Indexology^® Blog

Here is a 22-year history of a (hypothetical) actively-managed portfolio and its benchmark:

Results have been decisively mediocre. The portfolio outperformed in only five years out of 22, for a hit rate of 22.7%. Its cumulative return (68.2%) lagged that of the benchmark (74.0%), and its volatility was higher (4.79% vs. 4.25%). The manager’s marketing department will need to work overtime to hold onto this account.

And then a brainstorm occurs (as they occasionally do, in marketing departments). What happens if we look, not at annual performance, but at performance over rolling three-year windows?

The returns haven’t changed, but now, mirabile dictu, the portfolio outperforms in 15 of the 20 possible three-year intervals – 75 percent! The manager’s marketing staff trumpets his consistent outperformance for the last 20 years. And of course, the use of a three-year window adds credibility to the story, since “everyone knows” that you shouldn’t evaluate a manager over a period as short as a single year.

What has happened?

The manager’s five years of good performance were spread out over the 22 years of his history. Though few in number, there were enough good years that most of the three-year intervals contain at least one winner. The rolling average approach lets the good years do triple duty, and can convince the unwary observer that good performance is more frequent than it really is.

The lesson for students of investment performance is clear: Use all the data you have, but be wary of unnecessary aggregation. Aggregated performance data can conceal as much as they reveal.

I have probably been receiving them for years, but lately I have noticed opposing position papers in my inbox. Some claim Americans need a revival of defined benefit (DB) plans because of a looming retirement crisis, while others contend that defined contribution (DC) plans are doing great and there is no cause for alarm. DC plans do not define benefits in retirement, and DC accounts are personal. Therefore measuring average performance or aggregated account values, to assess the effectiveness of the DC system has limited utility for an individual. Harry Truman said, “It’s a recession when your neighbor loses his job; it’s a depression when you lose your own.” Similarly, everyone may be doing great in their DC plan, but if you have not saved enough and formulated a prudent withdrawal plan, retirement may feel like a depression. On the other hand, if you are a diligent saver and earn good returns, your retirement lifestyle may be better than it could have been with a DB plan.

In other words, the distribution of outcomes across DC plan participants tends to be more dispersed (has fatter tails) than the distribution of outcomes across DB plan participants—because DB plans define their outcome formulaically. To use a financial analogy, you might say DC plans are more stock-like while DB plans are more bond-like. The key for individuals is recognizing that many DC plans offer enough flexibility to create a more DB-like experience.

The S&P STRIDE Indices measure the performance of such a strategy, although there are many ways to accomplish similar aims depending on the available investments within given DC plans. The vital step to creating a more DB-like experience from available investments within a DC plan is lowering the risk to the future income expected to be drawn from the DC account.

Innovative plan sponsors are aware of the hurdles that participants face, which include not only saving and investing prudently, but also managing an effective withdrawal strategy in retirement. The title of Thomas Heath’s Washington Post column, published April 20, 2019, succinctly expresses the decumulation challenge. “Saving for retirement is hard. Knowing how to spend it down is harder.” Mr. Heath noted some of the challenges of retirement funding by quoting my colleague Howard Silverblatt and contemplating his own situation as he looks ahead to retirement. The DC system is essentially a collection of privately run investment menus from which individuals must handcraft their own retirement funding experience. Each sponsor should recognize the enormity of such a challenge and make income risk management solutions available to their participants. Each individual participant must develop their own situational awareness to inform their decisions about long-term accumulation, income risk management, and ultimately prudent decumulation. Relative to bond-like DB plans, there will be winners and losers. That is the nature of the DC system.

Our Year-End 2018 Canada SPIVA scorecard was released today.  In addition to showing that the majority of Canadian active equity managers failed to outperform their benchmarks, the scorecard’s results provide the opportunity to dispel some common misconceptions.  Here is a brief summary.

1) Higher volatility does not necessarily result in outperformance by active managers

A common view among market participants is that more volatile markets favor active management over passive solutions.  However, in a year when Canadian equities were caught up in global equity gyrations, 75% of Canadian active equity managers underperformed in 2018, as the majority of funds lagged in all categories.

Such underperformance by active managers in more volatile environments is consistent with other international regions, and perhaps speaks to a bias many active managers have for higher-beta stocks.  Indeed, these stocks are expected to be more heavily impacted by market corrections.

2) Smaller-cap stocks may not be better suited to active management

Another popular perception is that small- and mid-cap stocks are inefficient asset classes that are more suited to active management.  However, 80% of all small- and mid-cap managers failed to beat the S&P/TSX Completion (-12.85%) in 2018, suggesting they struggled to navigate the market turbulence as the equity benchmark recorded its worst calendar-year performance in a decade.

In fact, only once in the last eight calendar-year periods did the majority of small- and mid-cap managers beat the S&P/TSX Completion.  Hence, using an index-based approach to access smaller Canadian companies would have been beneficial, historically.

3) Get what you pay for? Not necessarily!

In many walks of life we are told that the cost of something is proportional to its quality.  But while some investors may believe higher-fee funds are illustrative of higher quality managers – as measured by their ability to outperform benchmarks – the data does not reflect this.

Exhibit 3 shows the relative performance of surviving active mutual funds in 2018.  Funds in each category are first grouped according to their expense ratio from the end of December 2017: “Q1” contains the 25% of funds in each category with the lowest expense ratio, while “Q4” contains the 25% of funds in each category with the highest expense ratio.  The average relative return in 2018 is then taken for each group; a negative number indicates the benchmark outperformed.

Quite clearly, higher expense ratios were typically associated with a greater degree of underperformance compared to their benchmarks.  Hence, market participants may find it useful to consider the impact of fees in determining relative performance.

As we close the first quarter of 2019, we see that Latin America did well for the period. The broad regional index, the S&P Latin America BMI, yielded nearly 9% and the S&P Latin America 40, representing the blue-chip companies in the region, generated returns just shy of 8%. These were in line with the returns for equity markets in Europe and Japan, where the S&P Europe 350^® and the S&P/TOPIX 150 generated returns of 11% and 8%, respectively. The U.S. market did exceptionally well, with the S&P 500^® gaining nearly 14% for the quarter.

All of the GICS^® sectors in Latin American did well, except for Consumer Discretionary, which remained flat. The sectors that significantly contributed to the region’s performance in Q1 were Energy and Utilities, generating 19% and 14%, respectively.

At the country level, Argentina had a strong quarter, generating 10.5% in ARS as measured by the S&P MERVAL Index. The broad country index, the S&P Brazil BMI, gained around 9% in both USD and BRL. Chile’s S&P/CLX IPSA gained 3% in CLP. The S&P Colombia Select had a stellar quarter, gaining 19% in COP. Mexico’s headline index, the S&P/BMV IPC, returned over 4% in MXN. Finally, Peru’s blue-chip index, the S&P/BVL Peru Select, returned nearly 10% in PEN. Overall it was a great first quarter for markets in the region.

When we look at the other segments of each market, we find indices that not only did well in Q1 2019, but also have been consistently positive over longer periods. A good example of this is the S&P Dividend Aristocrats Brasil Index, which gained nearly 13% for the quarter but also had a strong yield of 6.1%, providing investors with double gains. Likewise, the S&P/B3 Enhanced Value had unsurpassed returns of 35% for the one-year period and 39% for the three-year period ending March 2019. In Chile, the S&P/CLX Chile Dividend Index outperformed the country’s flagship index in terms of both returns and yield. Mexico had a good quarter, but many of its core indices were still in the red for the year and longer time horizons. However, there are a few shining stars that have managed to remain on the positive side for the short- and mid-term periods. Some examples of these are the multi-factor S&P/BMV IPC Quality, Value & Growth, the S&P/BMV FIBRAS Index, and S&P/BMV China SX20 Index. In Peru, the Consumer Staples and Financials sectors have proven to be the most consistent performers over the years.

As we continue through the first half of the year with three months gone and nine more to follow, it’s an opportune time to get a feel for the economies of Latin American countries. For 2019, the general sentiment of global economists for the region is positive. 2018 was a year of elections and new governments for many Latin American countries. In 2019, we are starting to see some of these changes take effect, although it is too early to see the actual impacts. Brazil is now armed with new pro-reform leaders, and its GDP is estimated to grow to 2.4% in 2019. As the U.S. economy is expected to slow down, Mexico, which is partly dependent on its northern neighbor, may be seeing a GDP growth of just under 2%. Additionally, the still-pending ratification of the USMCA agreement (formerly NAFTA) and the uncertainty of the new Mexican government’s policies are dampening the economic outlook for 2019. On the positive side, the GDP of Chile, Colombia, and Peru is estimated to increase 3.3%, 3.1%, and 3.8%, respectively. Argentina, which will have presidential elections later this year, is the only country expected to contract by about 1% in 2019, but has a positive outlook for 2020.[1]

Will these positive economic expectations translate into positive market performance? The answer is maybe. Markets with strong economies do not always generate strong results, and vice versa. However, economic fundamentals help to measure the perceived value of companies. Supply and demand, consumer confidence, credit, and market psychology are all factors that affect the value of a stock directly and indirectly, so it is important to see how our markets’ policies and expectations are developing in order to have a sense of what’s to come.

For more information, check out the Q1 2019 Latin America Scorecard.

[1] FocusEconomics. www.focus-cconomics.com. Feb 12, 2019. Country reports.

We recently updated our paper asking Is the Low Volatility Anomaly Universal? The alert reader (and we have no other kind) will have guessed that it is. This is an empirical conclusion, but a theoretical digression might help explain why this is so remarkable.

Low volatility strategies explicitly seek to lower the risk of a portfolio. We learn in basic finance that risk and return go hand in hand. We might therefore expect that with lower risk comes lower return. Except that it doesn’t, as Exhibit 1 below shows. In every market where we’ve developed a low volatility index, it has increased return as well as decreased risk — hence the academics’ description of low volatility’s performance as “perhaps the greatest anomaly in finance.”

Exhibit 1: Universally, Low Volatility Strategies Have Outperformed Respective Asset Class Benchmarks with Lower Risk

Source: S&P Dow Jones Indices LLC.  Data through Dec. 31, 2018.  Data start date varies for each index (see Appendix A of Is the Low Volatility Anomaly Universal?).  Standard deviations are computed by annualizing the standard deviation of monthly returns.  Past performance is no guarantee of future results.  Chart is provided for illustrative purposes and reflects hypothetical historical performance.  Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

Our paper explores the characteristics of low volatility strategies, the most important of which, by far, is that they attenuate the magnitude of market returns — in both directions.  Exhibit 2 below highlights the performance pattern of the S&P 500 Low Volatility Index^®.

Exhibit 2: Low Volatility Strategies Tend to Offer Protection in Down Markets but Won’t Participate Fully in Up Markets

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1990, to Dec. 31, 2018. Biggest declines were months when the benchmark was down more than 2.46%, moderate declines were months when the benchmark returned between -2.46% and 0%, moderate gains were months when the benchmark returned between 0% and 2.45%, and biggest gains were months when the benchmark gained more than 2.45%. Past performance is no guarantee of future results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

When the market is down, Low Volatility is highly likely to outperform; if the market is up substantially, Low Volatility is likely to underperform.  Small positive months are close to a toss-up.  Exhibit 2 summarizes data with respect to the S&P 500 Low Volatility Index, but our paper documents nearly-identical patterns for every other index in our low volatility family.  Our claim that the low volatility anomaly is universal rests not only on its long-term performance, but also in its common response to moves in the underlying market.