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S&P Latin America Equity Indices Quantitative Analysis Q2 2020

S&P Latin America Equity Indices Quantitative Analysis Q1 2020

S&P GIVI® Japan and Major Single Factors Q1 2020

S&P Target Date Scorecard Year-End 2019

S&P Target Date Scorecard Mid-Year 2020

S&P Latin America Equity Indices Quantitative Analysis Q2 2020

S&P Latin America Equity Indices Commentary: Q2 2020

We have made it through the first half of 2020. Despite the continued spread of COVID-19 wreaking havoc on public health and the global economy, the markets did surprisingly well during Q2. In the U.S., the equity market rebounded from Q1, driven by government stimulus packages and the easing of restrictions imposed during the pandemic. The S&P 500® gained 20.5%, while the S&P Latin America 40, which is designed to measure the 40 largest, most liquid companies in the region, followed close behind, gaining 19.5%. However, Latin America was still deep in the red YTD, down 35.9%.

Among S&P Latin America BMI sectors, Information Technology (63.2%), Consumer Discretionary (47.6%), and Energy (41.2%) were the best performers for the quarter. In this new era of working, shopping, and recreation from home, online-based companies like Brazil’s PagSeguro Digital and StoneCo Ltd, which help businesses manage their e-commerce services, seem to be booming in emerging markets, as shown by their price appreciation. It will be interesting to see how industries quickly adapt to the “new normal” and not only survive, but also thrive.

In terms of countries, Argentina led the pack with the S&P MERVAL Index gaining 58.7% in local currency for the quarter. Brazil came in second, with a return of 31.2% as reflected by the S&P Brazil BMI. Peru’s S&P/BVL Peru General Index returned 16.7%. Chile’s S&P IPSA also had a strong quarter, with a gain of 13.5%. Colombia barely stayed afloat, with a lower return of 1.4% for the S&P Colombia BMI. Year-to-date, the countries’ returns were still in the red, with Colombia the worst and Argentina at the top with single-digit negative returns. There is still a lot of work ahead before the region stabilizes. Pre-pandemic, there were already significant domestic troubles: social unrest in Chile, economic woes in Argentina, and political instability in Brazil, among other issues. Added to this mix, the pandemic of the century and the economic damage it is leaving behind will likely make for a tough recovery.

Despite the strong quarterly returns, many economists1 (not surprisingly) are predicting an uphill battle for the region. As the COVID-19 pandemic spreads and conditions worsen in several countries, S&P Global Ratings economists are reducing the 2020 GDP growth forecast to a contraction of roughly 7.5%. Growth for 2021 is expected to be around 4% and economic recoveries are expected to be slower than originally predicted. To put it in context, GDP for the U.S. is forecast to grow 4.8% for 2021.2 S&P Global Ratings expectations are that economies that implemented strong policy support, such as Chile and Peru, may have “smaller permanent GDP losses.” It adds that the story may be different in countries like Mexico and Brazil, where support has been more limited.

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S&P Latin America Equity Indices Quantitative Analysis Q1 2020

S&P Latin America Equity Indices Commentary: Q1 2020

This new decade has not really started well—if only we could jump straight to 2021. Amid the overwhelming impact of the COVID-19 pandemic on public health and on the economy, perhaps what resonates best is that “this too will pass.”

U.S. equities, which serve as a guidepost for the global economy, surpassed prior all-time highs in volatility. VIX®, also known as the “fear gauge” has not reached similar highs since the global financial crisis (GFC) in 2008. The higher the uncertainty, the higher the option prices that are used to calculate VIX. The precipitousdrop in oil prices following a price war between Russia and Saudi Arabia threatened a collapse of the Energy sector, adding to the uncertainty in the U.S. and globally. Unemployment in the U.S. continued to rise—in the last two weeks of the quarter, nearly 10 million American applied for unemployment benefits following the shutdown of thousands of businesses. It’s expected that this number is only a sign of further job losses to come and that unemployment filings will double in the coming weeks. Many impacted businesses are in the travel, entertainment, restaurant, retail, and real estate industries.

What about Latin America? Like a tsunami that started in Asia then ravaged Europe, COVID-19 and its effects are now flooding the Americas. Despite the closing of borders and quarantines, the pandemic continues to sweep the continent. Governments have started to institute policies to minimize the public health and the economic impact. Similar to the U.S., which has approved a USD 2 trillion stimulus package to help mitigate the effects of the pandemic, Brazil has approved around USD 30 billion. Peru is also reviewing a similar package. In Chile, the president approved a USD 12 billion package. In Argentina, the World Bank will lend USD 300 million in emergency funds. Colombia and Mexico have not yet announced any major economic measures at this time. The question many ask is, will all this be enough? In the midst of uncertainty, the answer depends on how quickly the pandemic recedes and life goes back to normal.

According to S&P Global’s rating analysts, it is expected that the outbreak will push Latin America into a recession in 2020, recording its weakest growth since the GFC. They have also forecast that GDP will contract by 1.3% in 2020, before bouncing back to a growth rate of 2.7% in 2021. Finally, the length of the recession—although potentially worse in some countries—may be much shorter: only two quarters are projected versus six quarters during the GFC.1

Latin American markets underperformed global markets during the first quarter. All gains from the previous years were completely wiped out. The S&P Latin America 40 posted the worst quarter on record, ending at -46% in USD terms. In comparison, the S&P 500®, which also had the worst quarter since 2008, lost 20%.

No economic sector was spared in the rapid downturn, as companies in important industries like energy, mining, and financials were hit hard. The average stock price drop for members of the S&P Latin America 40 was around -45% for the quarter. The Energy sector of the S&P Latin America BMI performed the worst among the 11 GICS sectors (-61%). Health Care had a difficult quarter (-45%), but thanks to its strong past performance, it lost a lot less for the mid-term periods. Looking at individual markets in local currency terms, Argentina’s S&P MERVAL Index lost 41.5% for the quarter. Brazil and Colombia followed, returning -36% and -32%, respectively, as measured by the S&P Brazil BMI and the S&P Colombia Select Index.

In a sea of red for the quarter, in Mexico some indices were able to stay in the black. The S&P/BMV IPC Inverse Daily Index, which seeks to track the inverse performance (reset daily) of the S&P/BMV IPC, gained 23%. The following three indices also did well: the S&P/BMV MXN-USD (26%), the S&P/BMV China SX20 Index (9.4%), and the S&P/BMV Ingenius Index (9.4%). The latter two indices are designed to measure international stocks trading on the Mexican Stock Exchange, and their strong performance is largely driven by the depreciation of nearly 20% of the Mexican peso relative to the U.S. dollar in Q1.

The first quarter is done, and the second quarter is looking gloomy. Comprehensive relief efforts are underway to help citizens and support our economies, and we can only hope for the best while we continue to tread carefully.


S&P GIVI® Japan and Major Single Factors Q1 2020

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Tianyin Cheng

Senior Director, Strategy Indices

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Izzy Wang

Analyst, Strategy Indices

The S&P GIVI (Global Intrinsic Value Index) Japan outperformed its benchmark index, the S&P Japan BMI, by 40 bps in Q1 2020. Since its launch in March 2012, the S&P GIVI Japan has outperformed its benchmark index by 13 bps per year, with a tracking error of 2.44%.

2020 has gotten off to a bad start.  The Japanese equity market, as measured by the S&P Japan BMI, declined by 17.96% in Q1 2020, which was the worst-performing quarter since the GFC.  Amid the concern over the global economy’s outlook when China placed itself on lockdown due to COVID-19 in January, the Japanese market saw a mild decline.  After oil prices crashed and the virus threw various countries into chaos in March, the worldwide economic slowdown became real, and Japan had to join the global fight against COVID-19.  On March 23, 2020, the S&P/JPX JGB VIX®, which measures the 30-day forward volatility of 10-year JGB futures and represents the macroeconomic stability of Japan, rose to an all-time high of 6.81 and closed at 4.77 for Q1.  Stressed investors were resorting to extreme behavior amid the uncertain economic outlook and pressure on market liquidity. 

In the COVID-19 crisis, sectors appeared to be the main driver of performance, with a large gap between winners and losers—the difference between the best- and worst-performing sectors was 24.74%.  On one hand, the sharp decline in consumption demand and shortage of supply heavily hit several cyclical sectors.  Energy was the worst performer under the pressure of low demand and the collapse of Saudi-Russia negotiations.  Real Estate was severely affected, especially in the hotels and malls segments.  On the other hand, traditional defensive sectors, such as Utilities and Consumer Staples, were the best performers.  Health Care outperformed, as demand for healthcare products surged this quarter and hopes were on biotech companies producing vaccines/testing tools.  Finally, the increase in social distancing boosted the use of internet-based products, which favored Communication Services. 

The outperformance of the S&P GIVI Japan was mainly due to the selection effect, especially in Information Technology and Communication Services.


S&P Target Date Scorecard Year-End 2019

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Hamish Preston

Director, U.S. Equity Indices

SUMMARY

  • The S&P Target Date® Scorecard provides performance comparisons, equal- and asset-weighted category averages, and analytics covering the target date fund (TDF) universe.
  • The S&P Target Date Index Series offers representative benchmarks for TDFs. The series distinguishes itself from peer group benchmarks because it is investable, comprises consensusderived asset allocation weights, and its composition is known in advance of evaluation periods.
  • The S&P Target Date Through benchmarks represent the “Through” glide path category, while the S&P Target Date To benchmarks represent the “To” category.
  • Through TDFs outperformed To TDFs over the three-year horizon. Each S&P Target Date Through Index posted higher returns than its corresponding S&P Target Date To Index by an average of 1.06% across the different vintages.
  • Outperformance was particularly pronounced in the nearer vintages. The S&P Target Date Through 2015 Index and the S&P Target Date Through 2020 Index beat their To counterparts by 1.55% and 1.53%, respectively.
  • Higher equity allocations helped to explain the higher returns for Through TDFs. On average across the different vintages, Through TDFs had a 10.9% higher equity allocation than To TDFs. This difference was especially pronounced among the 2015 and 2020 vintages. Unsurprisingly, perhaps, To TDFs were less volatile than Through TDFs. Each S&P Target Date To Index offered less volatile returns over the three-year period than the corresponding Through index vintage. Overall, To TDFs offered higher risk-adjusted returns over the three-year horizon, especially at nearer vintages.
  • Larger TDFs continued to outperform smaller TDFs. The assetweighted returns exceeded the equal-weighted returns over one-, three-, and five-year horizons in all but two instances.  The one-year figures for the 2010 and 2060+ TDFs offered the exceptions.


A UNIQUE SCORECARD FOR THE TARGET DATE UNIVERSE

The S&P Target Date Scorecard presents the performance of TDFs as compared to appropriate benchmark indices. We consider all target date asset allocation policies to be active decisions, so we include funds that use passive underlying investments as well as active underlying investments. The scorecard covers target dates from retirement income to 2060 and beyond, and it has the following unique features.

  • A Representative Target Date Benchmark: The S&P Target Date Index is the only consensusdriven target date benchmark offered by an independent index provider. Its asset class exposure and glide path are functions of market observations acquired from an annual survey of target date managers. The index currently includes target dates from retirement income through 2060+. The S&P Target Date To Retirement Income and the S&P Target Date Through Retirement Income series were launched in January 2015, and performance is incorporated as accumulated history becomes available.
  • Apples-to-Apples Comparison: Target date fund returns are sometimes compared to popular asset class benchmarks such as the S&P 500® or Bloomberg Barclays U.S. Aggregate Bond Index. The S&P Target Date Scorecard avoids this pitfall by measuring a fund's returns against the returns of the benchmark that is most appropriate for each target date category.
  • Asset Allocation Risk Revealed: Sometimes custom, multi-asset class benchmarks are used for comparison purposes. However, these benchmarks do not measure asset allocation risk, as they are typically set with asset class exposure selected by fund managers. They also may lack transparency with respect to the method behind their calculation and may not be adjusted for changes in asset allocation policy over time. The report avoids these problems by referencing our consensus-driven target date benchmark that provides a representative proxy of asset allocation risk for each target date vintage.
  • Asset-Weighted Returns: Average returns for a fund group are often calculated using only equal weighting, which results in the returns of a USD 10 billion fund affecting the average in the same manner as the returns of a USD 10 million fund. An accurate representation of how market participants fared in a particular period can be better ascertained by calculating weighted-average returns, in which each fund’s return is weighted by net assets. The S&P Target Date Scorecard shows both equal- and asset-weighted averages. Additionally, we now use all share classes to calculate average TDF returns and performance quartiles.
  • Data Cleaning: Appropriate peer groups are built from underlying databases so meaningful benchmark comparisons may be performed. TDFs with vintages of 2060 or beyond are compared with the S&P Target Date 2060+ Index. TDFs with vintages that have already passed, such as 2005, are compared with the S&P Target Date Retirement Income Index. Average TDF returns, both equal-weighted and asset-weighted, are calculated using all share classes within each fund family in order to represent the aggregate experience of TDF shareholders. The S&P Target Date Scorecard offers the only comprehensive, periodic, and publicly available source of such data.


S&P Target Date Scorecard Mid-Year 2020

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Hamish Preston

Director, U.S. Equity Indices

SUMMARY

  • The S&P Target Date® Scorecard provides performance comparisons and analytics covering the target date fund (TDF) universe.
  • The S&P Target Date Index Series offers representative benchmarks for TDFs. The series is investable, comprises consensus-derived asset allocation weights, and its composition is known in advance of evaluation periods.
  • The first half of 2020 saw sizeable swings as the market reacted to COVID-19. After we said goodbye to the longest ever bull market in March, U.S. equities hosted a tremendous rally in Q2: the S&P 500® (up 21%) posted its best quarterly total return since 1998.
  • Higher equity allocations made far-dated S&P Target Date Indices more sensitive to equity market movements. Indeed, Exhibit 1 shows that far-dated indices experienced greater drawdowns during Q1 2020 but also posted stronger returns in Q2.
  • Overall, nearer-dated S&P Target Date Indices outperformed their longer-dated counterparts in the first half of 2020. However, higher allocations to U.S. large caps helped far-dated indices to outperform over longer horizons: the S&P 500 posted the highest returns of any S&P Target Date Index component over three- and five-year horizons.

  • Given that S&P Target Date Indices are designed to embody market consensus asset allocations, it is unsurprising that, on average, nearer-dated TDFs outperformed their longer-dated counterparts during the first half of 2020. The opposite was true over longer horizons.
  • In a continuation of a recent trend, larger TDFs outperformed their smaller counterparts; asset-weighted returns were higher than equal-weighted for all but the 2010 category over the six-month, one-year and three-year horizons. Asset-weighted returns were higher in all categories over the five-year horizon.
  • S&P Dow Jones Indices also produces S&P Target Date Style Indices. The "T" style indices aim to mitigate the impact of market drawdowns around the expected retirement date, while the "THROUGH" style indices aim to negate longevity risk—the risk of outliving one’s assets in retirement. Hence, THROUGH style indices have higher equity allocations than TO indices.
  • The relative returns of TO versus THROUGH indices in the first half of 2020 and over the one-year horizon typically decreased as the time to the assumed retirement date increased. This reflects the fact that near-dated TO indices, with much lower equity allocations than their THROUGH counterparts, were more insulated against market drawdowns earlier this year. In contrast, smaller differences in equity allocations between far-dated TO and THROUGH indices meant both styles were similarly impacted during Q1 2020. Far-dated THROUGH indices then benefitted more from the substantial equity market recovery in Q2 2020.
  • THROUGH style indices posted higher returns than their TO counterparts over three- and five-year horizons, while TO style indices posted lower volatility. Such volatility reduction helped near-dated TO style indices to post higher risk-adjusted returns than their THROUGH counterparts. The opposite was true for far-dated style indices: higher returns helped far-dated THROUGH style indices to post higher risk-adjusted returns than their TO counterparts.

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