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What is VIX Predicting about Future Volatility?

Considering Factor Rotation Within the S&P 500 Universe

Rising Above the Noise in ESG: Green Bonds

Nine of Eleven U.S. Equity Sectors Gained Despite Size

The DJIA Crosses 24k

What is VIX Predicting about Future Volatility?

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Hamish Preston

Head of U.S. Equities

S&P Dow Jones Indices

VIX® closed last night at 11.33.  What, if anything, does that mean?

We recently published a research paper, together with a more digestible practitioner’s guide, that provides a method for converting a given VIX level into an expectation for S&P 500® volatility over the next 30 days.  Exhibit 1 shows that these estimates have provided a reasonable, but imperfect, guide for what was observed.

Exhibit 1: VIX-based Prediction Versus Actual Change in S&P 500 Volatility

Source: “A Practitioner’s Guide to Reading VIX”. Past performance is no guarantee of future results.  Chart is provided for illustrative purposes.

The first ingredient in the expected VIX is the present (or recent) volatility environment; expectations for the future are necessarily grounded in the recent past.  Over the past month, S&P 500 volatility ran at an annualized 6.58%.  The next key step is to account for the fact that we expect volatility to mean revert.  The long-term average volatility for the S&P 500 is around 15%, and history shows that in a given month volatility tends to move about 30% of the distance between its current level and that long-term average.  All else equal, this would lead to a realized volatility on January 4, 2018 of 9.10%.  This mean-reverted level is called “MR volatility” in our paper.

The second ingredient is a relationship between MR volatility and the expected VIX; this essentially accounts for the fact that VIX typically reflects a premium that purchasers of options pay for their insurance-like characteristics.  This relationship, for the S&P 500, looks like:

Substituting MR volatility = 9.10 gives expected VIX = 12.56. Last night’s closing VIX level of 11.33 is 1.23 percentage points lower than the expected VIX. But what does this mean?  One explanation is that when VIX is less than expected VIX, market participants are more relaxed than usual about the anticipated impact of upcoming news flow on the S&P 500.  However, a slight subtlety is required before we can say that the market is predicting a decline in realized volatility.

When VIX is different from expected, this indicates an anticipated change in realized volatility that is different from usual.  But mean reversion in realized volatility is usual.   (In the current example, mean reversion is expected to cause a rise in realized volatility from 6.58% to 9.10 %).  Adding the difference between VIX and expected VIX to the MR volatility level gives the resulting “prediction”; realized volatility is expected to rise from 6.58% to 7.87% over the next 30 days (9.10% MR volatility minus 1.23%) – a gain that is less than would be anticipated under mean reversion alone.

Of course, the observed change in realized volatility is extremely unlikely to be exactly 1.29%; Exhibit 1 demonstrates that it might be lower, and it could be much higher.  Nevertheless, and although it is imperfect, our approach allows for a “reading” of VIX that accounts for its major relationships, and offers a practical interpretation of what VIX is telling us. 

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

Considering Factor Rotation Within the S&P 500 Universe

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Derek Babb

Senior Portfolio Manager

Elkhorn Capital Group, LLC

While 2017 is winding down with volatility levels at historical lows, a calmness has remained in the market for quite some time. According to Fei Mei Chan, Director of Index Investment Strategy at S&P Dow Jones Indices, the S&P 500 is on track for its least volatile year in 22 years.

With volatility (or lack thereof) being a favorite discussion topic of market participants, now is a good time to brush up on S&P 500 based factor indices which provide pure exposure to opposing sides of the volatility trade: the S&P 500 Low Volatility Index and the S&P 500 High Beta Index.

Methodology Overview

According to S&P, the S&P 500 Low Volatility Index measures performance of the 100 least volatile stocks in the S&P 500. The index benchmarks low volatility or low variance strategies for the U.S. stock market. Constituents are weighted relative to the inverse of their corresponding volatility, with the least volatile stocks receiving the highest weights.

Its counterpart, the S&P 500 High Beta Index, measures the performance of 100 constituents in the S&P 500 that are most sensitive to changes in market returns. The index is designed for investors initiating a bullish strategy or making a directional bet on current markets.

Bull and Bear Markets

Since the methodologies behind both the S&P 500 Low Volatility Index and the S&P 500 High Beta Index do not have any sector restraints or requirements, sectors weightings may shift over time. This can be positive or negative, as the Low Volatility Index may avoid high beta sectors during bear markets, yet may under-allocate to those same sectors during bull markets.

The opposite may be true of the S&P 500 High Beta Index. The High Beta Index may play the risk-on trade more effectively, perhaps posting higher than market returns during bull markets. Yet, during bear markets, this index may find itself more concentrated in highly sensitive sectors, which may amplify the pain an investor may experience in a bear market.

Considering a Factor Rotation Strategy

Over the last decade, more and more single factor, multi-factor, and factor blending strategies have come to the marketplace. While certain factors, such as low volatility, have consistently exhibited outperformance over long time frames, there are certainly seasons where a given factor will underperform its benchmark. The S&P 500 Low Volatility Index and the S&P 500 High Beta Index are two opposing factors which exhibit periods of high dispersion with one another. While the low volatility factor has proven to generate market-beating returns across multiple business cycles, investors may want to consider a factor rotation strategy between the S&P 500 High Beta Index and the S&P 500 Low Volatility Index to capitalize on the relatively large performance disparity that exists between the two factors during certain periods.

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

Rising Above the Noise in ESG: Green Bonds

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Dennis Badlyans

Former Associate Director, Global Research & Design

S&P Dow Jones Indices

The emergence of ethical and sustainable concerns and the need for environmental investing has come with a wide range of options for fixed income market participants to navigate. One approach has been to rely on evaluation metrics, or ratings that measure the environmental and social impact of companies’ operations. The main challenge of this approach is that currently there is no clear standard of measurement in the market. Researchers at MIT working on the Aggregate Confusion Project found that when they compared “two of the top five ESG rating agencies and compute the rank correlation across firms in a particular year, we are likely to obtain a correlation of the order of 10 to 15 percent. At least the correlation is positive! It is very likely (about 5 to 10 percent of the firms) that the firm that is in the top 5 percent for one rating agency belongs to the bottom 20 percent for the other.”

Green bonds offer an opportunity for market participants to add an element of impact investing into their core exposure in a simple way. Green bonds are not too different than traditional bonds. They work in the same ways as traditional bonds and are issued by a similar issuer base. The key difference between a green bond and a traditional bond is that with a green bond, the issuer lets us know that the proceeds are earmarked for investments in projects that have environmental benefits.

The S&P Green Bond Index is designed to track the global green bond market. However, since green bonds are self-identified, market participants need independent, expert-led guidance on which investments are part of a low-carbon economy. This will ease decision-making and focus attention on credible climate change solution opportunities. In the selection process for the index, S&P DJI partners with the Climate Bond Initiative, which certifies and monitors the usage of proceeds on an ongoing basis. This approach is straightforward and doesn’t require the sophisticated analysis of a company’s behavior.

Historical performance of green bonds has been much like the ubiquitous aggregate index. Over the past year, when regressing the daily returns between the S&P Green Bond Select Index and the Barclays Global Aggregate, there is a 0.93 correlation, a slope of 0.97, and a small positive alpha (see Exhibit 1). That means that market participants looking to green up their portfolio may not need to sacrifice performance. In fact, over the one-year period, the S&P Green Bond Select Index outperformed the Barclays Global Aggregate in U.S. dollar terms (see Exhibit 2).

To tune-in to a further discussion of this topic, please see here.

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

Nine of Eleven U.S. Equity Sectors Gained Despite Size

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Jodie Gunzberg

Former Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

In November, mid-caps led the U.S. equity market with the S&P 400 gaining 3.68%, followed by small-caps in the S&P 600 that gained 3.52% and large-caps in the S&P 500 that gained 3.07%. The S&P 500 logged its 13th consecutive positive month, the longest streak in its monthly history ever (data going back to Oct. 1989.)  All eleven sectors of the S&P 500 were positive, an event that has happened just 13.9% of the time.  Perhaps what is more interesting is that nine of the eleven sectors were positive together across the market caps.  The last time this many sectors gained together in a month across all the market caps was in March 2016.  In total, nine or more sectors have gained together across the S&P 400, S&P 500 and S&P 600 in 19.6% of months in history (since Jan. 1995.)  Consumer Discretionary led both mid (+6.59%) and small caps (+7.53%) in November, making up 11.9% of the S&P MidCap 400 and 15.4% of the S&P SmallCap 600.  For large caps, Telecommunication Services was the best performer, gaining 6.03%, but is the smallest sector comprising just 2% of the S&P 500.

Source: S&P Dow Jones Indices

In November, the size mattered least for the value and growth styles since May 2013.  The difference between value and growth for the S&P 500, S&P 400 and S&P 600 was 0.58%, 0.06% and 0.45%, respectively.  In only four months in history (May 2013, July 2010, Aug. 2005 and May 2004) was the spread so tight between value and growth in mid-caps.  Large caps had just a 22 basis point discount in Feb. 2017 while small caps had a tight discount of 35 basis points in Aug. 2017.  In fact small caps styles have been performing very tightly in 2017, the closest since 2013 and at levels that only come this tight on a monthly basis on average per year 1/3 of the time.

Source: S&P Dow Jones Indices

That said, for the year through November in 2017, the S&P 500 Growth is outperforming the S&P 500 Value by 13.24%, the second most in history with a bigger value to growth discount only year-to-date through Nov. in 1998.

Source: S&P Dow Jones Indices

Lastly, 2017 may not be on pace to set any sector records, but for small caps, the S&P 600 Utilities and S&P 600 Health Care are having exceptionally strong performance, up a respective 26.42% and 21.48% YTD through November, on pace for their second and third best years in history.  On the flip side the S&P 400 Telecommunication Services and S&P 400 Energy are on pace for their second and fourth worst years in history, down 42.55% and 21.27% for the year through November, respectively.

Source: S&P Dow Jones Indices

 

 

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

The DJIA Crosses 24k

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Jamie Farmer

Former Chief Commercial Officer

S&P Dow Jones Indices

Wow.

It may not be experiencing quite the same year-to-date appreciation as bitcoin – nor its volatility, mind you – but by all accounts the Dow Jones Industrial Average has had a remarkable run in 2017.  And, powered Thursday by a gain of 331.67 points (+1.39%), it topped 24,000 for the first time in history.

A few highlights:

  • As of Thursday’s close, the DJIA is up 22.82%. If that level holds, this year will trail only 2013 (with a gain of 26.50%) as the best performing year in the past decade.
  • With 63 new highs already this year, 2017 ranks as the third most prolific year in history, trailing only 1995 and 1925 in the #1 and #2 slots respectively. There have been 52 calendar years when the DJIA notched at least 1 new high and 70 when none were recorded; see below for the top 10 calendar years.
  • With 5 new 1000 point milestones already (20k, 21k, 22k, 23k & 24k), this year is the most active such period on record. It took nearly twice as long for the DJIA to hit the first 1000 points as it has for all subsequent milestones combined.
  • Similarly, the speed with which the DJIA is crossing these thresholds is notable: it has taken only 257 trading days to run through those 5 marks.  By comparison, it took 483 days for the DJIA to move from 18k to 19k.  Of course, there is a big caveat:  it’s important to continue to note that as the DJIA gains in value each successive 1000 point milestone represents a smaller percentage gain.
  • The DJIA has gained nearly 271% from the low of 6,547.05 hit on March 9, 2009 during the depths of the Financial Crisis.
  • Through Thursday’s close, Boeing (BA) with 830.35, UnitedHealth Group (UNH) with 467.66 and 3M (MMM) with 443.64 have been the three largest point contributors to the DJIA’s advance this year.

And, yes, the 2017 column in the chart below is gold – for 24 karat – I couldn’t help myself.


Source: S&P Dow Jones Indices LLC. Data as of Nov. 30, 2017. Past performance is no guarantee of future results. Chart is provided for illustrative purposes.


Source: S&P Dow Jones Indices LLC. Data as of Nov. 30, 2017. Past performance is no guarantee of future results. Table is provided for illustrative purposes.

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