Indexology^® Blog

In addition to absolute returns, institutional investors also evaluate active funds by risk-adjusted returns. This is not surprising since Modern Portfolio Theory tells us that higher returns tend to be associated with higher risk.

Our Risk-Adjusted SPIVA Scorecard was introduced in 2018 as an extension of the standard SPIVA Scorecards.

• It aims to assess whether actively managed funds generate higher risk-adjusted returns than their corresponding benchmarks.
• We consider volatility, calculated through the standard deviation of monthly returns, as a proxy for risk, and we use return/volatility ratios to evaluate performance.
• Given that indices do not incur costs, we also present gross-of-fees performance figures by adding the expense ratio to net-of-fees returns. In this way, generally, higher risk should be compensated by higher returns.

Now, let’s look at the most recent report from year-end 2019.

U.S. Equity Funds: Scarce Outperformance

The Risk-Adjusted SPIVA Year-End 2019 Scorecard shows that, after adjusting for risk, most U.S. Equity Funds across all categories underperformed their benchmarks over mid- and long-term investment horizons, net of fees. Even on a gross-of-fees basis, outperformance only appeared in a few categories: Real Estate (over 5 and 15 years), Large-Cap Value (over 15 years), and Mid-Cap Growth funds (over 5 years). This is particularly noteworthy since the equity market was experiencing one of the longest bull markets during this period, with S&P 500^® gaining 257%.

International Equity Funds: Most Funds Fell Short

As in the U.S., most international equity funds across all categories generated lower risk-adjusted returns than their benchmarks when using net-of-fees returns. On a gross-of-fees basis, only International Small-Cap funds outperformed over the 10- and 15-year periods.

Fixed Income Funds: Fees Were Critical

Fees played a critical role in fixed income fund performance. When using net-of-fees risk-adjusted returns, most actively managed fixed income funds in most categories underperformed over all three investment horizons. The exceptions were Government Long, Investment Grade Long, and Loan Participation funds (over 5 and 10 years), as well as Investment Grade Short funds (over 5 years). However, unlike their equity counterparts, most fixed income funds outperformed their respective benchmarks gross of fees.

Large versus Small: Size Mattered

On a net-of-fees basis, asset-weighted return/volatility ratios for active portfolios were higher than the corresponding equal-weighted ratios, indicating that larger firms have taken on better-compensated risk than smaller ones.

On a gross-of-fees basis, most fund categories produced higher return/volatility ratios than their benchmarks when equally weighted. However, their outperformance diminished once fees or fund size were accounted for, especially in domestic and international equity funds. In general, equal-weighted return/volatility ratios improved more than the corresponding asset-weighted ratios when fees were ignored, indicating that fees played a prominent role in smaller funds’ performance.

Conclusion

While our SPIVA Scorecards typically show that active funds underperform their benchmarks in absolute returns, defenders often argue that active funds may be superior to passive investment after adjusting for risk. The Risk-Adjusted SPIVA Year-End 2019 Scorecard demonstrates that history showed us quite the opposite: most active funds lagged their benchmarks over the long term, and exceptions were even more scarce when fees were counted for.

Despite the early warning signs of a global pandemic and its devastating potential to obliterate economic growth, it appears that fund managers in Europe generally failed to position themselves appropriately for the storm that was to come.

Taking a sneak peek into our upcoming SPIVA^® Europe Scorecard, we can see the majority of Europe Equity active fund managers were unable to beat the S&P Europe 350^® in Q1 2020.

Month-by-Month

The invisible threat of COVID-19 began to shut down production in many parts of mainland China by mid-January 2020, but the market repercussions took some time to be felt in Europe. By the end of January, Europe Equity funds had only lost 1% of their value on an asset-weighted basis, compared with a 1.3% drop in the S&P Europe 350 benchmark.

Come the end of February 2020, many European-focused investors would have welcomed such returns. European fund returns were down 7.7% for the month, slightly better than the benchmark, which fell 8.6%. At this point, it may have looked like active fund managers had the upper hand and were well placed to continue this outperformance into March.

March 2020 will go down in European stock market history as one of the most volatile months ever (surpassed only by October 2008). European funds lost 15.5% for the month compared with a 14.1% drop in the benchmark.

Tallying it all up, the first quarter of 2020 saw fund returns down 22.7%, while benchmark returns were down 22.4%.

While active managers’ performance in the quarter may appear broadly level with the benchmark, the chances of choosing an active fund that outperformed were not. The majority of Europe Equity fund managers were unable to beat the benchmark in either March or Q1 2020 as a whole, with 66% and 57% underperforming the benchmark, respectively.

The large proportion of underperforming active funds in March 2020 would suggest that despite their ability to time the market and extract value, fund managers broadly failed to utilize their skills and navigate the market in one of the most turbulent months. This is contrary to the widely held belief that market volatility provides a better opportunity for active managers to outperform.

With the COVID-19 crisis not yet over and volatility remaining high, will fund managers’ skill begin to show or will passive benchmarks continue to outperform the majority? Stay tuned for SPIVA Europe Mid-Year 2020 Scorecard to find out more.

The world looks much different than it did three months ago. Since then equities hit their all-time peak, entered a bear market, exited a bear market, and currently sit 15% off peak with sustained higher volatility levels.

The latest rebalance for the S&P 500 Low Volatility Index^®, effective after the close of trading today, rotated out 64 names in the index (63% in weight). For context, the median annual turnover for the last 28 years has been 64%. This quarter’s turnover is notable not just for its size, but also because of some large shifts in sectoral allocation, as shown in Exhibit 1. Low Vol’s weighting in Utilities fell by 21%, Real Estate by 16%, and Financials by 11%, while Health Care (+21%) and Consumer Staples (+13%) witnessed double-digit gains.

By design, Low Vol favors the least volatile sectors, with no arbitrary constraints. This latest rebalance is a good demonstration of how dynamic the index can be, and its size is a function of two things. First, all factor indices are subject to drift. They best embody the factors they’re designed to track immediately after they’re rebalanced. In periods of high dispersion, factor drift is especially likely, and dispersion in the S&P 500 hit near-record levels in March.

Second (and unsurprising in view of the level of dispersion), the volatility of the S&P 500 also spiked since Low Vol’s last rebalance. Importantly, although all sectors were more volatile, the increase was uneven. Exhibit 2 shows, e.g., that the increase in intra-sector volatility for Energy was especially dramatic, and that for Health Care and Consumer Staples more muted.

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Over the past 20 years, the S&P 500^® experienced three bear markets with drawdowns greater than 30%—the 2000-2001 Tech Bust, the 2008 Global Financial Crisis (GFC), and the ongoing coronavirus sell-off.

During both the Tech Bust and the GFC, various U.S.-focused dividend indices outperformed the S&P 500. However, during the coronavirus sell-off, most dividend indices underperformed the S&P 500 (Exhibit 1).

The goal of this blog is to examine the characteristics of those dividend indices and factor(s) that contributed to the broad underperformance this time around.

• Not All Dividend Indices Are Created Equal

Each dividend index family has its own unique characteristics and is constructed with the goal of meeting its investment objective.[1] These indices have varying degrees of quality incorporated into their methodology, and can be incorporated into three broad categories: dividend growers, yield/quality blend, and high yielders.

While the indices are expected to have significant exposure to dividend yield, differences in construction among the indices can lead to differing primary and secondary risk exposures. Using a risk model, the fundamental exposures of U.S. dividend indices were examined relative to the S&P 500 over a period of 20 years from Dec. 31, 1999, to April 30, 2020.

The expected trade-off between yield and quality is such that indices selecting higher-yielding constituents tend to have lower relative profitability and higher debt, and a higher risk of falling into the “dividend traps[2].” Indices that focus on dividend growers or blend yield with measures of quality tend to have lower dividend yield, but dividends tend to be more sustainable because of lower debt and higher profitability characteristics.

Exhibit 3 shows that all the dividend indices had lower exposure to volatility than the benchmark. Additionally, upon examining the exposures to the size factor, it is evident the indices had considerable tilt to small-cap stocks; this comes as no surprise, as the indices are either modified market cap-weighted, equal-weighted, or yield-weighted. The last point to note is that all indices were exposed to low growth stocks.

Historically in bear markets, lower volatility and higher quality stocks have tended to outperform the overall market and those stocks with higher volatility and lower quality (Ung & Luk, 2016). Given the factor exposures, it is expected that indices in the dividend growers and yield/quality blend categories would fare better than indices in the higher-yielding category during bear markets. This is largely consistent with what was observed during the Tech Bust and GFC.

In terms of sector exposure, Exhibit 4 shows that all of the dividend indices in the analysis were considerably underweight the Information Technology sector. Sector exposures are more balanced for dividend growers compared to other strategies, which tend to have positive exposure to Utilities and Real Estate. As defensive sectors tend to perform better than cyclical sectors in bear market, similar conclusion can be drawn from the factor exposure based analysis.

• How Is It Different This Time?

While each scenario had different circumstances and causes, the coronavirus sell-off is driven by the simultaneous exogenous shocks of the pandemic and the oil market collapse. The forced shutdown of the global economy and spillover effect of oil price shock led many companies globally to announce a number of changes to their dividend programs in order to preserve cash.

From a factor performance point of view, the coronavirus sell-off resulted in a number of factors behaving unconventionally. For example, low volatility and low beta factors, which are typically defensive, did not have an outsized outperformance, while growth outperformed value (see Exhibit 5). The abnormal behaviors exhibited by these factors led to the relative underperformance of dividend indices between the Feb. 19, 2020, peak and the March 23, 2020, trough.

Moreover, from a sector perspective, the typically defensive Utilities sector underperformed; while Information Technology outperformed. These contributed further to the broad underperformance of dividend indices. Exhibits 6-8 show the return attribution analysis by factor and sector for each of the three bear markets.

Indices that focus on dividend growers or blend yield with quality shielded investors from large losses during the Tech Bust and GFC, but not during the recent Coronavirus sell-off. The reversal in performance could be explained to some extent by the unconventional behavior of some factors (volatility and growth) and sectors (Utilities and Information Technology).

References

Ung, D. a. (2016). What’s in Your Smart Beta Portfolio? A Fundamental and Macroeconomic Analysis. The Journal of Index Investing, 49-77.

[1] https://www.indexologyblog.com/2020/05/12/sp-djis-dividend-indices-the-importance-of-incorporating-quality-screens/

[2] A dividend trap occurs when a high dividend yield attracts investors to a potentially troubled company.