Indexology^® Blog

S&P DJI’s Craig Lazzara explains how style drift could be responsible for inflating the perception of active manager skill.

https://www.youtube.com/watch?v=bRKYDS7KPjA

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A wise man told me years ago that there are some things you can’t get if you go after them directly.  If you’ve ever watched someone trying to sound interesting, you’ll realize the truth of my friend’s observation.  There are plenty of interesting people out there, of course, but they achieve that status by pursuing the things that interest them, and their enthusiasm attracts the interest of others.

At least in this respect, portfolio management sometimes imitates life.  Factor indices come in many flavors – some tilt toward popularity and momentum, some toward unloved value names, and so on.  One helpful division is between risk enhancers and risk mitigators.  As the name suggests, risk mitigators have lower volatility levels than the parent indices from which their constituents are drawn.  Familiar examples would include such factor families as low volatility, dividend aristocrats, and quality.

One of the remarkable things about these factors is that, over extended periods of time, they’ve all outperformed the S&P 500:

This is remarkable because none of these factors are designed for outperformance.  The Dividend Aristocrats comprise consistent, committed dividend growers; Low Vol screens for low historical volatility; Quality looks for balance sheet strength and profitability.  All three aim to provide protection in down markets and participation in rising markets; they (usually) outperform when the market falls and underperform when the markets rises.

Yet all three defensive factors have outperformed, at a time when the vast majority of actively-managed portfolios have lagged the S&P 500.  They’ve achieved outperformance without going after it.  One reason for this result is the way in which dispersion interacts with returns.

Dispersion measures the degree to which the constituents of an index produce similar results.  If dispersion is low, the impact of deviations from an index – whether by active stock selection or factors tilts – is relatively small.  When dispersion is high, returns are widely separated, and the opportunity for active managers – or factor indices – to add value grows commensurately.  But dispersion varies as the market environment changes:

What the chart above illustrates is that when the market declines, dispersion tends to be high.  When the market rises, dispersion tends to be relatively low.  That means that defensive factors tend to outperform when the payoff for outperforming is above average, and to underperform when the penalty for underperformance is below average.  This asymmetric pattern explains why defensive factors typically capture more of the market’s upside and less of its downside – and, serendipitously, why defensive factors generally outperform over long periods of time.

Readers interested in learning more about defensive factors are invited join our webinar on Wednesday April 29^th at 2:00 PM EDT.  You can register here.

In the first quarter of this year, the China A shares market was on a roller coaster in response to the domestic coronavirus outbreak followed by the spread of coronavirus in other parts of the world. In our previous blog, “How the Chinese Equity Market Responded to the Domestic and Global Coronavirus Outbreak,” we looked into how industries reacted differently during recent market declines and rallies. In this blog, we extend our analysis to the performance of the S&P China A Factor Indices in the first quarter of 2020.

During the period from the day the virus was identified on Jan. 8, 2020, to Feb. 3, 2020, the Chinese equities market plunged by 10.5%. The S&P China A Enhanced Value Index, S&P China A Dividend Opportunities Index, and S&P China A Low Volatility Index decreased 13.2%, 12.2%, and 11.8%, respectively, while the S&P China A Short-Term Momentum Index and the S&P China A Quality Index only suffered 2.2% and 7.5%.

Momentum and value were the best- and worst-performing factors in this period, respectively, which explains the outperformance of S&P China A Short-Term Momentum Index and the underperformance of the S&P China A Enhanced Value Index. The excess return of the S&P China A Quality Index was mainly attributed to its active exposures to profitability, high momentum, and high growth and its negative exposure to value. In the S&P China A Low Volatility Index, the unintended biases to value and low momentum completely wiped out the positive impact of low beta and low volatility, which made the index underperform. Similarly, the unintended exposures to value, small cap, and low momentum caused the underperformance of the S&P China A Dividend Opportunities Index.

During the market recovery from Feb. 3, 2020, to Feb. 24, 2020, the outbreak in China was beginning to see declines in new infection cases, and the broad market increased 14.2% in response. Among the five S&P China A Factor Indices, the S&P China A Short-Term Momentum Index and the S&P China A Quality Index took the lead with gains of 23.5% and 16.7%, respectively, while the other three factor indices lagged the broad market.

During this period, liquidity, high volatility, and mid-term momentum were the best-performing factors, while dividend yield was the worst. This explains the outperformance of the S&P China A Short-Term Momentum and S&P China A Quality indices as both indices had favorable bets on these four factors. In contrast, the unfavorable bets on these four factors resulted in the underperformance of the S&P China A Enhanced Value Index and the S&P China A Low Volatility Index. Although the unintended exposures to small cap and value had contributed positively to the performance of the S&P China A Dividend Opportunities Index, it was not enough to offset the negative impact of its tilts to the dividend yield and low momentum factors.

In the latest market crash following the acceleration of coronavirus infection in the rest of the world and increasing investor concern on a global recession, the broad China A market posted a loss of 11.0% from Feb. 24, 2020, to March 31, 2020. During this period, the S&P China A Enhanced Value Index, S&P China A Low Volatility Index, and the S&P China A Dividend Opportunities Index reacted defensively, posting an excess return of 6.1%, 5.8%, and 3.0%, respectively. The S&P China A Short-Term Momentum Index and the S&P China A Quality Index, in comparison, underperformed the broad market with losses of 13.6% and 11.3%, respectively.

Low volatility, low beta, and low leverage factors behaved defensively in this market drawdown as expected, value, and small-cap factors also generated decent returns. In contrast, exchange rate sensitivity was the worst-performing factor, suggesting the vulnerability of companies with high revenue exposure to offshore markets in this market crash. Although the dividend yield factor generated negative return in this period, the unintended exposure to value, low volatility, and small cap gave a boost to the performance of the S&P China A Dividend Opportunities Index. Most of the underperformance posted by the S&P China A Short-Term Momentum Index and the S&P China A Quality Index was attributed to the unintended exposures to high volatility and expensive valuation.

With the stock market in the midst of a historic slump, many investors may be looking to alternatives to protect against a prolonged downturn. The S&P Strategic Futures Indices are designed to measure the performance of passively constructed, liquid, and transparent solutions by spreading risk evenly across global futures markets utilizing a long/short trend-following strategy to deliver results with little correlation to traditional markets. The recent performance of these indices has reflected their usefulness in providing liquidity and capital preservation during broad market downturns (see Exhibit 1).

The unlevered risk of these indices has historically been nearly half that of U.S. equities (see Exhibit 2).

The S&P Systematic Global Macro Index (SGMI) has had a relatively modest correlation to the S&P 500®, while the S&P Dynamic Futures Index (DFI) and the S&P Strategic Futures Index (SFI) have been negatively correlated to equities (see Exhibit 3). Low and negative correlations can make these strategies attractive to investors looking to diversify their portfolios and preserve capital during periods of broad equity market stress.

While the absolute performance of the S&P Managed Futures Indices was modest over most of the past decade, their performance during equity market drawdowns has been admirable. During the drawdown of close to 50% in the S&P 500 during the global financial crisis, all three indices rallied, and the same has occurred in the first quarter of 2020 (see Exhibit 4).

There are a number of advantages of passive managed futures strategies. Passive strategies may offer an enhanced level of liquidity and lower fees as compared with active managed futures strategies and other alternative strategies, such as real assets and private equity. The transparent, rules-based approach of passive managed futures strategies also improves the ease with which investors can track and benchmark relative performance. Style drift has become a major concern of investors in the managed futures space; many fear managers have made changes to their investment processes over recent years to improve short-term performance relative to the bullish equities market. Passive managed futures solutions based on an index eliminate the risk of style drift.

Finally, from a benchmark perspective, the S&P Strategic Futures Indices seek to represent the performance of a pure strategy, not the fund of fund approach adopted by other benchmarks that combine the actual performance of individual managed futures strategies.

Explore how high volatility and high dispersion can impact passive and active managers’ performance with S&P DJI’s Craig Lazzara.

https://www.youtube.com/watch?v=zdU50uYbvs0

Get the latest Dispersion, Volatility, & Correlation dashboard: https://spdji.com/documents/commentary/dashboard-dispersion-2020-03.pdf