Indexology^® Blog

In our two previous blogs on risk parity 2.0 (see here and here), we covered the philosophy and methodological differences between the original S&P Risk Parity Indices and the newly launched S&P Risk Parity 2.0 Indices. This third and final installment of this series now looks at the performance and attribution statistics of the S&P Risk Parity 2.0 Indices, specifically the S&P Risk Parity 2.0 Index – 10% Target Volatility.

As Exhibits 1 and 2 show, the performance of the S&P Risk Parity 2.0 methodology compares favorably to that of the original risk parity indices and significantly outperformed actively managed funds, as measured by the HFR Risk Parity Vol 10 Institutional Index.

The last decade and a half have had no shortage of interesting market events, as the 36-month realized volatility graph in Exhibit 3 underscores. The onset of the Global Financial Crisis in September-October 2008 showed a spike in volatility initially, but then largely flattened out (dropping closer to the “target” as the 36-month window rolls off). Realized volatility stayed in a downtrend for much of the ensuing decade, before once again moving higher during the pandemic.

Drawdown periods and performance were similar across the indices. While the S&P Risk Parity 2.0 Index performed better in Q4 2018 and March 2020 than the other indices, it lagged slightly during the Global Financial Crisis.

As expected, leverage for the S&P Risk Parity 2.0 Index dropped during these periods of volatility. Leverage reached the life-to-date max of 263.9% in November 2007, before falling to the lifetime low of 228.7% in August 2009. After slowly growing over the next decade, it reached a high of 257.5% before the start of the COVID-19 pandemic, and subsequently retreated ~10% over the next few months.

Exhibit 5 shows these leverage drops and the allocated asset class weights over time. The relative commodities and Treasury inflation-protected securities (TIPS) notional allocation have slightly but steadily decreased since inception, with that weight largely being reallocated to fixed income.

Finally, the core of risk parity is neatly displayed in Exhibit 6. While the notional asset allocation is dominated by fixed income, the lower volatility of that asset class translates into a far smaller risk attribution. On the other hand, commodities necessitate a far smaller notional share to satisfy its allocated risk budget. Following the largely downward trend of interest rates globally during this period, fixed income provided the lion’s share of returns, with equities in second place. TIPS, by nature a hybrid instrument that reflects interest rates and inflation/growth expectations, were largely stable across all three metrics.

Today is the 125^th Boston Marathon—a big day in the world of distance running. Organized by the Boston Athletic Association (BAA), it is perhaps the pre-eminent annual event on the global marathon calendar. The 20,000 runners in today’s race were selected in May 2021, around the same time S&P DJI rebalanced the constituents of the S&P 500^® ESG Index. What does one have to do with the other? More than you’d think.

The way S&P DJI and the BAA determine eligibility and eventual selection for these two fields of competitors is strikingly similar. They both start with an overall universe of candidates, apply a transparent rules-based screening process to determine eligibility, and compare potential constituents to their peers in a math-based selection process.

The Objective

The S&P 500 ESG Index is designed to measure securities from the S&P 500 that meet sustainability criteria while maintaining similar overall industry group weights as the underlying index.

The Boston Marathon comprises a field of marathoners that is faster than the broader universe of runners but is still reflective of the overall runner population. It achieves this by maintaining similar gender and age group diversity to the applicant field.

The Eligibility Universe

To be included in an index or a marathon, one must first be eligible. Both begin with a broad universe of constituents and whittle things down from there. For the S&P 500 ESG Index, that universe is the S&P 500. For the Boston Marathon, it’s all runners who have completed a certified marathon in the 12 months before the application period. Both are broad but already impressive fields.

The Screening Process

S&P DJI first eliminates companies involved with certain business activities, companies with disqualifying UN Global Compact Scores, and companies with ESG scores in the bottom 25% of their Global GICS^® industry group. The remaining companies form the S&P 500 ESG Index eligibility universe.

The BAA eliminates runners who do not meet the time qualifying standards, which vary depending on the runner’s age and gender. All runners who meet their respective qualifying times are eligible for the Boston Marathon.

The Selection

Here’s where the S&P 500 ESG Index and Boston Marathon methodologies become eerily similar. In both cases, just because you meet the eligibility criteria does not mean you are ultimately selected for inclusion.

S&P DJI goes through each GICS industry group and selects the highest-performing companies by ESG score until as close to 75% of the group’s market cap is reached. Once complete, the S&P 500 ESG Index is formed.

The BAA goes through each gender’s age group and selects the fastest applicants first until the entry limit for each group is reached. Once complete, the field of Boston Marathon runners is set.

It’s All Relative

The common theme between the S&P 500 ESG Index and the Boston Marathon selection processes is the way eligible constituents are ranked against their peers. For the index, it’s not how high your ESG score is, but how high your ESG score is within your industry group. And for the Boston Marathon, it’s not how fast you are, but how fast you are relative to your gender and age group peers.

That’s why it’s difficult to predict each year which companies will make it into the S&P 500 ESG Index and which runners will get to run the Boston Marathon. Every year the scores and finish times are different—we don’t know who makes the cut until we can compare everyone.

Rising Standards

As distance running has surged in popularity, it has become increasingly difficult to get into the Boston Marathon. The race has served as a proverbial carrot that encourages runners to train harder, and the result has been faster entry times and higher qualifying standards.

ESG investing is also surging in popularity, as market participants across the globe are increasingly prioritizing investments that align with their values. This, in turn, has had the desirable effect of increased engagement from companies through greater transparency and implementation of sustainable business practices. Benchmarks such as the S&P 500 ESG Index look to further encourage this trend and make the competition for inclusion tougher each year, as companies increase their ESG adoption.

The broad-based S&P GSCI started Q4 2021 off with a bang; as of October 5 it was up 3.9% for the month and 44% YTD. The spot version of the index has reached its highest level since October 2014. Natural gas and the petroleum complex have continued their dominance of the commodity charts, filling out the top six spots among S&P GSCI constituent performances for the month. However, they all pale in comparison to U.K. and European natural gas prices, which currently sit outside the S&P GSCI single commodity series. The S&P GSCI Natural Gas, which seeks to track the performance of U.S. natural gas prices, was up 137% YTD, while benchmark U.K. natural gas prices have more than quadrupled since the beginning of June, and Dutch gas prices have risen nine-fold since the beginning of the year.

Record natural gas and electricity prices in Europe, record coal prices in China, multi-year highs in natural gas prices in the U.S., and Brent crude prices tipping USD 82/barrel are all manifestations of a global energy shortage that has come into sharp focus over recent weeks. Supply chains are stretched, in some cases broken, and energy stockpiles are abnormally low. Unusual weather has worsened the energy supply crunch, while ambitious climate plans and a growing reliance on renewable energy sources have further complicated the situation. However, energy crises are not a new phenomenon. The challenge this time around is that the global economy is recovering more quickly than expected from a once-in-a-generation economic shock while most countries are simultaneously ramping up their commitment to the energy transition and a net-zero carbon future.

Arguably, the market is doing its job; prices and volatility have spiked in an attempt to destroy sufficient demand to protect depleted inventories. European gas and electricity prices are now signaling the need for urgent factory closures in order to reduce gas consumption. For manufacturers, shutdowns have the effect of cutting energy costs, but they can also drive up the price of their products, which in turn may see inflation worries bleed from energy to other sectors of the economy.

European importers have been locked in competition with Asian buyers to attract extra liquefied natural gas cargoes, while pipeline deliveries from Russia have so far failed to respond to higher prices. China is facing an electricity squeeze of its own from a shortage of coal supplies, tougher carbon emissions standards, and strong post-pandemic demand from manufacturers and heavy industry, which have triggered widespread curbs on usage.

Physical commodities markets are prone to exaggerated price moves in both directions, and the high prices and associated levels of extreme volatility across the energy complex reflect an acute shortage of the raw materials needed to produce the energy that powers every aspect of the global economy. How long the situation takes to revert, or at least stabilize, remains to be seen, but this is yet another example of the importance of appreciating the role of commodities in the broad financial ecosystem, even for those market participants who have no intention of trading European natural gas.

When people talk about indexes, they are usually referring to market-cap weighted indexes.

Market-cap weighting is based on price and outstanding number of shares. One simply takes the number of shares outstanding and multiplies them by the share price to arrive at market cap. This calculation results in the biggest companies commanding the largest weights.

The first goal of the S&P Global QVM Multi-Factor Index is to “break the market-cap link” that many indices utilize.

Instead of weighting by market capitalization, the index – and a fund based on the index — holds all companies with a nearly equal weighting. This accomplishes a few objectives.

First, it provides broader diversification across the REIT sector by avoiding the index constituents being concentrated in only a handful of names. Second, it favors smaller companies relative to market-cap weighted indexes by giving them the same weighting in the index as large-cap firms. Lastly, the index also may tilt towards value.

So, what’s the real benefit of these steps as manifested in risk-adjusted returns?

To answer that, below we compare three approaches to the REIT sector. First, we’ll examine market cap weighted U.S. REITs; second, we’ll expand to include market cap weighted global REITs; and third, we’ll look at global REITs with the aforementioned factors – in other words, S&P Global REIT Quality, Value & Momentum (QVM) Multi-Factor Index.

As you’ll see, for similar volatility levels using back-tested data with respect to the periods listed below, the S&P Global REIT Quality, Value & Momentum (QVM) Multi-Factor Index experienced a few percentage points of additional performance over U.S. and global REITs, with similar or lower levels of volatility and drawdowns.  Index performance does not equal fund performance because one cannot invest directly in an index, and index performance does not reflect management fees, trading costs and other expenses.

How REITs Can Affect a Broader Investment Portfolio

Does a REIT allocation add any benefit to a traditional equity/fixed income portfolio?

Below is a sample hypothetical 60/40 portfolio composed of U.S. stocks as represented by the S&P 500 and U.S. 10-year government bonds, back-tested with monthly rebalances.  In the second column, a hypothetical allocation of 20% of REITS as represented by the constituents of the S&P Global REIT Quality, Value & Momentum (QVM) Multi-Factor Index has been introduced.

The historical back-tested data results for this time period show an increase of over 1.3% in annual performance. The REIT allocation does increase volatility slightly, but the end result is a higher portfolio Sharpe Ratio.

To learn more about the S&P Global REIT Quality, Value & Momentum (QVM) Multi-Factor Index, it’s described in greater detail in Part I and Part II. See also the methodology.

Disclaimer:

The views and opinions of any third-party author are his/her own and may not necessarily represent the views or opinions of S&P Dow Jones Indices or any of its affiliates.

This blog is the second in a three-part series introducing the S&P Risk Parity 2.0 Indices. The first blog highlighted the differences between these new indices and the original ones. In this installment, we will take a closer look at the methodology of the newly launched S&P Risk Parity 2.0 Index Series.

Constituent Changes

Incorporating TIPS

Although commodity prices tend to increase in value with rising inflation, many investors prefer to have a more explicit inflation hedge. Treasury inflation-protected securities (TIPS) are designed to increase in value to keep pace with inflation. Their principal is tied to inflation and interest is paid based on the adjusted principal.

In this index series, the S&P U.S. TIPS 7-10 Year Index was selected to represent TIPS. U.S. TIPS are typically liquid, especially across the 7-10-year maturities, which are of similar tenors to several of the other fixed income constituents included in the index.

TIPS as a Fourth Asset Class

When including TIPS in the index, thought had to be given as to how to position them—namely whether they should be bucketed with another asset class or stand alone. TIPS are not expected to react in similar ways to changes in growth and inflation as the other three asset classes (equities, nominal bonds, and commodities). But there were several other considerations when deciding whether to bucket with another asset class (i.e., comparison of volatilities, weighting approach, and impact on overall risk/return characteristics and leverage).

Overall, given the unique characteristics of TIPS, it was deemed most appropriate to include them as a separate asset class. Therefore, the S&P Risk Parity 2.0 Indices include four asset classes: equities, nominal bonds, commodities, and TIPS.

Allocation Changes

Marginal Contribution to Risk

Now that the S&P Risk Parity 2.0 Indices include TIPS, which have a 60-70% correlation with nominal bonds, Marginal Contribution to Risk (MCTR) is deemed a more comprehensive risk measure. It accounts for both correlation and volatility to assess the risk of each asset class in terms of its contribution to the overall portfolio.

Budgeted Risk Allocation

As part of the index design process, different risk budgets (such as 10%, 15%, 20%) were evaluated for TIPS. This analysis, as well as input from several market participants, led to the decision to allocate 15% risk to TIPS, with the remaining 85% risk split equally among equities, nominal bonds, and commodities.

Limiting TIPS to 15% was deemed most appropriate since it reduced the combined exposure to bonds (nominal and inflation-linked) as well as the overall leverage while still providing sufficient exposure to meaningfully contribute and to provide an inflation hedge.

Equal Notional Weights within Nominal Bonds

Within the nominal bonds asset class bucket, 10-year JGB futures have the lowest volatility and correlation to other bond futures. If the risk is allocated equally across the constituents, roughly one-third of the asset class weight is allocated to JGB. Furthermore, it leads to a substantial increase to the asset class weight and to the overall leverage. To prevent this, the constituents in the nominal bond asset class bucket are equally weighted.

In the next blog, we will discuss the performance of these newly launched indices.