Indexology^® Blog

Over a three-year period, the annualized returns of the U.S. preferred market have been more bond-like than equity-like.  The S&P U.S. Preferred Stock Index had a three-year annualized return of 7.95% as of March 27, 2015 while long U.S. Treasury bonds have returned 8.14% in the same period.  Meanwhile, the three-year annualized return of the S&P 500 has been well over 15%.  All of this is pointed out by J.R. Rieger in his recent blog post: U.S. Preferred Stock: Equity & Bond Characteristics Helping or Hurting Performance?

In order to address the growing interest in the infrastructure market, S&P Dow Jones Indices recently launched an index designed to track an additional segment of the preferred market: the S&P U.S. Preferred Infrastructure Stock Index.  The index has returned 0.03% MTD and 4.96% YTD on a total rate of return basis, as of April 2, 2015.  Returns for 2015 have all been positive at 3.37% (January), 1.11% (February), and 0.39% (March), while the dividend yield was 5.88% as of April 2, 2015.

As mentioned in J.R.’s post: “While it is easy to relate the performance of preferred stock and long-term bonds to interest rate changes, the two asset classes have shown a low correlation to each other over the last three years.  Actually, the S&P U.S. Preferred Stock Index has had a higher correlation to the S&P 500 than it did to long-term bonds.  There is a danger in just looking at the last three years, of course, as interest rates have been held low during the period.”

Below are three visuals.  The first reports on the three-year correlation across four index types, while the second shows the returns of the S&P U.S. Preferred Infrastructure Stock Index.  The graphic that concludes this piece reports on the historical total returns of U.S. preferred infrastructure stocks.

Source: S&P Dow Jones Indices, LLC.  Data as of April 2, 2015.  Past performance is no guarantee of future results.  Charts and tables are provided for illustrative purposes and may reflect hypothetical historical performance.  Please see the Performance Disclosures at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

This is the third in a series of blog posts relating to the in depth analysis of performance differential between the S&P SmallCap 600 and the Russell 2000.

As we noted in the previous post, the reconstitution effect seen in the Russell 2000 doesn’t fully explain the differences in returns between the S&P SmallCap 600 and Russell 2000. Our analysis turns to factor testing, first using the Fama-French three-factor model, which includes the Market, Size and Value factors [1]. All three factors are statistically significant in explaining the index returns, though the S&P SmallCap 600 shows a statistically significant unexplained positive alpha (Intercept). The market factor is similar between the two indices, while the size and value factors differ. The size coefficient is larger in the 2000, leading to the conclusion that the Russell has more exposure to smaller capitalization companies. The 600 has a higher value factor coefficient, thus being tilted more towards value companies versus the 2000.

[1] Fama and French, 1993

With a statistically significant unexplained alpha present in the three-factor model for the 600, additional factors are added to the analysis with the introduction of two separate four-factor regressions models.

The first model incorporates the momentum factor (WML) first introduced by Mark Carhart [1], to the traditional Fama-French three-factor model. Momentum, the tendency for stocks to exhibit persistence in their relative performance, is a well-known anomaly in investing and gives sufficient reasoning to test its efficacy in explaining small-cap returns. As shown in the exhibit below, the momentum factor fails to add explanatory power to the three-factor model, with both coefficients near zero and both t-statistics insignificant.

[1] Carhart, 1997

The second model incorporates the quality factor (QMJ) first introduced in a paper by AQR, defined as companies that are profitable, growing and well managed [1]. The authors go on to mention that investing in high quality companies earns significant historical risk-adjusted returns. When the quality factor is added to the Fama-French model, interesting effects are seen in the output. In both indices, quality is positive, but the factor is larger for the S&P SmallCap 600 and statistically significant (it is not significant in the Russell 2000). In addition, the unexplained positive alpha of the S&P SmallCap 600 is no longer present- leading to believe that quality is a driving factor in the excess returns. Since profitability is a component of quality, the positive earnings screen implemented in the S&P Dow Jones Indices methodology could be seen as a contributor to the larger factor loading in the 600.

[1] Asness, Frazzini and Pedersen, 2014

The past month was a wild ride for U.S. Treasuries, and April seems to be starting out the same.  The yield of the S&P/BGCantor Current 10 Year U.S. Treasury Index closed the half-day trading session for the Good Friday holiday (April 3, 2015) at 1.86%.  The yield is at a two-month low, as rates have bounced around since the 1.81% reached on Feb. 5, 2015.  Friday’s speculation that the Fed won’t be able to raise rates anytime soon came off the back of a slowdown in job growth, as measured by the Change in Nonfarm Payroll number, which was 126,000 versus the surveyed and expected 245,000.

Prior to Friday’s trading, the yield of this index had increased by 13 bps, reaching 2%, after a 1.87% monthly low on March 24, 2015.  This low had resulted from a rally down in yield (38 bps) after the monthly peak of 2.25% on March 6, 2015.  The return of the index as of the end of March was 0.76% MTD and 3.06% YTD, while in April, the index has returned 0.66% MTD and 3.74% YTD (as of April 3, 2015).

Exhibit 1: Index Yield to Worst

Source: S&P Dow Jones Indices LLC.  Data as of April 3, 2015.  Charts and tables are provided for illustrative purposes.  Past performance is no guarantee of future results.

Recently, I seem to have gotten a bit addicted to online shopping, after experiencing the ease of online transactions and the constant exposure to multiple options.

Choice is important, and we are increasingly becoming spoiled by abundant choices in our everyday lives, be it with consumer goods or investments.  Online transactions are gaining popularity, not only due to their ease of execution, but also because of the convenience of being able to compare a varied number of options that meet one’s needs.  Furthermore, there is an increased awareness of new market entrants and ideas in the online space.  When there is a plethora of options from various sources, it becomes critical to be organized in order to evaluate them.  Hence, classification is essential.

This is applicable to financial market indices, as well.  There are multiple markets globally, with regional preferences and different rules and standards governing each one.  However, there are some common classifications that can be used to create comparable indices across regions. For example, every market does classify its components into large-cap, mid-cap and small-cap companies.  While the market itself could comprise various sizes based on regional capabilities, there seems to be standardization and a clear trend on how this classification is done.  The large-cap classification generally represents a significantly large percent of the total market capitalization, typically over 50%, followed by the mid-cap category, normally in the range of 10%-15%, and finally the small-cap label, which usually consists of a small percentage of total market cap.

Index classification is not only restricted to market capitalization—there are a number of other categories to choose from, as well.  Regional indices cover areas like the U.S., LATAM, APAC, EMEA, etc.  The regional offerings can be further defined into sub regions and countries.  There are sector indices offering other splits, like information technology, auto, banking and financials, manufacturing, etc., as there are many sectors that can prove useful to market participants and have a clear classification.  Additionally, there are an asset class-based index, which means there are either equity, fixed income, or commodities in the index universe.  While the aforementioned classifications are fairly generic for indices, there are also other classifications that offer access to a specific strategy or theme.  For example, S&P Dow Jones Indices has created the Shariah index series, which uses screening techniques to provide a variety of indices that are Shariah compliant, and this series is subdivided by region, as well.  In India, the S&P BSE 500 Shariah is the regional offering.  Themes such as asset allocation, dividends, etc. can also be used to classify indices.  Finally, custom indices can be created from standard classifications, offering another wide range of choices.

The classification of indices offers product providers the choice to create a range of offerings for investors.  Index providers are recognizing the need for choices and are creating innovative and varied options to suit market requirements.

Lower yields and newly issued coupons have added an element of danger to fixed income investing.

The following chart shows that since September 2013, the weighted average coupon of the S&P U.S. Issued Investment Grade Corporate Bond Index has trended down, as higher-coupon bonds are called away and lower coupon new issuance is added to the index at the monthly rebalancing.  The result of a lower coupon for the index is that the modified duration has been moving up, or longer out on the curve.  The modified duration of the index is currently at 6.9 years, and the coupon is 4.35%.   The index has returned 0.41% MTD and 2.11% YTD as of March 31, 2015.

As issuance in the primary markets hits record levels, lower coupons, yields, and longer bonds could change the characteristics of an index.

• The lower the bond’s coupon or yield, the higher the duration and volatility of price. Bonds with low coupon rates and lower yields will have a higher duration than bonds that pay high coupon rates or offer higher yields.  Because the bond pays a low coupon rate, the holder of the bond receives repayment of the bond at a slower rate.
• Longer-maturity bonds also have higher durations and are exposed to more risk.
  

 
Source: S&P Dow Jones Indices LLC.  Data as of March 31, 2015.  Charts and tables are provided for illustrative purposes only.  Past performance is no guarantee of future results.