Credit Markets – Part 1

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Frans Scheepers, CFA

Global Head of Fixed Income Products

S&P Dow Jones Indices

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Nicholas Godec

Head of Fixed Income Tradables

S&P Dow Jones Indices

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Brian D. Luke

Senior Director, Head of Fixed Income Indices - Americas

Part 1: Index and Pricing

The iBoxx USD Liquid High Yield Index has served as the leading benchmark for the high yield market since its debut in 2006. Designed to track the most liquid instruments in the high yield market, the index supports a broad trading ecosystem via ETFs and derivatives. Though they have been generally excluded from traditional aggregate-type fixed income benchmarks in the past, high yield bonds remain a growing asset class that has historically offered yields that exceed investment grade debt (see Exhibit 1). In exchange for incremental yield are typically heightened credit and liquidity risk. In this article, we examine the components of the iBoxx USD Liquid High Yield Index (“IBOXHY”) that have demonstrated potential mitigation of liquidity risk. Contrasting other broad benchmarks to IBOXHY helps explain why liquid index construction matters, not just for the indices, but for the broader corporate bond ecosystem. We estimate the size of the ecosystem currently supported by IBOXHY to be in the hundreds of billions of U.S. dollars, and liquidity is measured as its underlying bond bid offer spreads. Because of the index design, it has been able to achieve the liquidity objective for over 15 years.

Promoting transparency with an emphasis on liquidity, the indices are constructed to serve as a basis for tradable instruments like ETFs, swaps and futures. In a follow up to this paper, we will explore the fund, derivative and securities lending markets that propagate liquidity in various forms.

Income in Indexing: How the iBoxx Liquidity Ecosystem Impacts Credit Markets – Part 1 - Exhibit 1

The iBoxx Liquidity Ecosystem in Different Markets

ETFs have been used to access high yield markets since the first ETF tracking the iBoxx USD Liquid High Yield Index launched in 2007. We will detail how index construction plays a pivotal role in identifying the optimal mix of bonds to track the performance of the overall high yield market. Beyond ETFs, total return swaps on IBOXHY are often used to express short positions, or to hedge a long position. We will discuss how volumes in that market have exceeded assets in the funds several times over, perhaps due to use as a means to hedge risk. For example, in 2021 iBoxx Standardized Total Return Swaps and futures volumes linked to the iBoxx USD Liquid High Yield Index were USD 57.3 billion and USD 40.6 billion, respectively. Given the USD 21.4 billion in ETF AUM tracking the iBoxx USD Liquid High Yield Index at year-end 2021, derivative trading volume-to-ETF AUM was 4.6x. Lastly, holders of funds tracking the iBoxx USD Liquid High Yield Index are seeing increased demand for their shares in the securities lending market, highlighting the growing opportunity set that has evolved around the iBoxx HY ecosystem. Thus, by comparing liquidity of eligible and ineligible bonds in the securities lending market of the iBoxx USD Liquid High Yield Index, we see new ways to independently measure liquidity. Each of these areas shines a light on how together they contribute to the index liquidity ecosystem.

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Defense Beyond Bonds: Defensive Strategy Indices

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Fei Mei Chan

Director, Core Product Management

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Craig Lazzara

Managing Director, Core Product Management

EXECUTIVE SUMMARY

  • The S&P 500® peaked on Jan. 3, 2022, and recorded a 20% decline in the first six months of the year. Bonds declined at the same time, as the U.S. 10-Year Treasury yield more than doubled.

  • The combination of falling stock prices and rising interest rates is historically uncommon. When the equity and bond markets decline simultaneously, defensive equity factors—which aim to provide protection during falling markets and participation in rising markets—become more relevant.

  • We explore ways of utilizing defensive strategy indices in order to improve the risk/return profile of a traditional asset allocation.

    Defense Beyond 
Bonds: Defensive Strategy Indices - Exhibit 1

    Rising Rates and Falling Stocks

    The S&P 500 reached its most recent peak on Jan. 3, 2022, and declined 20% through June 30, 2022. Were investors prescient, of course, avoiding losses would be easy: simply shift from equities to cash on or about Jan. 3, 2022. For those of us not gifted with omniscience, however, market timing is an inadequate solution.

    As Exhibit 1 suggests, in the first six months of 2022, investors were beset not only by the declining stock market, but also by rising interest rates. (The S&P U.S. Treasury Bond 7-10 Year Index was off by -10.6% as rates more than doubled.) This represents a radical change of fortune from the rising stock and bond markets that characterized most of the past 40 years. It also has an important implication for portfolio construction. Historically, investors who were unwilling or unable to bear the full risk of the equity market could hedge by constructing a balanced portfolio of stocks and bonds. During the bull market in bonds that began in 1981, such defensive allocations did not require a major sacrifice in returns. If the bull market in bonds has ended, however, defensively minded investors might seek other ways of limiting their equity risk.

    Exhibit 2 shows that some factor indices would have dampened the S&P 500’s volatility in the first half of 2022; some even outperformed the bond market. Our intent in this paper is to explore what we can learn from the history of these indices. Which factors are best suited to providing defensive outcomes?

    Defense Beyond Bonds: Defensive Strategy Indices - Exhibit 2

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    The Hidden Costs of Retail Purchases in Municipal Bonds

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    Jason Giordano

    Director, Fixed Income

    Executive Summary

    • Despite recent innovations providing greater access to bond markets, the tax-exempt municipal bond investor base is still dominated by retail buyers.
    • Independent research on retail transactions has shown an average loss in income of 0.55%. In a low-rate environment, this number reflects a substantial potential disadvantage to retail bond buying.
    • These costs could potentially be avoided by accessing bonds through mutual funds or ETFs. ETFs have a distinct advantage in that shares of the fund can be exchanged without the need to incur any transactions in the institutional market.
    • In a low-yield environment, retail transaction costs can be a significant cause of erosion of potential returns.

    Hidden Risks

    Owning individual bonds has its risks and rewards.  However, buying a bond may also entail an unseen transaction cost that might not always be clear to purchasers.  This transaction cost exists because individual bonds are not typically sold with a commission.  Instead, a markup is built into the bond price.

    This report offers a transparent look at these hidden transaction costs for U.S. municipal bonds.  To determine these costs, we used large, recently issued investment-grade bonds tracked by the S&P National AMT-Free Municipal Bond Index and the S&P AMT-Free Municipal Index Series, and high-yield municipal bonds tracked by the S&P Municipal Bond High Yield Index, in conjunction with bond transaction data provided by the Municipal Securities Rulemaking Board (MSRB).  This information can help market participants compare the cost of buying individual bonds to the cost of investing in bond alternatives, such as mutual funds and ETFs.

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    An Index Approach to Factor Investing in India

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    Jason Ye

    Director, Strategy Indices

    Introduction

    Interest in factor investment solutions have significantly risen in the past decade.  In general, factor investing refers to an approach that targets stock characteristics that drive the difference in expected returns over the long term.  Sometimes, factor investing is referred to as smart beta, or strategic beta, because the factor approach will deviate the underlying portfolio from the market portfolio (the market beta) in a systematic method.  Some of the common factors that have been well documented in academic literature and adopted by the investment industry include low volatility, momentum, quality and value. Most of the evidence has been strong and promising that those factors can generate excess returns over the historical sample periods.  As of March 31, 2022, factor ETFs managed about USD 1.6 trillion assets globally, a 24.6% CAGR compared with the USD 178 billion 10 years ago.

    How did these factors perform in the Indian market?  Can investors access factor performance through an indexing approach?  What are some applications of factor indices in the Indian market?  In this paper, we introduce the S&P BSE Factor Index Series, which implements the factor investing framework through an indexing approach to reflect the performance of the low volatility, momentum, quality and value factors.

    In the following four sections, we provide brief descriptions of the S&P Dow Jones Indices (S&P DJI) approach to each of the common factors.  We will then provide an extensive discussion on the performance of the four factor indices, and a potential approach to combining the four factor indices to form an alternative for core equity allocation.

    In each of the introductory sections, we follow the same framework to present the factors.  The underlying index universe to construct the S&P BSE Factor Index Series is the S&P BSE LargeMidCap, which is designed to represent the top 85% of the total market cap of the S&P BSE AllCap.  The S&P BSE LargeMidCap was launched in 2015, with the first value available in September 2005, so we use back-tested historical data starting on Sept. 30, 2005, to study the full sample period performance of each factor.  Every six months, at month-end in March and September, we sort the constituents of the S&P BSE LargeMidCap in order by each factor.  We then form equal-weighted quintiles and market-cap-weighted quintiles from those sorted values, denoting Quintile 1 as the stocks with the highest exposure to the factor and Quintile 5 as the stocks with the lowest exposure.  We are interested in whether Quintile 1 generates better performance than Quintile 5.  The performance of Quintile 1 tends to be more important, especially for long-only investors.  We analyze the performance from both the annualized compound return and the risk-adjusted return perspectives.

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