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Indexing With Large Caps at the Core

Exploring Commodity Equity and Futures

The S&P 500 Equal Weight Index: A Supplementary Benchmark for Large-Cap Managers’ Performance Evaluation? – Part II

Proximate Cause

Some Bite-Sized Highlights from our Sectors Webinar

Indexing With Large Caps at the Core

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Koel Ghosh

Head of South Asia

S&P Dow Jones Indices

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The end of May 2018 marked another milestone in the history of ETF growth in global markets, with the total assets in ETFs crossing USD 5 trillion. Indian ETF markets are also growing significantly. The support from the Indian government via the Employees’ Provident Fund Organisation and Department of Investment and Public Asset Management, which are promoting investment in ETFs, has helped with the acceptance and adoption of passive investing.

However, with every investment decision comes planning and strategy. Asset allocation is important for a sound portfolio strategy. A core satellite approach has been adopted by many to achieve the necessary portfolio targets. In Indian markets, as active is a well-established strategy and passive is slowly getting a foothold, a combination of the two via core satellite can allow both strategies to be at play.

The large-cap space has long been established to contain companies with large market capitalization and stronger financials, which are understood to be stable and sometimes referred to as blue chip. The benchmark S&P BSE SENSEX consists of large-cap companies and many passive strategies and investment are linked to it today. The Indian market also hosts a wide range of active funds in this space. However, the SPIVA® India Scorecard has highlighted how the benchmark, in this case the S&P BSE 100, has outperformed active funds. It does make one wonder if, rather than going through the effort and spending time sorting through and picking an active strategy, isn’t it may be easier to replicate an index or follow an index fund or ETF?

Exhibit 1 is an example of the outperformance of the S&P BSE 100 over active funds in the past few years. The trend could compel one to think that it may be easier to take a low-cost, diversified, transparent, and flexible option.

An advantage of index-based investing is low concentration risk. For example, the S&P BSE 100 spreads across a broad basket of 100 securities diversified across sectors. For a more concentrated basket, the S&P BSE SENSEX 50 seeks to measure a group of 50 stocks, while the S&P BSE SENSEX seeks to track a set of 30 stocks. The S&P BSE SENSEX Next 50 is designed to measure the next 50 stocks from the same large-cap space beyond just the top 50 large caps.

Diversification can help with efficient risk management, as the exposure is not concentrated. An index measures a basket of securities, rather than a single stock, with an additional benefit of a wide sectoral exposure. Each of the S&P BSE LargeCap Indices provides exposure across 10 sectors, as per BSE sectoral classification, with various weights. Exhibit 2 demonstrates the sector weights of the S&P BSE LargeCap Indices, which are led by finance at over 30%, consumer discretionary and fast moving consumer goods (FMCG) at over 10%, and basic materials, industrials, and information technology with good shares as well.

Given that there is a variance in the sectoral balance in each of the large-cap indices, the performance of the indices varies and can provide options with different risk/return profiles. A look at the performance of the sectors in the last few years can help provide a perspective as to how the different sectoral exposures aggregate to a performance characteristic for the indices. Exhibit 3 demonstrates that while information technology was the outperforming sector in the one-year annualized return category, followed by energy, FMCG and finance were the leaders over the long term (i.e., 10 years).

Hence, using indices to measure market segments could provide a cross-sectoral exposure that enables strategies to benefit from diversification.

The indexing route is more diversified than single-stock approaches. Compared with active investing, the methodological approach to index design and consistency helps protect against fund manager bias. The exposure to the large-cap space via indexing as a core strategy offers a portfolio with risk/return characteristics similar to those of the indices.

Exhibit 4: Risk and Risk-Adjusted Returns of S&P BSE Indices
INDEX ANNUALIZED RISK (%) ANNUALIZED RISK-ADJUSTED RETURNS
3-YEAR 5-YEAR 10-YEAR 3-YEAR 5-YEAR 10-YEAR
S&P BSE SENSEX (TR) 13.56% 13.51% 20.83% 0.73 1.06 0.57
S&P BSE SENSEX 50 (TR) 13.44% 13.60% 21.26% 0.80 1.10 0.57
S&P BSE SENSEX 50 TMC (TR) 16.76% 18.20% 23.95% 0.81 1.00 0.64
S&P BSE SENSEX Next 50 (TR) 17.32% 18.32% 24.66% 0.57 0.96 0.51
S&P BSE 100 (TR) 13.71% 14.04% 21.84% 0.77 1.08 0.55
S&P BSE LargeCap (TR) 13.55% 13.80% 21.16% 0.75 1.06 0.56

Source: AIPL. Data as on June 29, 2018. Past performance is no guarantee of future results. Table is provided for illustrative purposes and reflects hypothetical historical performance. The S&P BSE SENSEX 50 was launched on Dec. 6, 2016. The S&P BSE SENSEX Next 50 was launched on Feb. 27, 2017. The S&P BSE SENSEX NEXT 50 TMC was launched on Apr 18, 2018.

Exhibit 5: Annualized Returns of S&P BSE Indices
INDEX ANNUALIZED RETURNS (%)
1-YEAR 3-YEAR 5-YEAR 10-YEAR
S&P BSE SENSEX (TR) 15.96 9.9 14.37 11.77
S&P BSE SENSEX 50 (TR) 15.1 10.75 15 12.22
S&P BSE SENSEX Next 50 (TR) 1.77 9.88 17.65 12.49
S&P BSE SENSEX Next 50 TMC (TR) 6.32 13.5 18.14 15.44
S&P BSE 100 (TR) 12.94 10.58 15.21 12
S&P BSE LargeCap (TR) 13.24 10.14 14.69 11.79

Source: AIPL. Data as on June 29, 2018, 2018. Past performance is no guarantee of future results. Table is provided for illustrative purposes and reflects hypothetical historical performance. The S&P BSE SENSEX 50 was launched on Dec. 6, 2016. The S&P BSE SENSEX Next 50 was launched on Feb. 27, 2017.The S&P BSE SENSEX NEXT 50 TMC was launched on Apr 18, 2018.

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

Exploring Commodity Equity and Futures

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Marya Alsati

Product Manager, Commodities, Home Prices, and Real Assets

S&P Dow Jones Indices

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In April 2017, S&P Dow Jones Indices launched the S&P GSCI Dynamic Roll Reduced Energy 70/30 Futures/Equity Blend. This index is designed to measure the performance of a multi-asset allocation strategy that consists of a futures-based commodities index and an equity index that is based on various commodity-related GICS® subsectors.

The futures portion is represented by the S&P GSCI Dynamic Roll Reduced Energy, which reduces the weight of energy relative to the other commodities in the index, compared with the production-weighted benchmark. It also utilizes a flexible futures contract rolling strategy based on the shape of the forward curve to alleviate the negative impact of rolling into contango and potentially limiting volatility exposure to the commodity market. The futures included in the index cover agriculture, energy, livestock, and industrial and precious metals.

The equity portion is represented by the S&P GSCI Sector Equities, which is designed to measure the performance of companies involved in agriculture and livestock, the exploration and production of industrial and precious metals, and the exploration and production of coal, gas, and oil.

In the past year, commodity futures and equities posted double-digit gains, with the S&P GSCI Sector Equities up 25.8%, the S&P GSCI Dynamic Roll Reduced Energy up 16.3%, and the blend up 19.1% (see Exhibit 1).

An index that includes both commodity equity and futures can provide more diversification than an index composed of only one asset class. As seen in Exhibit 2, the correlation between the assets was relatively low.

In terms of risk/return analysis, looking at the three-year period, the blended portfolio outperformed the commodity futures index, returning 1.7% compared with -1.5%. It also had a lower annualized risk, at 11.3%, compared with the 16.5% of the equity-only portion (see Exhibit 3).

Analysis of the indices’ inflation beta, which measures the sensitivity of an asset’s nominal prices to changes in inflation levels, showed that commodity futures and producers provided significant inflation protection. The futures-only index provided an inflation beta of 12.0, which indicated that the index historically increased 12% on average for a 1% increase in inflation. The commodity equity index’s inflation beta was 10.4, while the blend’s was 11.6%.

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

The S&P 500 Equal Weight Index: A Supplementary Benchmark for Large-Cap Managers’ Performance Evaluation? – Part II

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Aye Soe

Managing Director, Global Head of Product Management

S&P Dow Jones Indices

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In a prior blog, we demonstrated that the S&P 500® Equal Weight Index was a more difficult benchmark to outperform than the S&P 500 over intermediate- to long-term investment horizons. In this blog post, we examine the underlying factor exposures of the S&P 500 Equal Weight Index to evaluate the performance of large-cap managers.

As a starting point, we should note that by deviating from market-cap weighting, an equal-weight index generally displays a small-cap bias, value tilt, and higher portfolio volatility than a broad market-cap-weighted index. For example, the annualized volatility of the S&P 500 Equal Weight Index was 15.81% versus that of the S&P 500 at 14.18%.[1]

Next, to determine the underlying factor exposures of the indices, we regress the monthly returns of the two indices against the Fama-French factors’ returns, specifically the size, value, and momentum factors. We can see that the S&P 500 Equal Weight Index had higher exposure to the size and value factors and higher negative exposure to the momentum factor (see Exhibit 1) compared with its market-cap-weighted counterpart, the S&P 500.

All the factor coefficients were statistically significant at a 95% confidence level, with the exception of the size factor. These findings were not surprising, as several studies have noted similar results. A research paper by S&P Dow Jones Indices reached a comparable conclusion where the size and momentum factors acted as key drivers of the S&P 500 Equal Weight’s excess returns.[2]

Understanding the factor exposures of the S&P 500 Equal Weight Index allows us to consider a possible framework in which we can potentially evaluate the performance of large-cap active managers on a style-adjusted basis. To be fair, actively managed large-cap funds in our study generally benchmarked themselves against a market-cap-weighted large-cap index, such as the S&P 500 or the Russell 1000. Therefore, one can argue that the S&P 500 Equal Weight Index is not a natural benchmark for these managers, and that they are not managing their portfolios to deliver excess returns over the S&P 500 Equal Weight Index.

However, to the extent that a large-cap manager has an investment process to seek value exposure (or avoid overpaying in general) and to construct a well-diversified portfolio that reduces concentration risk, the underlying risk properties of the S&P 500 Equal Weight Index can be matched up against his/her portfolio. Therefore, we propose that the S&P 500 Equal Weight can serve as a secondary or a supplementary benchmark to the market-cap-weighted S&P 500 to measure the effectiveness of the strategy.

[1]   The annualized volatility is from Jan. 31, 1990 to May 31, 2018.

[2]   Edwards, T., Lazzara, C., Preston, H., and Pestalozzi, O. “Outperformance in Equal-Weight Indices.” S&P Dow Jones Indices LLC. January 2018.

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

Proximate Cause

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Craig Lazzara

Managing Director and Global Head of Index Investment Strategy

S&P Dow Jones Indices

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Our colleagues at S&P Global Market Intelligence recently completed a paper analyzing the impact of exchange-traded funds on stock-level pricing.  Their work found that “…the impact of ETF trading is transient and of only a modest magnitude under even extreme assumptions” (my italics).  This conclusion is a rebuttal to critics who believe that the growth of ETFs has distorted the capital markets and diminished market efficiency.

In our view, such criticisms conflate issues that all market participants face with issues that are uniquely attributable to index funds.  From the standpoint of formal logic, the critics confuse proximate with ultimate causation.

If index funds are net sellers on a day when the market is otherwise under pressure (e.g., February 8, 2018), their selling may well cause the market’s decline to be greater than it otherwise would have been.  That decline will be transmitted, to one degree or another, to each of the index’s component stocks.  In that sense, the liquidation of ETFs might be a proximate – i.e., immediate or near-term – cause of the decline in the values of most index components.

But ETFs are only one type of index vehicle, and index vehicles are only one type of investment portfolio.  Surely the ultimate cause of the decline in stock market values on February 8th was the desire of investors to reduce their equity exposure.  In any such environment, prices are likely to fall.  We would argue, in fact, that the existence of passive vehicles can actually mitigate the extent of a market pullback.

To see this, imagine that there were no index funds and that the ETF wrapper had never been invented.  In that environment, if investors decided to reduce their equity exposure, they would liquidate actively-managed portfolios rather than passive ETFs.  The extent of the overall selling would be the same but, since active portfolios are less diversified than index funds, the effect on individual securities would arguably be even greater (as those of us who remember October 1987 will readily concede).

Investors may or may not have been correct in their desire to reduce equity exposure on February 8th.  But to blame the role of ETFs, or of passive management generally, is a red herring.  ETFs are simply a more efficient way to do what investors wanted to do, and would have done, regardless.

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

Some Bite-Sized Highlights from our Sectors Webinar

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Hamish Preston

Associate Director, U.S. Equity Indices

S&P Dow Jones Indices

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We recently hosted a webinar examining the potential value in a sector-based approach to portfolio construction, their application in navigating different market environments, and some key considerations for those adopting sector-based strategies.  You can view a replay of the event here; a few highlights might whet the appetite…

The Global Importance of U.S Equity Sectors

In recent years, products such as futures and ETFs linked to U.S. sectors and industries have become increasingly popular.  The sheer size of the U.S. equity market means that investors hoping to gain exposure to certain market segments – either to offset the inherent sectoral biases present in their local market, or as part of a tactical allocation – will necessarily require exposure to the U.S.  For example, the U.S. accounted for the majority of market capitalization in 31 of 68 S&P Global BMI industries at the end of 2017.

Exhibit 1: Growth in popularity of S&P 500® sectors

The Outperformance Potential From Sectors

For investors adopting a sector rotation strategy, the potential benefit of favouring one sector over another is dependent on the differences in the returns to various sectors; the greater the difference, the greater the value of insight.  This is where dispersion is useful – it provides a gauge of the expected difference in returns across sectors.  Historically, the average monthly dispersion among S&P 500 sectors has been 3.11%, which compares to 6.82% for S&P 500 stocks.  It might therefore be said that roughly half of the value of stock picking could have been accessed through successful sector-selection.

Exhibit 2: S&P 500 Stock Dispersion vs Sector Dispersion

Rotate Don’t Retreat!   

Trade tensions, a flattening yield curve, and political uncertainty in several markets have induced some market participants to cut positions, waiting for the risks to “blow over”.  But leaving the equity market altogether can mean missing out on returns.  A potential alternative is to use sector rotation strategies to manage risk.  While remaining fully invested in equities, changing the sectoral mix of an equity portfolio can have an impact on performance that is comparable to swapping out equities for Treasury bonds.  

Exhibit 3: Sector changes within an existing equity allocation can be comparable to switching between equities and bonds.

Consider the Macroeconomic Environment

Companies with shared sensitivities to particular economic factors are often found in the same sector.  For example, the Financials sector tends to outperform in periods of rising inflation, while the Utilities sector tends to falter.  Macro-economic considerations may help to inform which market segments might benefit from identified trends, or diversify risks within a pre-existing portfolio.

Exhibit 4: Sectors and Macroeconomic Factors

This last chart was provided by Rebecca Chesworth from SSGA, who joined our webinar along with Sam Stovall from CFRA.  The full replay of the event – and a discussion of all of these charts (and others) – may be found at this link.

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