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Introducing the S&P QVM Top 90% Multi-factor Indices

Examining a Custom Approach to Factors

Commodities Rise with Inflation in July

Has the Illiquidity Trade Run its Course?

A Hypothetical Look at 35 Years of Indexes that “Buy” SPX Options

Introducing the S&P QVM Top 90% Multi-factor Indices

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Rupert Watts

Head of Factors and Dividends

S&P Dow Jones Indices

Earlier this year, S&P DJI launched three S&P Quality, Value, and Momentum Top 90% Multi-factor Indices (the “S&P QVM Top 90%” Indices) across our large-cap, mid-cap, and small-cap universes. Each of these indices is tracked by an ETF.

Compared to S&P DJI’s other flagship multi-factor indices, this new series represents a differentiated approach to multi-factor index construction because it selects a high percentage of the universe and weights proportionally to float market cap. Based on internal back-tested research, this approach historically demonstrated moderate outperformance while retaining many of the core benchmark characteristics.

Methodology Overview

The S&P QVM Top 90% Indices are designed to track companies in the top 90% of their respective underlying index universe, ranked by their multi-factor score, which is based on the average of three separate factors: quality, value, and momentum.

Back-tested data shows that removing the lowest-ranked decile led to performance improvement. Exhibit 1 shows the cap-weighted return of each decile in the S&P 500®. Here, stocks have been ranked by their multi-factor score, placed into deciles (D1 = the lowest ranked, D10 = the highest ranked), and rebalanced quarterly.

For the S&P 500, the lowest-ranked decile exhibited the lowest performance over the period tested. Similarly, for the mid- and small-cap universes, the bottom decile has been the lowest, or close to lowest, performing decile.

Moreover, removing only the lowest decile also resulted in improved returns over the benchmark at relatively low tracking error. Exhibit 2 plots the ratio between excess returns over the S&P 500 and its resulting tracking error for a series of indices, each differentiated by the number of deciles removed. For example, T90% removes only the lowest-ranked decile (ranked by multi-factor score), T80% removes the two lowest-ranked deciles (i.e., the 20% lowest-ranked stocks), and so on.

Generally, as further deciles were removed from the back-tested strategy, the increase in tracking error did not result in proportional gains in excess returns. This is represented in Exhibit 2 by the slope of the line.

Headline Performance Statistics

The index construction methodology is such that the potential for substantial outperformance over the benchmark is limited, but so is the risk of significantly underperforming. Exhibit 3 shows the back-tested risk/return statistics for each of the S&P QVM Top 90% Indices. Since the start of the back-test period, the large-, mid-, and small-cap S&P QVM Top 90% Indices outperformed their benchmarks by 74, 107, and 107 bps per year, respectively, each with low tracking error.

Benchmark Characteristics

Removing only the lowest-ranked decile and weighting stocks proportionally to float market capitalization results in the S&P QVM Top 90% Indices having retained many of the qualities of the underlying benchmark. The back-tested analysis in Exhibit 4 shows that the active share, tracking error, and turnover historically remained low across the cap range.

Conclusion

The design of multi-factor strategies affects the expected performance characteristics and impacts positioning within a portfolio. For the S&P QVM Top 90% Indices, the construction methodology demonstrates moderate outperformance while retaining “benchmark-like” characteristics.

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

Examining a Custom Approach to Factors

How does viewing companies through the prism of price-to-sales influence risk/return? Explore a systematic approach to indexing factors with a focus on valuations with Justin Lowry, President and Chief Investment Officer at Global Beta Advisors and S&P DJI’s Michael Mell.

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

Commodities Rise with Inflation in July

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Jim Wiederhold

Former Director, Commodities and Real Assets

S&P Dow Jones Indices

The S&P GSCI rose for a fourth consecutive month, by 1.6% in July, as the main positive catalysts of 2021 remained in play. Many individual commodities constrained by supply chain bottlenecks and disruptions continued to be in deficit around the world. Half of the U.S. experienced drought conditions last month, compared to 25% this time last year. Reopening and reflationary demand continued to pick up. Inflation readings were again released higher than expected. Everyone has a story about something being more expensive than it was a year ago. The Fed maintained its dovish supportive posture that inflation is transitory. A concern on market participants’ minds was how disruptive the spread of the Delta variant of COVID-19 might get and if it could cool off the outstanding YTD performance of commodities. Exhibit 1 shows the performance of the S&P GSCI by sector, with Energy and Industrial Metals outperforming YTD and July performance muted overall.

Within Energy, the S&P GSCI Unleaded Gasoline rose 4.54%, beating out heating oil as the top performer in the petroleum complex. Summer driving demand in the northern hemisphere continued to be one of the key drivers for gasoline. The S&P GSCI Natural Gas broke higher by over 7.71% in July. The U.S. Energy Information Administration reported that Natural Gas makes up 40% of annual U.S. electrical generation. It is a key commodity to watch in the global energy transition, as it is viewed as a less carbon intensive commodity than other, higher emitting ones. Another interesting note from the report showed renewables now make up 21%, beating out nuclear and coal-based generation for the first time ever. The green transition continues to be one of the key thematic stories inspiring commodity price action.

The S&P GSCI Nickel led the way for the metals, rising 7.34% on the month. Mostly used to create stainless steel, Nickel is also used extensively in electric vehicles. Most electric vehicle metals edged higher in July, as new competitors to Tesla drove enthusiasm in the space. Preorders for new electric vehicles exploded, with many people willing to wait to own a new electric vehicle as opposed to paying current inflated used car prices. This helped to push the S&P GSCI Copper up 3.59% for the month. Four times as much copper is needed in the average electric vehicle as is needed in the average internal combustion engine vehicle. Copper was also influenced from the supply side with the potential for a strike coming as labor talks broke down at BHP’s Escondida copper mine in Chile, the world’s largest copper mine.

Across Agriculture & Livestock, the Softs stood out. The S&P GSCI Coffee sprinted past the rest, rising 12.04% due to extreme frost conditions, erasing 10% of Brazil’s crop production for the year. Brazil is the number one coffee producer in the world, with a 40% share of global output, double that of the next highest producer. The S&P GSCI Corn fell the most, down 8.72% as the highly liquid CME July contract expired, with traders taking profit or moving exposure to the December contract. The S&P GSCI Lean Hogs rose another 1.20% in July, bringing the YTD performance to an impressive 29.24%. No matter if the pandemic gets worse or tapers off, everyone still wants to bring home the bacon.

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

Has the Illiquidity Trade Run its Course?

S&P Global Market Intelligence’s Lynn Bachstetter explores whether illiquidity still has a place in insurance investments with S&P Global Ratings’ Carmi Margalit, F&G’s Leena Punjabi, and BlackRock’s Peter Gailliot.

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

A Hypothetical Look at 35 Years of Indexes that “Buy” SPX Options

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Matt Moran

Head of Index Insights

Cboe Global Markets

35 Years of Hedging Indices

Below are three Cboe S&P benchmark indices that theoretically “buy “SPX put options as part of their index methodology and have 35 years of back-tested performance history going back to June 30, 1986.  As shown below, the three options indices were introduced in either 2008 or 2015, and the data histories before the introductions are back-tested.

  • Cboe S&P 500 5% Put Protection Index (PPUTSM) tracks the performance of a hypothetical strategy that holds a long position indexed to the S&P 500 Index and buys a monthly 5% OTM SPX put option as a hedge. The PPUT Index was introduced in 2015.
  • Cboe S&P 500 95-110 Collar Index (CLLSM) tracks the performance of a strategy that purchases stocks in the S&P 500 Index, and each month sells SPX call options at 110% of the index value, and each quarter purchases SPX put options at 95% of the index value. The CLL Index was introduced in 2008.
  • Cboe S&P 500 Zero-Cost Put Spread Collar Index (CLLZSM) tracks the performance of a hypothetical option trading strategy that 1) holds a long position indexed to the S&P 500 Index; 2) on a monthly basis buys a 2.5% – 5% SPX put option spread; and 3) sells a monthly OTM SPX call option to cover the cost of the put spread. The CLLZ Index was introduced in 2015.

Histogram and Less Tail Risk

The histogram chart shows that the methodology element of theoretically “buying” of puts by the PPUT Index helped lessen the left tail risk when looking at back-tested data over 35 years. The S&P 500 Index had 35 monthly declines of down 6% or more, while the PPUT Index had 18 such declines. There is a hypothetical cost imputed to the Index for the for the paying of premiums for the put options, and the PPUT Index also had fewer monthly gains of more than 4%.

Lower Betas and Standard Deviations for the Indices

In their analysis of potential asset classes for diversification purposes, asset managers may look to see investments with relatively low betas.  The table below shows that all three Cboe S&P indices had betas of less than 0.75 over the 35-year period. The three Cboe S&P indices had higher annualized returns than the MSCI EAFE Index, but lower than the S&P 500 Index.

To Learn More

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Disclaimer

Options involve risk and are not suitable for all investors. Prior to buying or selling an option, a person must receive a copy of Characteristics and Risks of Standardized Options. Copies are available from your broker or from The Options Clearing Corporation, One North Wacker Drive, Suite 500, Chicago, Illinois 60606 or at www.theocc.com. The CLLSM, CLLZSM, and PPUTSM indexes (the “Indexes”) are designed to represent proposed hypothetical options strategies. The actual performance of investment vehicles such as mutual funds or managed accounts can have significant differences from the performance of the Indexes. Investors attempting to replicate the Indexes should discuss with their advisors possible timing and liquidity issues. Like many passive benchmarks, the Indexes do not take into account significant factors such as transaction costs and taxes. The three Cboe S&P indexes in this blog were announced in either 2008 or 2015 as set forth above.  Information presented prior to the announcement dates is back-tested. Back-tested performance is not actual performance, but is hypothetical. A limitation of back-tested information is that it reflects the application of the Index methodology in hindsight. No theoretical approach can completely account for the impact of decisions that might have been made during the actual operation of an index. Cboe Global Indices, LLC calculates and disseminates the Indexes pursuant to an agreement with S&P Dow Jones Indices LLC (“S&P DJI”). CLLSM, CLLZSM, and PPUTSM are service marks of Cboe Exchange, Inc. or its affiliates. S&P®, S&P 500® and SPX® are registered trademarks of Standard & Poor’s Financial Services, LLC (“S&P”) and have been licensed for use S&P DJI and sublicensed by Cboe Exchange, Inc.  The S&P 500 and S&P GSCI are products of S&P DJI.  Any products (including options) that have the S&P Index or Indexes as their underlying interest are not sponsored, endorsed, sold or promoted by S&P DJI or S&P and neither S&P DJI nor S&P makes any representations or recommendations concerning the advisability of investing in products that have S&P indexes as their underlying interests.

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