Indexology^® Blog

Consistently outperforming the S&P 500^® is difficult. The S&P Dow Jones Indices SPIVA report shows that less than 18% of funds outperformed the S&P 500 (SPX) over the five-year period ending 12/31/2018. So how is it that the S&P 500 Equal Weight Index (SPEWI), a passive index comprised of the very same 500 stocks, accomplished what so few active managers have been able to do, outperforming the S&P 500 in 13 of 19 years from 2000-2018[1]? And how can understanding the nature of that outperformance yield further portfolio innovation?

Through selling winners and buying losers to parity each quarter, equal-weighting attempts to address a core inefficiency of cap weighted indices, which by definition – systematically over-weight, overvalued companies. While it is impossible to identify ahead of time which companies are the overvalued ones, the index should take the mathematical loss over time.

When viewed through this lens, it’s apparent that exploiting the allocation inefficiency of Cap Weighting through Equal Weighting is only a half measure.

The opposite of “Cold” isn’t “Room Temperature,” it’s “Hot.”

The Reverse Cap Weighted Index (Reverse), which as the name implies – reverses the order of the S&P 500 through weighting by 1/Mkt Cap, takes exploiting that inefficiency one step further. In direct contrast to Cap Weighting, Reverse by definition – systematically over-weights undervalued companies.  More information on Reverse Cap Indexing can be found here. The net result of weighting a portfolio in this manner is effectively a contrarian play within the S&P 500, as the largest companies/industries in SPX would be the lowest weighted within the Reverse Index.

Historically, in environments in which SPEWI outperforms SPX, we would expect Reverse to outperform them both. Conversely, in environments where SPX outperforms SPEWI (as is the case over the last three years) we would expect Reverse to be the worst performing of the three. Below is a chart detailing the performance of the three indices from 12/31/1996 – 6/30/2019.

Note: S&P EWI has an index launch date of 1/8/2003 and Reverse has an Index launch date of 10/23/2017. Both Indices are licensed and calculated by S&P Dow Jones Indices and all information for the Indices prior to its Launch Date is back-tested by S&P DJI, based on the methodology that was in effect on the Launch Date. Standardized performance for S&P 500, S&P EWI, and REVERSE can be found by clicking the respective link. Risk & Return data sourced from Bloomberg. All figures represent Total Return of the indices.

Consistent with this expectation, just as SPEWI has outperformed SPX with additional volatility, Reverse was the best performing of the three alongside the highest volatility of group. While the total return figure demonstrates the robustness of the outperformance, the below daily 5-year rolling return chart shows the consistency of that outperformance, with Reverse being the highest returning of the three indices in 78% of the observed data points.

Note: S&P EWI has an index launch date of 1/8/2003 and Reverse has an Index launch date of 10/23/2017. Both Indices are licensed and calculated by S&P Dow Jones Indices and all information for the Indices prior to its Launch Date is back-tested by S&P DJI, based on the methodology that was in effect on the Launch Date. Standardized performance for S&P 500, S&P EWI, and REVERSE can be found by clicking the respective link. Risk & Return data sourced from Bloomberg.

This additional return (and the relationship to SPEWI) is partially derived from the higher Size (SMB), Value (HML) and Anti-Momentum (MOM) factor loads expressed in the Reverse Index, relative to the other S&P weighting schemes. Reverse merely places additional load on the factors that drive differentiation between SPEWI and SPX. These findings (as they relate to SPEWI and SPX) are consistent with prior S&P DJI research.[2]

Note: S&P EWI has an index launch date of 1/8/2003 and Reverse has an Index launch date of 10/23/2017. Both Indices are licensed and calculated by S&P Dow Jones Indices and all information for the Indices prior to its Launch Date is back-tested by S&P DJI, based on the methodology that was in effect on the Launch Date. Standardized performance for S&P 500, S&P EWI, and REVERSE can be found by clicking the respective link. Fama-French factor portfolios are from the Ken French Data Library.

While SPX represents an operationally efficient index, Reverse takes the well understood elements of SPEWI (which exploit the investment inefficiencies of Cap Weighting), one step further and provides a unique contrarian play within the S&P 500 universe.

[1] Calendar year returns were calculated from 2000 through 2018.

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

Disclosure:
The author is an employee of Exponential ETFs, the creator and owner of the Reverse Cap Weighted U.S. Large Cap Index (the “Index”). Exponential ETFs has contracted with S&P Opco, LLC (a subsidiary of S&P Dow Jones Indices LLC) to calculate and maintain the Index. The Index is not sponsored by S&P Dow Jones Indices or its affiliates or its third-party licensors (collectively, “S&P Dow Jones Indices”). S&P Dow Jones Indices will not be liable for any errors or omissions in calculating the Index. “Calculated by S&P Dow Jones Indices” and the related stylized mark(s) are service marks of S&P Dow Jones Indices and have been licensed for use by Exponential ETFs. S&P® is a registered trademark of Standard & Poor’s Financial Services LLC (“SPFS”), and Dow Jones® is a registered trademark of Dow Jones Trademark Holdings LLC (“Dow Jones”).
The Reverse Cap Weighted U.S. Large Cap Index (Reverse) is a rules-based reverse capitalization weighted index comprised of the 500 leading U.S.-listed companies as measured by their free-float market capitalization contained within the S&P 500 universe. The Index has an inception date of October 23, 2017, with a back tested time-series inception date of December 31, 1996. You cannot invest directly in an index.
The S&P 500 Index is a widely recognized capitalization-weighted index of 500 common stock prices in U.S. companies. You cannot invest directly in an index.
The S&P 500 Equal-Weight Index is the equal-weight version of the widely-used S&P 500. The index includes the same constituents as the capitalization weighted S&P 500, but each company in the S&P 500 EWI is allocated a fixed weight – or 0.2% of the index total at each quarterly rebalance. You cannot invest directly in an index.
Past performance of an index is not a guarantee of future results, which may vary. The value of investments may go down as well as up and potential investors may not get back the amount originally invested. Performance figures contained herein contain both hypothetical and live returns; results, hypothetical or otherwise, are intended for illustrative purposes only. Index performance returns do not reflect any management fees, transaction costs, or expenses, which would reduce returns. Inclusion of a security within an index is not a recommendation by to buy, sell, or hold such security, nor is it considered to be investment advice. It is not possible to invest directly in an index.
The Index, strategy, and performance returns discussed are for informational purposes only and do not represent an offer to buy or sell a security and should not be construed as such.

Our fundamental credit strength strategy uses credit ratios to screen out issuers with risky credit profiles and construct corporate bond portfolios with strong credit quality (for a detailed methodology, please see our previous blog). Our research shows that a credit strength strategy can potentially reduce return volatility and improve drawdowns. Our goal in this blog is to further highlight that a credit strength strategy can offer downside protection and sector diversification.

Exhibit 1 illustrates the defensiveness of the credit strength strategy. Both investment-grade and high-yield credit strength portfolios tend to outperform (underperform) the broad market when the credit market falls (rises). This observation is consistent with the reduction in return volatility and drawdown we find in our research (volatility and drawdown are reduced by 12%/16% and 25%/30% for investment grade/high yield, respectively).[1]

As a bottom-up fundamental credit approach, our credit strength strategy emphasizes issuer selection and weighs issuers equally, thereby reducing the overconcentration of financial issuers in the portfolio. A traditional corporate bond index weighs constituents by bond size, meaning an issuer’s weight is dictated by the amount of debt the issuer has outstanding. Therefore, a market-value-weighted corporate bond index tends to have its weight disproportionately concentrated in issuers from the Financials sector, as illustrated by the S&P U.S. Investment Grade Corporate Bond Index (see Exhibit 2).

Weighting issuers equally is one way to avoid overconcentration in issuers or sectors with the most debt, and this strategy is consistent with the goal of constructing a portfolio with better credit fundamentals. Exhibit 2 compares the Financials sector weights in our hypothetical credit strength portfolios versus traditional corporate bond indices.

The diversification effect is noticeable in both investment-grade and high-yield bonds, and it is particularly pronounced in investment-grade bonds, where the average allocation to Financials in the credit strength strategy is nearly half of the broad investment-grade corporate bond index (20% versus 40%).

Defensive portfolios with diversified sector allocation may potentially be able to offer lower return volatilities. A properly constructed credit strength portfolio can offer effective credit exposure for long-term corporate bond investors, while improving risk-adjusted returns and mitigating credit risk.

[1] For more details, please see our previous blog: https://www.indexologyblog.com/2019/07/10/using-credit-ratios-to-build-defensive-corporate-bond-portfolios/

We recently published a research paper, “Building Better International Small-Cap Benchmarks,” offering a comprehensive look at the recently launched S&P Global SmallCap Select Index Series. These indices are designed to measure the performance of small-cap companies with positive earnings.

Why incorporate positive earnings criteria into small-cap benchmarks? The initial foundation stems from two prior studies[1]^,[2]; the first study showed that the quality factor was one of the primary drivers of the return differential between two prominent small-cap benchmarks in the U.S. The second study found that the variability of the size effect mainly stemmed from the volatile performance of low-quality, or junk, small-cap firms. Additionally, the authors found that when junk or low quality is controlled for, the size premium becomes more robust in nature and can be found across industries, time periods, and 23 different markets.

Based on evidence found in the two papers, we investigated whether quality has earned a similar premium in international S&P DJI small-cap universes. To test the effectiveness of positive earnings, Exhibit 1 shows the average one-month excess return of positive earnings companies to negative earnings companies for each country in the S&P Global BMI universe.[3]

On average, profitable companies outperformed unprofitable companies in over 80% of the countries in the S&P Global BMI universe. In addition, we did not observe any geographical region bias, which leads us to conclude that excess returns being earned by profitable small-cap securities is potentially a global phenomenon. This is a key point in showing the robustness of this strategy, as the criteria shows consistent results across markets and regions.

Exhibit 2 shows that applying a positive earnings criteria to small-cap benchmarks has been an effective tool in attaining outperformance across multiple universes. For example, the S&P SmallCap Select Indices outperformed their S&P Global BMI counterparts across all regions, and the performance differential was particularly prominent in emerging markets.

As a result, incorporating a positive earnings screen can potentially be a useful way to boost returns across a number of markets, globally. To find out more about our recently launched S&P Global Small Cap Select Index Series, see the latest research paper.

[1] Brzenk, P. and A. Soe (2015). “A Tale of Two Benchmarks: Five Years Later.” S&P Dow Jones Indices.

[2] Asness, C., A. Frazzini, R. Israel, T. Moskowitz, and L. Pedersen (2018). “Size matters, if you control your junk.” Journal of Financial Economics. 129: 479-509.

[3] We limited the countries to those that had been in S&P Global BMI for the entire testing period. One-month returns are total returns (inclusive of dividends) in local currency.

Commodities markets hit the summer doldrums in July. The S&P GSCI was down 0.2% for the month and 13.1% YTD. The Dow Jones Commodity Index (DJCI) was down 0.8% in July and up 6.1% YTD, reflecting its lower energy weighting. Impressive rallies in nickel and silver markets were pitched against a slump in agriculture prices, leaving the broad commodities indices little changed over the month.

The S&P GSCI Petroleum ended the month up 0.7%. Oil prices have remained relatively stable despite a serious escalation of geopolitical tensions in the Middle East, which may speak to a global economy that is weakening at a notable pace. It is also likely that U.S. production is now acting as a firewall against the geopolitical risks apparent in the global economy.

The S&P GSCI Industrial Metals ended the month up marginally, with most metals displaying bland monthly and YTD performance. However, there has been one notable exception; the S&P GSCI Nickel was the big outperformer in July, up 14.4% on the back of a widening global market deficit and the ongoing contraction in visible inventories. Nickel inventories at the London Metal Exchange are the lowest since January 2013, having fallen by 30% since the beginning of 2019. Little progress at the Sino-U.S. trade talks at the end of July and the Chinese Purchasing Managers’ Index suggesting another month of contraction in manufacturing activity present significant head winds for industrial metals into the end of the year.

After the U.S. Fed cut rates as expected amidst a revival of global central bank easing, gold’s performance cooled slightly into the end of the month. According to the World Gold Council, global gold demand rose 8% in the first half of the year driven by central bank buying and a flurry of funds into gold-based exchange-traded products. The S&P GSCI Silver spiked 7.1% higher in July, with some speculators betting silver will catch up to gold’s double-digit YTD performance.

It was a poor month for agricultural commodities, with the S&P GSCI Agriculture falling 5.5%. Grain market participants remain wary regarding the exact size and condition of the U.S. crop after heavy rain caused unprecedented planting delays in spring. Many are waiting for the USDA to issue updates on how much corn and soybeans were planted in a report to be issued by the USDA next month. There were conflicting reports over the month regarding the purchase of U.S. soybeans by Chinese crushers, but with little official progress in the trade talks between China and the U.S. the return of this major export market seems some way off .The S&P GSCI Coffee fell 8.8% in July. A frost scare in Brazil early in the month sent prices to 2019 highs, but prices subsequently fell as crop damage appeared minimal.

The so-called Chinese protein gap and falling feed prices offered some support to U.S. livestock markets in July. The S&P GSCI Livestock rallied 3.1% for the month. China, the world’s largest pork producer and consumer, has reported more than 140 outbreaks of African swine fever since the first case was reported in August 2018. Despite a 63% tariff on U.S. pork, China is still buying U.S. pork, though not at pre-trade war levels.

One of the classic scenes from the original Top Gun movie recounts the exchange Maverick (Tom Cruise) had with a MiG-28. Maverick corrects Charlie’s (Kelly McGillis) intelligence report on the Russian fighter jet with his eyewitness account. When she asks how he saw a MiG-28 perform a 4G dive from above, he responds: “Because I was inverted.” Goose (Anthony Edwards) interrupts Mav that it was “we,” not “I.”

Fed Chairman Jerome Powell could have responded the same way when asked why he cut rates today. The treasury yield curve was inverted for the first time since the dark days of 2007. This is cause for alarm as the previous three recessions occurred after the 10-year U.S. Treasury Note yield fell below the three-month yield, as is the case today.

By cutting rates, the Fed is hoping to be ahead of the curve to stave off another recession. History has shown precedent for this. Looking at the S&P U.S. Treasury Current 10-Year Index yield minus the S&P U.S. Treasury Current 2-Year Index yield, the curve inverted the previous two recessions, but it hasn’t fallen below zero in the current cycle, unlike the 10-year/3-month curve.

Then there’s the Maestro. It was former Fed Chair Alan Greenspan’s deft use of the overnight rate during the previous longest bull market in history that gave him the nickname “Maestro” (not less brave than Maverick’s move, by the way). In 1994, Greenspan cut rates despite the strong equity market performance. The S&P 500^® climbed 88% from the October 1990 lows and it rallied another 42% before the Fed would tighten monetary policy again. With a bull market long in the tooth and a similar political landscape (an incumbent gearing up for his reelection campaign), Jerome Powell is taking a page out of the Maestro’s songbook by cutting before the yield curve inverts.

History has shown that maintaining exposure to equities during an easing cycle can still be profitable despite substantial prior gains. Throughout the 1990s, Greenspan cut rates a total of 23 times. The S&P 500 responded positively each time, averaging a 16% annual return following each cut. However, his same approach did not work as well in the 2000s after the yield curve inverted and the bull market ended.

It remains unclear whether the Fed is channeling the Maverick move by pushing the limits or Alan Greenspan’s “Maestro” of the 1990s with sustained economic success. Market participants can only wait to see what the consequences of the Fed’s moves might be. For now, investors will have to follow the bond market for clues on the next Fed move.