Indexology^® Blog

The latest results from the SPIVA U.S. Mid-Year 2018 Scorecard show improvement in the relative performance of actively managed domestic equity funds against their respective benchmarks. During the one-year period ending June 30, 2018, the overall percentage of all domestic funds outperforming the S&P Composite 1500^® increased to 42.02%, compared with six months prior (36.57%). During the same period, 63.46% of large-cap managers, 54.18% of mid-cap managers, and 72.88% of small-cap managers underperformed the S&P 500^®, the S&P MidCap 400^®, and the S&P SmallCap 600^®, respectively (see Exhibit 1).

Exhibit 2 shows that, among the three market cap segments, small cap (20.50%) was the best performing segment over the 12-month period ending June 30, 2018. Nevertheless, compared to active managers in the large-cap and mid-cap segments, more small-cap managers underperformed their benchmark, the S&P SmallCap 600. This finding dispels the myth that small cap is an inefficient asset class in which active management offers the best solution to access. Year after year, the SPIVA U.S. Scorecard has repeatedly shown that the majority of small-cap active managers have underperformed the S&P SmallCap 600, and this trend can be seen in all the periods studied.

While the near-term performance of active equity funds improved, the majority still underperformed their benchmarks over the medium term as well as the longer-term investment horizon (see Exhibit 3). For example, over the five-year period, 76.49% of large-cap managers, 81.74% of mid-cap managers, and 92.90% of small-cap managers lagged their respective benchmarks. Similarly, over the 15-year investment horizon, 92.43% of large-cap managers, 95.13% of mid-cap managers, and 97.70% of small-cap managers failed to outperform on a relative basis.

Similarly, across all investment horizons measured, managers in each of the international equity categories underperformed their benchmarks. Furthermore, the longer the time horizon, in general, the more funds underperformed. Over 94% of active emerging market equity funds and nearly 79% of international developed equity funds underperformed when measured over the 15-year horizon.

Similar to our findings in the U.S. small-cap space, emerging market equities is also another asset class where conventional wisdom dictates using active management to access. However, as the SPIVA U.S. Scorecard results have repeatedly shown, an overwhelming percentage of active emerging market equity managers have difficulty beating their benchmark.

It is also worth noting that compared to the results from six months prior, more international equity managers underperformed their benchmarks in the one-year investment horizon, especially in the international small-cap category.

When it comes to fixed income, during the 12-month period ending June 30, 2018, the majority of actively managed funds investing in long-term government and long-term investment-grade bonds underperformed their benchmarks, but their relative performance over the benchmarks improved compared to six months prior. In contrast, funds investing in short- and intermediate-term investment-grade bonds outperformed their benchmarks.

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Real U.S. interest rates have shifted upward YTD in 2018, with a larger shift on the short end than the long̬̬—producing a flatter curve. Exhibit 1 shows the real yield curve (from 5 to 30 years) at the end of each quarter since December 2017 and also includes data as of Oct. 9, 2018 to reflect a recent move since September 2018.[1]

The curve shift produced lower present values of inflation-adjusted cash flow streams for future retirees. These changes are quantifiable and shown in Exhibit 2. Each bar represents a cost decrease of 25-year, inflation-adjusted cash flows, commencing at the respective 5-year increments indicated on the horizontal axis for the year-to-date through Sept. 28, 2018 period.[2]

What is the significance for retirement savers? When rates decline (increase), static wealth levels buy less (more) income. For example, the cost of income commencing in 2030 declined by $1.51 (to $19.58 as of September 2018 from $21.09 in December 2017). For a given wealth level, a 2030 retiree can expect to generate almost 8% additional income. Here’s the arithmetic for a $100,000 hypothetical account.

As of December 2017: $100,000/$21.09 = $4,742.24 of inflation-adjusted income per year starting in 2030

As of September 2018: $100,000/$19.58 = $5,108.34 of inflation-adjusted income per year starting in 2030

($5,108.34/ $4,742.24) – 1 = 7.7%

A key lesson is that uncertainty comes in more flavors than market risk. The cost of future income, driven by interest rates, can be a major source of uncertainty. Even if a portfolio has not changed in value YTD in 2018, the amount of future income one could buy currently would have increased by almost 8% due to the shift in interest rates. On the other hand, had rates moved downward, the opposite would be true, which is tricky because most investors tend to feel safer if their investments do not change in value. The takeaway is that when investors are trying to provide future income for themselves, low portfolio volatility does not typically equate to low income volatility due to movements in interest rates.

How can one manage such variability? One way would be to gradually allocate more assets to a portfolio structured to hedge interest rates. The trade-off is that when you hedge interest rates, or the future variability of the amount of income you’ll have, you give up the opportunity to participate in the long-term growth of stock markets. This trade-off is one of the central long-term risks that retirement investors should consider carefully and develop an investment policy to manage.

[1] U.S. Department of the Treasury. https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=realyield

[2] For more information, see S&P STRIDE Metrics.

Equal-weight indices have a small-cap tilt. Therefore, one might naturally assume that the volatility of equal-weight indices is higher than that of their cap-weighted counterparts. Surprisingly, this is not always the case, and we can understand why using the lens of dispersion and correlation.

Exhibit 1 shows that the volatility of the S&P 500^® Equal Weight Index was about 1% less than that of the (cap-weighted) S&P 500, as of the end of Q3 2018. (A key driver of this difference was the Information Technology sector, as the S&P 500 Equal Weight Information Technology Index was 1.6% less volatile than the S&P 500 Information Technology. Readers who are particularly interested in comparing equal-weight and cap-weighted sectors would enjoy perusing our new U.S. Equal Weight Sectors Dashboard.)

Exhibit 2 shows that the dispersion of the S&P 500 Equal Weight Index was consistently higher than that of the S&P 500. This is not a surprising outcome since, as a function of equal weighting, the index has higher weights in smaller, more idiosyncratic stocks.

Exhibit 3 provides two important insights about the relative correlation of the S&P 500 Equal Weight Index and its cap-weighted parent:

• The weighted average correlation of the equal weight index is consistently lower than that of the S&P 500.
• The spread between the correlation of the two indices has recently widened.

Other things equal, volatility rises as either dispersion or correlation rise. (This interaction helps us, for example, to understand the volatility of the new Communication Services sector.) The equal weight index’s higher dispersion drives volatility higher, but is balanced by its (unusually) lower correlations. This combination caused the S&P 500 Equal Weight Index’s volatility to drop below that of the S&P 500, an unexpected but justifiable outcome.

This quarter has brought mixed expectations for the region. The quarter itself resulted in overall positive returns. However, Latin America is still in the red for the year. The S&P Latin America 40, a widely used benchmark for the region, ended the quarter strong with a return of 6.4%. The countries that contributed to this upturn were the two largest markets in the region: Brazil and Mexico. In USD terms, the S&P Brazil BMI returned 5.1%, and in Mexico, the S&P/BMV IPC returned 10.3% for the quarter.

As 2018 enters its last three months of the year, many uncertainties from the earlier months have begun to unfold. Elections in many Latin American countries have concluded, with new leaders in Mexico, Colombia, Chile, Peru, and soon in Brazil. Despite many controversies, the markets have responded positively to their respective elections. In Mexico, NAFTA has been replaced by a similar agreement called the United States-Mexico-Canada Agreement (USMCA). This is good news for Mexico, causing a rally in the country’s equity market at the end of the quarter. Brazil is in the midst of presidential elections, with the first round concluded on Oct. 7, 2018. As predicted, the far-right presidential candidate Jair Bolsonaro won the first of two rounds of elections. In general, his win is seen as more favorable to financial markets compared with the other candidates. This also yielded a rally in the country’s equity market. The other countries did not fare as well when looking at USD returns for the third quarter, with Colombia showing the largest losses, followed by Peru, Chile, and Argentina.

It is interesting to note the important role currencies play in index returns. In the S&P Colombia Select, the S&P/BVL Peru Select, and Chile’s S&P/CLX IPSA, the returns in USD and local currency were not that different. However, in other markets like Brazil or Argentina, currency exchange rates had a greater impact. In Brazil, the local return of the S&P Brazil BMI was almost double compared with the USD return: 9.0% versus 5.1%, respectively. The most dramatic difference was in Argentina, where the USD version of the S&P Argentina BMI was almost flat, at -0.48%, and in ARS, the index soared to 40.7% for the same period. In Mexico, the currency exchange rates had the opposite effect. The S&P/BMV IRT showed better performance in USD than in MXN, with returns of 10.8% and 4.3%, respectively.

Other noteworthy highlights for the quarter saw Energy, Materials, and Financials emerge as the top three sector performers, as measured by the S&P Latin America BMI sector indices. The sectors returned 12.5%, 8.2%, and 6.6%, respectively. Not surprisingly, three of the five best-performing stocks in the S&P Latin America 40 for the quarter were from Energy: Colombia’s Ecopetrol rose 31%, and Brazil’s Petrobras ON and PN shares were up 23% and 18%, respectively.

Besides returns, several indices have shown strong dividend yields for investors seeking income. As expected, indices focusing on dividends and real estate had the highest generating yields. The S&P Dividend Aristocrats® Brasil Index had a yield of 7%. Similarly, in Mexico, the S&P/BMV FIBRAS Index had a yield of nearly 8%. The S&P/BVL Peru Dividend Index had the highest yield of all the indices in this report, with a yield of 8.2%.

So far, this year has been full of ups and downs, and the third quarter brought a bit of hope to investors in the region. There are still three more months to go before the year ends, and as things begin to unfold, it will be interesting to see what is left for Latin America—hopefully one more upswing.

To see more details about performance in Latin America, please see: S&P Latin America Equity Indices Quantitative Analysis Q3 2018.

Many people believe that index-based investing and market beta are synonymous. With the growing popularity of index-based investing, exchange-traded funds and index funds based on market benchmarks such as the S&P BSE SENSEX, S&P BSE 100, and S&P BSE 500 are slowly gaining ground. Investors have been familiarizing themselves with market returns linked to these benchmarks that represent the behavior of India’s equity markets. Assets in the passive Indian landscape have witnessed a significant growth with a range of products that have also started expanding to factor-based strategies.

What are these factor indices, and how are they different from standard market benchmarks and sector indices? Let’s look at factor indices using an analogy to tea drinking. While one can have the standard black tea with or without milk, today we are flush with options and different available flavours such as mint, chamomile, lemon, etc. Each of the flavours provides a different experience that differs from the standard.

If we extend this to indices, the S&P BSE SENSEX, S&P BSE SENSEX 50, S&P BSE 100 and similar indices that are market-cap based and showcase the movements of the Indian equity market within the segments they seek to track, be it the top 30 stocks of the market, top 50, or 100. Similarly, other market-cap-based indices such as the S&P BSE LargeCap Index, S&P BSE 150 MidCap Index, and S&P BSE 250 SmallCap Index are designed to represent market segments based on size.

Now if we want to add a new flavour to index design, we could select index constituents based on factors. These factors can be measures of volatility, quality (based on return on equity, accruals ratio, or financial leverage ratio), value (based on book value-to-price, earnings-to- price, or sales-to-price), among others. The resulting index is not market-cap weighted, but rather it is weighted by the specific factor. The behavior of such indices differ from those that are market-cap weighted in that the specific factor plays the primary role in the characteristics of these indices. For example, the S&P BSE Quality Index will have different risk/return characteristics from the S&P BSE SENSEX.

Exhibit 1 demonstrates the behavior of the various S&P BSE factor indices compared with one of India’s market benchmarks, the S&P BSE SENSEX.