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Vanishing Stocks

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

Vanishing Stocks

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David Blitzer

Managing Director and Chairman of the Index Committee

S&P Dow Jones Indices

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The number of stocks listed in the US is falling. Currently there are 3,758 listed stocks, ten years ago there were 4,500 and 20 years ago the number topped 7,400. The total value of the market, as measured by the total market capitalization of the S&P Total Market Index, continues to rise. As of yesterday it was $27.3 trillion, up 20% from a year earlier.  However, this gain was largely due to increasing stock prices, not to new capital coming into the market.  Not only are there fewer stocks today than earlier, but capital is flowing out of the market.  Two leading reasons for the declining number of stocks are fewer IPOs and more mergers. The explanation for the capital outflows are dividends and buybacks, plus acquisitions by foreign or private companies.

The annual pace of initial public offerings (IPOs) collapsed after the tech bust in 2000. In the 1990s, IPOs averaged 400 per year; dropped to about 150 in 2000-2006 and then to 100 per year in 2007-2016. In the last four years since the financial crisis the number showed little improvement, only reaching 140 per year. Analysts suggest various reasons for the drop: regulatory costs of being a public company, fear of activist investors and, most of all, the ease of raising capital in the private markets.

The stars in the private markets are the unicorns – private companies with valuations over a billion dollars.  Uber, worth about $60 billion is the most famous unicorn, but certainly not the only one. Other household names include AirBnb, Dropbox and WeWork. There are over 100 unicorns in the US and a roughly equal number outside the US. China is second in terms of both the number and the total value.  When a company can reach a valuation of a billion, or ten billion or possibly $60 billion in the private market, it is no surprise that IPOs are slowing down. While some private companies do eventually become public they are older and larger than they were in the 1990s, and may have a better chance of surviving. Moreover, not all the unicorns become IPOs and some that do vanish shortly thereafter. Since 2009, 110 companies left the unicorns list – 61 IPO-ed including Facebook, Tesla and Pandora but 49 were acquired including BATS, LinkedIn and Zappos. Some promising companies like WhatsApp are acquired before they have a chance to go public.

Mergers and acquisitions are another drain on the number of public companies. Bloomberg data shows an average of 7,700 transactions annually since 2005 totaling about $980 billion each year. Similar data from the Institute for Mergers, Acquisitions and Alliances (IMAA) shows that mergers climbed steadily from 1985 to the mid-1990s when the number of listed stocks peaked. Since there the pace has varied somewhat, but the annual number of mergers never dropped below what was seen in 1995.  Anti-trust efforts faded as mergers rose.

While the number of companies was dropping, capital was also leaving the markets. The drain was not due to mergers which only drain capital when the acquirer is a foreign company or private equity. Rather, stock buybacks and dividends together drain about 5% a year out of the US markets. The Federal Reserve’s Flow of Funds data show that from 2012 to 2016, there was negative net issuance of corporate equity of $2.2 trillion. If one examines the S&P Total Market Index divisor it fell 12% from 2005 to 2016 indicating that capital flowed out of the index and the market over that time period.

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

What is VIX Predicting about Future Volatility?

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Hamish Preston

Associate Director, U.S. Equity Indices

S&P Dow Jones Indices

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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

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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

Associate Director, Global Research & Design

S&P Dow Jones Indices

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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

Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

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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.