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Performance of Latin American Markets in Q3 2019

Staying the Course: S&P MARC 5% Q3 2019 Performance

The Road Less Traveled

Adding Liquidity to the Global Dairy Market – S&P DJI Launches S&P GSCI Skim Milk Powder

ESG: Why Not? Insignificant Alpha Observed between the S&P 500 ESG Index and the S&P 500

Performance of Latin American Markets in Q3 2019

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Silvia Kitchener

Director, Global Equity Indices, Latin America

S&P Dow Jones Indices

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The third quarter was a difficult one for the Latin American region. Meanwhile, it was a mixed bag for global markets—the U.S. ended on a slightly positive note, Europe on a negative one, and Japan also on a positive one, with global markets remaining nearly flat.

The S&P 500® ended the quarter up 1.7%, the S&P Europe 350® posted almost the exact opposite with -1.6%, while Japan’s S&P/TOPIX 150 was up nearly 4%. Latin America’s blue-chip index, the S&P Latin America 40, was down 6.3%. Many internal factors contributed to the region’s underperformance, including reductions in exports, contractions in the industrial and service sectors, soft labor markets, political uncertainty, a slump in commodities prices, and low consumer sentiment. External factors also weighed heavily on the region, primarily the uncertainty surrounding trade negotiations between the U.S. and China.

While all Latin American markets ended in the red for Q3 2019, when comparing with USD-based returns, we noticed that, with the exception of Argentina and Peru, all markets in the region outperformed in USD terms or were flat in local currency terms. This is an example of how currency depreciation can have an impact on performance. The biggest differences were seen in Brazil and Colombia, with the S&P Brazil BMI posting a return of -3.9% in USD but 4.2% in BRL, and, the S&P Colombia Select Index returning -5.7% in USD but a decent 2.3% in COP. Mexico’s headline benchmark, the S&P/BMV IPC, generated a -2.6% total return in USD but was nearly flat in MXN (0.2%).

Overall, most currencies in the region saw significant depreciation during Q3 2019. Argentina led the pack in the depreciation rate for the quarter, with a fluctuation of nearly 60% between the highest and lowest rates. Brazil followed with a fluctuation of 16%, and Colombia followed with a change of nearly 11%.

Interestingly, sectors seemed to offer a clearer picture of the region. It was certainly a tough quarter for most economic sectors, although we still saw defensive sectors like Health Care and Consumer Staples were still able to post positive returns. Real Estate, Consumer Discretionary, and Information Technology also ended the quarter in positive territory. The Materials sector, which includes mining companies, was the worst-performing sector, followed by Financials.

As Exhibit 1 shows, Brazil was the best performer in the region for the quarter. Not surprisingly, most of the best-performing stocks were Brazilian, with BRF S.A., a Consumer Staples company, finishing at the top of the list among the constituents of the S&P Latin America 40, which seeks to track the performance of the leading 40 companies in the region. In terms of indices, the S&P/B3 Momentum Index, which focuses on the top companies in the Brazilian market that show persistence in their relative performance, as measured by their risk-adjusted price momentum score, had the best return for the quarter at 14.5%.

In Mexico, the momentum index was also a top performer among factor strategies. The S&P/BMV IPC CompMx Short-Term Momentum Index returned nearly 4%, significantly higher than the benchmark S&P/BMV IPC’s return (0.2%). However, in Mexico, FIBRAS ruled, and the S&P/BMV FIBRAS Index had an outstanding quarter (10.5%), as much of its returns are attributable to the high yields FIBRAS generate. As of Sept. 30, 2019, the indicated dividend yield for the S&P/BMV FIBRAS Index was 8.1%.

Chile had a relatively flat quarter, with the S&P IPSA returning -0.2%. The worst performers were small-cap stocks, as measured by the S&P/CLX IGPA SmallCap (-7.1%). In terms of sectors, the S&P/CLX IGPA Consumer Staples did the worst (-8.4%). Meanwhile, the S&P/CLX IGPA Real Estate and the S&P/CLX IGPA Industrials had strong returns of 11.1% and 7.3%, respectively.

Peru and Colombia had difficult quarters, with Peru being the worst performer of the two. However, in both markets the best-performing stocks were from the Electric Utilities industry, proving the Utilities sector’s defensive potential during challenging market environments.

As we enter the last quarter of the year, many are already looking forward to 2020. Most economists’ consensus is that Latin America will continue to struggle with market volatility, stagnant economic growth, and political uncertainty. As an optimist, I think there are always investment opportunities in the short- and long-term horizon, despite the tough times. In fact, the diversity of our leading country and regional indices shows exactly that.

For more information on how Latin American benchmarks performed in Q3 2019, read our latest Latin America Scorecard.

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

Staying the Course: S&P MARC 5% Q3 2019 Performance

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Joe Kairen

Senior Director, Strategy & Volatility Indices

S&P Dow Jones Indices

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Despite still ending the quarter higher, Q3 2019 was relatively subdued across asset classes when compared to the stellar performance we saw in equities in Q1 and Treasuries and gold in Q2. Exhibit 1 shows that the gains captured in Q1 and Q2 continued to compound in Q3, with the YTD performance of the S&P MARC 5% (ER) reaching 11.2%. As of Q3’s end, all components of the S&P MARC 5% ended in positive territory for each of the three quarters of 2019.

Looking at the index allocations from the beginning of Q3 2018 to the end of Q3 2019 (see Exhibit 2) we see that, while the mix of assets has changed significantly throughout this time, with equities taking a less prominent role due to the volatility seen at year-end 2018, the index continued to be over 100% allocated across the various asset classes at least 95% of the time. Despite Q4 2018’s volatility, the index only dropped below 100% on 15 days over the past year, keeping the strategy allocated to its underlying asset classes and not cash.

When looking at the relative performance of the S&P MARC 5% (ER) components versus the S&P MARC 5% (ER) itself, one can see that for the first half of the year, the gold and fixed income components actually lagged in performance. This changed toward the end of Q2 through mid-Q3, when gold also joined equities in outperforming the S&P MARC 5% (ER) on a relative return basis. The strength of the components allowed the S&P MARC 5% to start Q4 with a strong YTD performance, while still capturing the diversification built into the index.

During the 64 days in Q3 2019, we can see that for any of the rolling 252-day periods, the return of the S&P MARC 5% (ER) would have been positive despite the inconsistency of returns in most of its components. It’s also worth noting that across this period of time, the lowest rolling 252-day return for the S&P MARC 5% (ER) was 8.6% and the highest return was 13.4%—with an average return of 11.4%.

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

The Road Less Traveled

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Chris Bennett

Director, Index Investment Strategy

S&P Dow Jones Indices

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It is a truth universally acknowledged that liquidity is critical to market health; typically when liquidity falls, volatility rises.  The Financial Times recently cited claims that the increased use of passive investment vehicles had caused trading volumes in individual S&P 500 constituents to decline.  Should we be alarmed?

In reality, the notion that single-stock traders only add liquidity, while passive vehicles only diminish it, is wrong.  There are a great many active users of “passive” products, and any market-wide conclusions about liquidity require analysis not only of single stocks, but also of the ETFs and futures that track them.  A wider perspective is required because the volume of trading in ETFs, futures, and other index-based exchange-traded products is substantial.  Our research shows that there was an equivalent of around $127 trillion traded in products tracking the S&P 500 over the 12 months ending June 2019, while the implied average holding period across all S&P DJI index-linked exchanged traded products included in the report was 11 days.

To offer just one example that might broaden our perspective, consider how volumes in sector and industry-based products have grown over the past few years.  The assets, open interest, and trading volume in futures and ETFs tracking S&P DJI’s U.S. based sector and industry products has more than doubled.

In part, this may be a simple reflection of the recently increasing importance of sectoral drivers to stocks in the S&P 500.   At any rate, sectors have a long-term importance to stock returns.  Around half of all the daily variations in S&P 500 single stock returns over the past 15 years may be attributed to risks shared with their sectoral peers.

Because of their current liquidity and importance to returns, sector products can be, and often are, used to make active bets in place of individual stocks.  Individual stock volumes tell only part of the story, as investors may be choosing to use different vehicles to express their views.   An active manager who over- or under-weights a sector makes no less a contribution to price discovery and market efficiency than a manager who over- or under-weights the sector’s components.    Individual securities may currently be the road less traveled, but markets can arrive at accurate valuations from a different road.

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

Adding Liquidity to the Global Dairy Market – S&P DJI Launches S&P GSCI Skim Milk Powder

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Fiona Boal

Head of Commodities and Real Assets

S&P Dow Jones Indices

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On Oct. 21, 2019, S&P Dow Jones Indices (S&P DJI) launched the S&P GSCI Skim Milk Powder, an expansion of the single-commodity series offering of indices based on the S&P GSCI and the first index of its kind in the market. The S&P GSCI Skim Milk Powder is designed to provide investors with a reliable and publicly available investment performance benchmark for skim milk powder (SMP).

The S&P GSCI Skim Milk Powder is based on the NZX SMP futures contract, and it represents the first Oceania-based single-commodity index for the S&P GSCI index series.

Until now, dairy has been an inaccessible commodity for many market participants. The S&P GSCI Skim Milk Powder seeks to offer access to the return stream of a unique asset that is uncorrelated to major commodities such as gold but, at the same time, has a strong relationship to the New Zealand dollar and the New Zealand equity market.

There may also be opportunities for participants in the physical dairy market to utilize financial products based on the S&P GSCI Skim Milk Powder in conjunction with other risk management instruments. Broadening the financial instruments available to hedgers in the global dairy market is an important goal of the S&P GSCI Skim Milk Powder.

The S&P GSCI Skim Milk Powder joins the following two additional S&P GSCI dairy commodity indices that were launched by S&P DJI earlier this year based on CME futures contracts by the same name.

  1. The S&P GSCI Nonfat Dry Milk, which is designed to provide investors with a reliable and publicly available benchmark for investment performance in the dry milk market.
  2. The S&P GSCI Class III Milk, which seeks to provide investors with a reliable and publicly available benchmark for investment performance in the milk market.

The Global Dairy Market in Perspective

According to the International Dairy Federation, the consumption of dairy products is expected to increase by 25% between 2015 and 2024. While SMP is only a relatively small proportion of global dairy consumption, it is a large proportion of the global dairy trade. The dairy export market is dominated by milk powder, with approximately 3.9 million metric tons of SMP and whole milk powder traded annually.

Importance of Dairy to the New Zealand Economy

Dairy represents the largest export industry in New Zealand, and the dairy sector contributes NZD 7.8 billion (3.5%) to New Zealand’s total GDP. Export revenue from dairy farming was NZD 15.1 billion in 2017-2018, equivalent to 28% of the total value of New Zealand’s merchandise exports. This is more than two times the meat sector, three times the wood sector, and seven times the wine sector. New Zealand is the third-largest SMP exporter in the world after the EU and the U.S. China is most important destination for New Zealand’s dairy product exports.

 

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

ESG: Why Not? Insignificant Alpha Observed between the S&P 500 ESG Index and the S&P 500

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Ben Leale-Green

Analyst, Research & Design, ESG Indices

S&P Dow Jones Indices

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Does the S&P 500® receive a premium over the S&P 500 ESG Index? Absent a premium from the S&P 500, investors could have their cake and eat it too with the S&P 500 ESG Index: similar or better performance, along with the benefits of ESG.

Academic literature suggests no sin stock premium over their non-sin counterparts. Sin stocks are usually defined by their product involvement (e.g., tobacco, controversial weapons, etc.). “The Price of Sin”[1] explored apparent outperformance of sin stocks, citing theories of neglected stocks and segmented markets. When adding sector controls to factors while ensuring the sin stock indices assessed are market-cap weighted[2] and evolving asset pricing models to include quality and low volatility factors,[3] a lack of sin premia was observed.

While the S&P 500 ESG Index does exclude some sin stocks, it also takes a more holistic view of ESG and removes the worst ESG companies, as measured by the S&P DJI ESG Scores.[4] Exhibit 1 displays the selection process for the S&P ESG Index Series.

The S&P 500 ESG Index is designed in alignment with the S&P 500’s risk/return profile, while removing the worst ESG performers. The S&P 500 ESG Index seeks to provide greater exposure to companies that, for example:

  • Limit scope 3 GHG emissions and set targets for reduction;
  • Actively monitor diversity-related issues;
  • Have at least 50% female management representation
  • Include performance and reporting on their ESG materiality analysis; and
  • Tie executive compensation to material ESG issues.

Exhibit 2 shows the excess return over the risk-free rate for the S&P 500 ESG Index and the S&P 500, and it can be observed that the excess returns are similar. Furthermore, the tracking error over this period was 0.93% (which was even lower over the past five years, at 0.74%[5]). The annualized volatility of the S&P 500 ESG Index was slightly lower than the S&P 500, at 14.63% and 14.86%, respectively. The annualized return was 0.02% higher for the S&P 500 ESG Index than the S&P 500.

Following Blitz and Fabozzi’s approach,[6] the Capital Asset Pricing Model and its derivatives[7], which include factors assessing relative size, value, momentum, low volatility, and quality[8]. The S&P 500 excess return was used as the market risk premium to assess alpha (α) of the S&P 500 ESG Index.

For each model implemented, there is insignificant alpha present (see Exhibit 3), thus no significant out- or underperformance of the S&P 500 ESG Index compared with the S&P 500 during this period.

As the returns of the S&P 500 ESG Index are so close to those of the S&P 500, plus the opportunity to receive all the ESG benefits, why not choose the S&P 500 ESG Index over its market-cap-weighted parent?

[1]   Hong, H., & Kacperczyk, M. (2009). The Price of Sin: The Effects of Social Norms on Markets. Journal of Financial Economics, 15-36.

[2]   Adamsson, H., & Hoepner, A. (2015). The ‘Price of Sin’ Aversion: Ivory Tower Illusion or Real Investable Alpha?

[3]   Blitz, D., & Fabozzi, F. (2017). Sin Stocks Revisited: Resolving the Sin Stock Anomaly. Journal of Portfolio Management, 82-94.

[4]   Please see the S&P 500 ESG Index methodology for more information.

[5] Source: S&P Dow Jones Indices LLC. Performance data from May 31, 2014, to May 31, 2019.

[6]   Blitz, D., & Fabozzi, F. (2017). Sin Stocks Revisited: Resolving The Sin Stock Anomaly. Journal of Portfolio Management, 82-94.

[7]   French, K. F. (1992). The cross-section of expected stock returns. Journal of Finance, 427-465; French, K., & Fama, E. (2015). A Five-Factor Asset Pricing Model. Journal of Financial Economics, 1-22; Carhart, M. (1997). On Persistence in Mutual Fund Performance. The Journal of Finance, 57-82; Frazzini, A., & Pedersen, L. (2013). Betting Against Beta. Journal of Financial Economics, 1-25.

[8]   These models have been run using data from May 1, 2010, the start of the S&P 500 ESG Index’s back-tested history, through July 31, 2019, the most recent date for which the factor returns are available, using daily returns. The index levels are sourced from S&P Dow Jones Indices LLC, while the factor returns are sourced from Kenneth French’s website (French, K. [September 2019]. Current Research Returns. (French K. , Current Research Returns, 2019) and AQR (AQR. (2019, September). Betting Against Beta: Equity Factors, Daily. https://www.aqr.com/Insights/Datasets/Betting-Against-Beta-Equity-Factors-Daily)

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