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Channeling Maverick and the Maestro: The Fed Cut Rates because “We Were Inverted”

Cboe S&P 500 Buffer Protect Indexes: First Outcome Period Recap

Concentration Concerns

For Active Managers, Staying on Top Is Not Enough

What’s inside the S&P China A-Share Factor Indices? The Impact of Style Risk Factors

Channeling Maverick and the Maestro: The Fed Cut Rates because “We Were Inverted”

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Brian Luke

Global Head of Fixed Income Indices

S&P Dow Jones Indices

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One of the classic scenes from the original Top Gun movie recounts the exchange Maverick (Tom Cruise) had with a MiG-28. Maverick corrects Charlie’s (Kelly McGillis) intelligence report on the Russian fighter jet with his eyewitness account. When she asks how he saw a MiG-28 perform a 4G dive from above, he responds: “Because I was inverted.” Goose (Anthony Edwards) interrupts Mav that it was “we,” not “I.”

Fed Chairman Jerome Powell could have responded the same way when asked why he cut rates today. The treasury yield curve was inverted for the first time since the dark days of 2007. This is cause for alarm as the previous three recessions occurred after the 10-year U.S. Treasury Note yield fell below the three-month yield, as is the case today.

By cutting rates, the Fed is hoping to be ahead of the curve to stave off another recession. History has shown precedent for this. Looking at the S&P U.S. Treasury Current 10-Year Index yield minus the S&P U.S. Treasury Current 2-Year Index yield, the curve inverted the previous two recessions, but it hasn’t fallen below zero in the current cycle, unlike the 10-year/3-month curve.

Then there’s the Maestro. It was former Fed Chair Alan Greenspan’s deft use of the overnight rate during the previous longest bull market in history that gave him the nickname “Maestro” (not less brave than Maverick’s move, by the way). In 1994, Greenspan cut rates despite the strong equity market performance. The S&P 500® climbed 88% from the October 1990 lows and it rallied another 42% before the Fed would tighten monetary policy again. With a bull market long in the tooth and a similar political landscape (an incumbent gearing up for his reelection campaign), Jerome Powell is taking a page out of the Maestro’s songbook by cutting before the yield curve inverts.

History has shown that maintaining exposure to equities during an easing cycle can still be profitable despite substantial prior gains. Throughout the 1990s, Greenspan cut rates a total of 23 times. The S&P 500 responded positively each time, averaging a 16% annual return following each cut. However, his same approach did not work as well in the 2000s after the yield curve inverted and the bull market ended.

It remains unclear whether the Fed is channeling the Maverick move by pushing the limits or Alan Greenspan’s “Maestro” of the 1990s with sustained economic success. Market participants can only wait to see what the consequences of the Fed’s moves might be. For now, investors will have to follow the bond market for clues on the next Fed move.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Cboe S&P 500 Buffer Protect Indexes: First Outcome Period Recap

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Matt Kaufman

Principal and Senior Director, Head of Distribution and Product Development

Milliman Financial Risk Management LLC

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On June 28, 2019 the July Series of the Cboe S&P 500 Buffer Protect Indexes completed their first one-year outcome period (6/28/18 – 6/28/19). The Cboe S&P 500 Buffer Protect Indexes are designed to afford investors defined exposures to the S&P 500 Price Index, where the downside buffer levels, upside growth potential, and outcome period are all pre-determined. The approach taken by the Buffer Protect Indexes is analogous to certain equity-linked strategies used in structured products and indexed annuities—industries with more than $1 trillion in assets in the U.S. alone.

In short, the Buffer Protect Indexes performed as they were designed, exhibiting the same positive return as the S&P 500 Price Index over the outcome period, with approximately half the beta and a significantly lower maximum drawdown. The table and chart below depict the historical performance of two Cboe S&P 500 Buffer Protect Indexes:

  • Cboe S&P 500 15% Buffer Protect Index – July Series: Designed to provide access to the price return of the S&P 500, to a cap, with a built-in buffer of 15%, over an outcome period of one year.
  • Cboe S&P 500 30% (-5% to -35%) Buffer Protect Index – July Series: Designed to provide access to the price return of the S&P 500, to a cap, with a built-in buffer of 30% (beginning at -5%), over an outcome period of one year.

Did the Indexes Deliver a Defined Outcome?

Yes. The Indexes seek to match positive returns of the S&P 500 Index, to a cap, in up markets and in down markets, buffer investors against losses of 15% or 30% (-5% to -35%) over the outcome period. The S&P 500 was positive at the end of the outcome period, and the Buffer Protect Indexes matched the price returns of the S&P 500. Additionally, as a result of the downside buffers and upside caps, the Indexes experienced significantly less volatility and drawdowns than the S&P 500 along the way (while matching the return of the S&P 500 at the conclusion of the outcome period).

Implications

The investment community has been widely tracking the Cboe S&P 500 Buffer Protect Indexes, and the completion of their inaugural one-year outcome period was an important milestone in the adoption of “defined outcome” based investment strategies. This could add to financial advisors’ toolkit as they manage varied risk tolerance levels and investment objectives.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Concentration Concerns

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Craig Lazzara

Managing Director and Global Head of Index Investment Strategy

S&P Dow Jones Indices

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Readers of this morning’s Wall Street Journal learned (on the front page, no less) that many of the largest investors in the U.S. equity market hold similar portfolios.  “The overlap in the top 50 stockholdings between mutual funds and hedge funds…now stands at near-record levels, a study by Bank of America Merrill Lynch found.”  An upshot of increased “crowding” into a small number of popular names also means that “stocks that are comparatively cheap have attracted little interest.”

Here are a few words of qualification, and perhaps comfort, to readers concerned about these issues.

  • It’s impossible for every investor to overweight a stock. If mutual funds and hedge funds are overweight in aggregate, some other investors must be underweight.  (Possible underweights might come from pension funds, endowments, DC schemes, individual investors, etc.)  There’s no particular reason to believe that the overweighted investors are more likely to be correct than the underweighted investors.  Our SPIVA results have consistently shown that the average mutual fund manager underperforms a benchmark appropriate to his investment style.
  • If the market is being driven by a small number of highly-owned names, we’d expect that to show up in good results for momentum strategies.  Indeed, momentum has done well this year – the S&P 500 Momentum Index (essentially the 100 top performers in the S&P 500) has outperformed its parent 500 so far in 2019 (23.5% vs. 22.1%).  But the story is different for the last 12 months: Momentum has lagged (7.2% vs. 8.8% for the S&500).  So concentration in fund portfolios may not be driving the market as much, or as consistently, as feared.
  • Finally, concentration is not necessarily hurting the performance of relatively inexpensive stocks. Value has famously underperformed for most of the past decade, but concerns about concentration in fund holdings are new.  Ironically, for the month of July, the best-performing of our factor indices is…S&P 500 Enhanced Value.   Not only is Enhanced Value ahead of the S&P 500 (3.6% vs. 3.0%), both are well ahead of Momentum.  Despite some investors’ concentration in glamour names, in other words, value strategies have held their own in July’s rally.

The holdings of some institutional investors may be unusually concentrated in the same stocks.  Although the degree of overlap may be a statistical oddity, it should not be a cause for general concern.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

For Active Managers, Staying on Top Is Not Enough

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Berlinda Liu

Director, Global Research & Design

S&P Dow Jones Indices

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S&P DJI’s Mid-Year 2019 Persistence Scorecard may offer a hint of encouragement for active fund managers. Performance persistence, measured over the three-year period ending March 2019, rose from prior periods. Among the domestic equity funds that were in the top quartile as of March 2017, 11.36% were able to go on and maintain their top-quartile status in the subsequent two years. This figure is a substantial increase from six months prior (7.09%) or even one year prior (2.33%).

However, further study of these top quartile funds shows that it is not enough for active managers to stay ahead of the game with one’s peers; the challenge of beating the benchmarks has intensified.

Using the same methodology as the S&P Persistence Scorecard, we first identified the domestic equity funds that made top quartile status as of March 2017 according to their annualized returns from the prior three-year period. These are the same top quartile funds that we refer to in this blog. We then compared these funds with the universe of all domestic equity funds and the broad market benchmark, the S&P Composite 1500®.

Our goal was to examine whether the top quartile status of active funds led to future outperformance relative to their peers and to the benchmark.

Only a fraction of these original top quartile funds managed to stay in the same league for the two subsequent consecutive years. However, the final top quartile funds displayed some remarkable characteristics. First, they collectively navigated the seesawing market conditions of the past year better than their peers. As shown in Exhibits 1 and 2, these funds generated approximately three percentage points of extra returns, as measured by the mean and median. On average, their annualized volatility was 0.78 percentage points lower than that of the peer group category. Exhibit 1 also shows that the risk/return profiles of these funds were more homogenous than the peer group category; the standard deviations of return distribution and volatility distribution were smaller in this group of funds.

However, the advantage of these top quartile funds disappears once we compare them with the benchmark. The S&P Composite 1500 returned 8.79% with 16.38% volatility during the trailing 12-month period ending March 2019. Compared to the benchmark, the top quartile funds on average returned 70 bps less with 179 bps higher volatility in the same period when compared with the benchmark (see Exhibit 2). In other words, beating the benchmark remained challenging even for managers that ranked high in their peer group category.

For more information on how fund performance persisted, read our latest Persistence Scorecard.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

What’s inside the S&P China A-Share Factor Indices? The Impact of Style Risk Factors

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Liyu Zeng

Director, Global Research & Design

S&P Dow Jones Indices

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In our previous blog, our studies indicated that most factor indices in China exhibited distinct return characteristics during up and down markets. To understand the sources that drive differential factor performance, we examined the risk factor exposures and factor impact on the performance of S&P China A-Share Factor Indices[1] based on the Axioma AXCN4-MH China equity factor risk factor model.

As indicated in Exhibit 1, over the period from July 31, 2006, to April 30, 2019, value, small caps, and low volatility were the best-performing risk factors in the China A-Share market. Therefore, exposures to these factors could have a significant impact on portfolio returns.

Different factor indices displayed distinct risk factor exposures (see the Appendix for risk factor definitions). All S&P China-A Share Factor Indices exhibited targeted active factor exposures relative to the eligible universe (see Exhibit 1). Unintended active factor exposures were also observed in various indices. For instance, the S&P China A-Share Short-Term Momentum Index showed strong active exposure to high volatility, expensive valuation, and low dividend yield. The S&P China A-Share Enhanced Value Index had significant active exposure toward large caps, low volatility, and high dividend yield, while the S&P China A-Share Dividend Opportunities Index displayed significant active exposure to cheaper valuation and high profitability. The S&P China A-Share Quality Index exhibited an active tilt toward expensive valuation, high dividend yield, and low beta, while the S&P China A-Share Low Volatility Index had unintended active exposure toward high dividend yield and cheaper valuation.

To understand the main drivers of portfolio performance, we decomposed the active returns of portfolios into different style risk factors, industry factors, and stock-specific risks.

As shown in Exhibit 2, over the same period, most of the underperformance of the S&P China A-Share Short-Term Momentum Index was driven by its exposure to high momentum, high volatility, and expensive valuation. Small caps was the only style factor that had significant positive impact on active returns.

As expected, the value factor was the main driver of the outperformance of the S&P China A-Share Enhanced Value Index. Its unintended exposure to low volatility and high dividend yield also had a positive contribution to its active returns.

The excess returns of the S&P China A-Share Dividend Opportunities Index were mainly driven by its targeted exposure to high dividend yield and associated exposure to cheaper valuation, low volatility, and small caps.

Consistent with the design of the quality index, profitability and low leverage contributed positively to its active returns. However, the unintended exposure to high volatility and expensive valuation generated negative return contribution historically.

Unsurprisingly, low volatility was the main source of the active returns of the S&P China A-Share Low Volatility Index. Its unintended biases to cheaper valuation and small caps had a significant contribution to its outperformance as well.

As we can see from this risk attribution analysis, different factor portfolios had distinct factor exposures, which might drive performance differently. Decomposing the source of active returns can be useful for investors to understand the behavior of factor portfolios in different market environments.

[1]   All portfolio constituents are drawn from the combined universe of the S&P China A BMI Domestic and S&P China A Venture Enterprises Index except for the S&P China A-Share Dividend Opportunities Index. To ensure investability, eligible stocks must have a float-adjusted market capitalization no less than RMB 1 billion and a three-month average daily value traded not below RMB 20 million. The S&P China A-Share Enhanced Value Index, S&P China A-Share Short-Term Momentum Index, and S&P China A-Share Quality Index include the 100 stocks with the highest factor scores, and the stocks are weighted by their score-tilted market cap, subject to security and sector constraints. The S&P China A-Share Low Volatility Index includes the 100 stocks with the lowest realized return volatility, and the stocks are weighted by the inverse of volatility. The S&P China A-Share Dividend Opportunities Index includes the 100 stocks from the S&P China A Composite Index with the highest dividend yield, while meeting earnings-per-share growth criteria, with all the stocks weighted by their dividend yield. The S&P China A-Share Small Cap Portfolio is a hypothetical portfolio, which includes 100 stocks with the lowest float-adjust market capitalization, and stocks are weighted by float-adjust market capitalization. All indices were rebalanced semiannually apart from the S&P China A-Share Low Volatility Index, which was rebalanced quarterly.

The posts on this blog are opinions, not advice. Please read our Disclaimers.