Indexology^® Blog

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%.

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.

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 8^th 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 8^th.  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.

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 Association of Southeast Asian Nations (ASEAN) region is well known for its growth potential among market participants who seek to diversify their exposure within emerging markets. ASEAN originally consisted of Indonesia, Malaysia, Philippines, Singapore, and Thailand. It then expanded to include Brunei, Cambodia, Laos, Myanmar, and Vietnam. Within ASEAN, the World Bank classifies Singapore and Brunei in the high-income category, while the others fall under the middle-income group. For emerging markets exposure, middle-income markets with relatively higher growth and a sizable GDP generally have an attractive diversification benefit. Within the middle-income ASEAN markets, the GDPs of Indonesia, Malaysia, Philippines, Thailand, and Vietnam were well over USD 100 billion in 2009 and have been growing steadily (see Exhibit 1). Let’s take a closer look at the characteristics of these five markets.

The global competitiveness index (which determines the level of productivity, the state of public institutions, and the technical conditions) of these five markets has either remained stable or improved since 2008-2009 (see Exhibit 2). An improvement in rank points to a favorable business and political environment in relation to other markets.

The market capitalization of the listed domestic companies as a percentage of GDP has been growing steadily and was more than 50% for all the markets in 2017 (see Exhibit 3). The growth of the stock markets kept pace with the growth in the GDPs of these markets, indicating a balanced development of the public market in relation to the overall capital market.

Brazil, Russia, India, China, and South Africa (BRICS) make up another standard group of emerging markets that may provide diversification benefits. The emerging ASEAN markets had no more than 70% correlation with individual BRICS markets (see Exhibit 4), demonstrating the possible diversification benefit from treating it as a separate asset class.

Based on these observations, it’s no surprise that market participants looking for growth potential and diversification have shown increased interest in emerging ASEAN markets.