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Getting to Know the S&P BSE 500

The S&P Risk Parity Indices: Risk Contribution Versus Capital Allocation

Juxtaposition and Paradox

Puerto Rico Bonds: A Surging Force

Equal-Weight Versus Equal-Risk-Contribution Strategies – Performance Comparison

Getting to Know the S&P BSE 500

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Mahavir Kaswa

Former Associate Director, Product Management

S&P BSE Indices

Over the past three to four decades, the Indian equity market has witnessed significant growth, on account of increasing foreign capital flows and participation by domestic institutional investors. The expanding depth and breadth has brought a stronger demand from market participants for suitable benchmarks. The S&P BSE SENSEX launched in 1986 and was the first and most popular Indian benchmark, followed by the S&P BSE 100 and S&P BSE 200 in 1989 and 1994, respectively. In 1999, the S&P BSE 500 was launched in response to market demand for broader benchmarks that offer more complete coverage of the Indian equity market.

The S&P BSE 500 is designed to be a broad representation of the Indian equity market, consisting of the 500 leading companies in terms of total market capitalization that are members of the S&P BSE AllCap. The differential voting rights shares class is eligible to be part of the index, which means that at any point in time, the index will include a fixed number of 500 companies, but the number of stocks in the index could be greater than or equal to 500. The index constituents and sectors are weighted in proportion to their float market capitalization. The index is reviewed semiannually in June and December.

In a recently published paper titled “Measuring Indian Equities: The S&P BSE 500,” we saw that as of April 30, 2018, the S&P BSE 500 represented approximately 88% of all BSE-listed companies, with a total market capitalization of INR 1,35,14,943 crores (approximately USD 2 trillion).

The S&P BSE 500 is diversified across sectors, and no individual sector had an excessive overweight in the index in the period studied. As shown in Exhibit 1, the financials sector had the highest weight in the index, with 30%, followed by consumer discretionary at 12.5%. The services sectors, which include financials, information technology, and telecommunications services, contributed nearly 41% to the total index weight. Also, the combined weight of constituents that have individual derivative contracts was 87%, which facilitates risk management of the index.

Similarly, the S&P BSE 500 offers exposure to all size segments. Large-cap stocks accounted for 79% of the total index weight, mid caps 13%, and small caps 8% as of April 30, 2018 (see Exhibit 2).

With coverage of more than 88% of India’s listed equity universe and diversified exposure to all sizes and all key economic sectors of India’s economy, the S&P BSE 500 seeks to provide comprehensive coverage of the Indian equity market.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

The S&P Risk Parity Indices: Risk Contribution Versus Capital Allocation

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Berlinda Liu

Former Director, Multi-Asset Indices

S&P Dow Jones Indices

In a prior blog, we showed that the S&P Risk Parity Indices tracked the average performance of active risk parity funds closer than a traditional 60/40 equity/bond portfolio. In this second part of the blog series, we will examine the risk contribution and capital allocation of these indices.

The principles behind risk parity strategies relate to answering a deceptively straightforward question: What is diversification? Traditionally, investors have allocated their capital across multiple asset classes to achieve diversification, such as the 60/40 equity/bond blend. A previous blog by Phillip Brzenk showed that such an approach led to a disproportionate allocation of risk across asset classes, with equities occupying almost all of the portfolio risk. A risk parity strategy, on the other hand, aims for balanced risk contribution from all asset classes. A proper risk parity benchmark should demonstrate roughly equal risk contribution from all asset classes.

Exhibit 1 shows the back-tested historical risk contribution of the S&P Risk Parity Index – 10% Target Volatility. Over the past 14 years, equities, fixed income, and commodities have contributed roughly the same amount of volatility to the portfolio, despite some fluctuations over time. We can see that the risk contribution of the different asset classes varies based on different market environments. This is not surprising, as we use realized volatilities as the risk measure in the index methodology. For example, in 2008, when the equity market was experiencing a bear market, the risk contribution by equities reached an all-time high of 42.79%. After the volatility seen in 2008 was included in the realized volatility calculation, equity risk contribution subsided to 33.99% in 2009, close to the one-third risk attribution expected in a risk parity portfolio. Despite fluctuations in annual risk attributions, the three asset classes contributed almost equally to the portfolio volatilities over time, either measured as mean or median (see Exhibit 1).

As seen in Exhibit 2, the historical capital allocation verifies that equal risk allocation did not lead to equal capital allocation. Fixed income, the least volatile asset class among the three, has the largest capital allocation to ensure its equal risk contribution to the portfolio. During the 14-year back-tested period, about 60% of the capital was allocated to fixed income securities (mean = 60.0%, median = 62.3%). The remaining 40% of the capital was split between equities (mean = 19.8%, median = 18.2%) and commodities (mean = 20.2%, median = 19.7%) almost evenly. The allocations among the three asset classes were fairly stable over time.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Juxtaposition and Paradox

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Anu Ganti

U.S. Head of Index Investment Strategy

S&P Dow Jones Indices

Effective prior to the market open on Sept. 24, 2018, the Telecommunication Services sector will be replaced with a new Communication Services sector, which will combine telecom with parts of the Information Technology and Consumer Discretionary sectors.

As a result, Telecom, the ugly duckling sector comprising three stodgy telephone companies, will now be joined by companies including Alphabet, Facebook, and Netflix. Given the addition of these younger juggernauts in the social media space, one might assume that the volatility of the new Communication Services sector would skyrocket. However, this is paradoxically not the case, and we can understand why using the lens of dispersion and correlation.

When comparing pro-forma indices with their current counterparts, we find that Consumer Discretionary and Info Tech’s historical dispersion and correlation levels are about the same. But when we look at Telecom versus the pro-forma Communication Services sector, as seen in Exhibit 1, we discover that the dispersion of Communication Services is consistently higher than that of Telecom. This is not a surprising outcome, given that the number of constituents increases from the current three and includes such names as Alphabet and Facebook, which have little in common with traditional telephone utilities.

Moreover, as seen in Exhibit 2, the correlation of Communication Services is generally lower than that of Telecom. This result is again not surprising, given the fundamental differences between phone companies and the new names coming into the new sector.

These findings have important implications for how the volatility of pro-forma Communication Services compares with that of Telecom, as volatility manifests itself in both dispersion and correlation. As shown by Exhibit 3, over time, the volatility of pro-forma Communication Services is roughly equal to that of Telecom. This results from the juxtaposition of two opposing forces: Communication Services’ higher dispersion, which drives volatility higher, is balanced by its lower correlations, which pull volatility lower. This is indeed an unexpected and notable outcome.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Puerto Rico Bonds: A Surging Force

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Kevin Horan

Former Director, Fixed Income Indices

S&P Dow Jones Indices

After wreaking havoc on the municipal bond markets, Puerto Rico bonds have recently been adding value through their recovery. Bonds rallied after the latest debt restructuring deal was struck between the commonwealth and the bond holders. Additional supporting news, as mentioned in an article from Reuters,[1] was a federal court ruling affirming the budgetary powers and enforcement of fiscal discipline by the federal oversight board that was created by the 2016 federal PROMESA Act.

These recent developments have led to positive returns for indices containing Puerto Rico bonds. As of Aug. 20, 2018, the S&P Municipal Bond Puerto Rico Index returned 25.4% YTD and the S&P Municipal Bond Puerto Rico & Defaulted Index returned 61% YTD.

The S&P Municipal Bond High Yield Index, which contains Puerto Rico bonds (with a weight of 9.3%), returned 5.72% YTD, while the S&P Municipal Bond High Yield ex Puerto Rico Index returned 3.64% YTD—2% less for excluding Puerto Rico bonds.

The S&P Municipal Bond Defaulted Index is a universe of bonds considered to be in monetary or technical default. Defaults are currently 0.70% of the broad benchmark S&P Municipal Bond Index, averaging 0.26% over the history of the two indices. This ratio has been as low as 0.09% during the summer of 2015 and as high as 0.79% from Sept. 13 to Sept. 18, 2017.

The month-end rebalance for September 2016 saw the market value of the default index jump from USD 1.7 billion to USD 7.6 billion, as 110 bonds (92 of which were Commonwealth of Puerto Rico bonds) moved into the default realm. Index rebalancings similar to September 2016 also occurred Jan. 31 and July 31, 2017.

Currently Puerto Rico bonds account for 92% of the default index, so as Puerto Rico bond prices go, so goes the S&P Municipal Bond Defaulted Index, which is up 15.4% MTD as of August 20, 2018.

As mentioned in a Seeking Alpha article, “Muni bonds, in general, are second only to U.S. Treasuries in terms of perceived safety. Headline-grabbing though the above cases may be, municipal bond defaults remain extremely rare. In the period from 1970 through the end of 2015, out of the thousands of muni bonds issued across the country, there were just 99 defaults. That translates into an annual default rate of 0.09% for all-rated municipal bonds throughout the 46-year period. In fact, investment grade “Aaa” and “Aa” rated munis experienced zero defaults.”[2]

[1]   Reuters, “Puerto Rico bond prices surge as restructuring deals struck

[2]   Seeking Alpha, “Municipal Defaults, While Rare, Do Occur

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Equal-Weight Versus Equal-Risk-Contribution Strategies – Performance Comparison

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Phillip Brzenk

Managing Director, Global Head of Multi-Asset Indices

S&P Dow Jones Indices

As we highlighted in a prior blog post, the risk decomposition of a multi-asset equal-weight portfolio showed that equities and commodities were the main contributors to total portfolio volatility. We then went on to explore what the weights would have been if we were to form an equal-risk-contribution portfolio consisting of the same assets.

In this post, we review the performance of an equal-weight portfolio against an equal-risk-contribution portfolio, starting in 2000. Exhibit 1 shows historical annualized return and annualized volatility for both portfolios for several lookback time horizons.

When determining the weights in the equal-risk-contribution portfolio, we set the target portfolio volatility to be equal to the realized portfolio volatility of the equal-weight portfolio from the prior year, subject to a maximum of 10%. Hence, the realized historical volatilities of the two portfolios are similar. This is particularly interesting given the fact that the equal-risk-contribution portfolio’s total nominal weights averaged over 200%.[1]

We can see that the returns for the equal-risk-contribution portfolio were higher than those of its equal-weight counterpart across all measured periods. The long-term horizons (10 years and 17 years), covering periods of bear market(s) in equities and commodities, show relatively high return spreads, which led to substantially higher risk-adjusted returns. We also compute the rolling three-year annualized returns (see Exhibit 2).

The two portfolios performed similarly in some periods, while in others the equal-risk portfolio noticeably outpaced the equal-weight portfolio. In fact, the equal-risk portfolio outperformed the equal-weight portfolio 84% of the time, by an average of 5.51%.

Over the last several posts, we have demonstrated the merits of constructing multi-asset risk parity portfolios. Compared to an equal-weight multi-asset portfolio, a risk parity portfolio can potentially lead to superior returns on an absolute and risk-adjusted basis. In related future posts, we will take a deeper dive into the S&P Risk Parity Indices.

[1] See Equal-Weighting Versus Equal-Risk-Weighting Strategies

The posts on this blog are opinions, not advice. Please read our Disclaimers.