Indexology^® Blog

In the first seven trading days of 2019, the S&P 500 had its hottest start since 2003.  That happened following the Fed’s message that it was in no hurry to raise interest rates.  The Fed met again yesterday signaling it might end the interest rate increases, which pushed the S&P 500 up 1.55% for the day (Jan. 30, 2019).  This has put the S&P 500 on track to post its 9th best January on record since 1928, its best January since 1989, and its best month since October 2015 with a gain of 6.95% through Jan. 30, 2019.  In the years including the prior 8 top Januaries, the S&P 500 finished positively 6 times, of which 5 years had gains over 19%. However, the subsequent Februaries were only positive half the time with biggest gain of 5.99% in February 1975.

The S&P 500 had a notable turnaround in January after posting its second worst December on record.  While there were, and still are some major global uncertainties – both domestically and internationally – it seems like the market was being mainly driven by the Fed.  It wasn’t just the S&P 500 but was the entire U.S. equity stock market that was impacted.  All 42 segments of size, style and sector were positive, which has happened in just 11 prior months, last in March 2016.

Half of the 42 segments of the U.S. equity market are on pace to post their best January on record, using data starting Sep. 1989, the earliest available sector data.  Also, some sectors are on pace to post relatively strong record months, for example, the S&P 600 Real Estate and the S&P MidCap 400 Value are each targeting their 4th best month ever, with respective gains of 12.88% and 11.30%.  The S&P MidCap 400 gained 9.87% and S&P SmallCap 600 9.63%, both posting their best Januaries and beating the S&P 500, as they historically have in rebounds.  Energy was the best performing sector, and unsurprisingly (due to hedging,) large caps (+10.24%) lagged the smaller company performance (+18.67%) as oil rose from sanctions on Venezuela and supply cuts from Saudi Arabia.

Lastly, value outperformed growth significantly, especially in small-cap and mid-cap segments.  While the S&P 500 Value only outperformed the S&P 500 Growth by 1.63% in January, the S&P MidCap 400 Value outperformed the S&P Midcap 400 Growth by 2.77%, the most since the 4.18% outperformance in November 2016.  Moreover, the S&P SmallCap 600 Value outperformed the S&P SmallCap 600 Growth by 3.28%, the most since 4.27% of value outperformance in February 2001, and the 10th biggest outperformance on record.

Style, the name for the value (growth) factor, is one of the oldest known investment factors.  It can be defined in different ways, but in the S&P Composite 1500 that includes the S&P 500, S&P MidCap 400 and S&P SmallCap 600, style is measured by growth and value along two separate dimensions, with three factors used to measure each style:

Once stocks are classified into value, growth or a combination of both, the stocks are weighted by market capitalization in the traditional style indices like the S&P 500 Growth and the S&P 500 Value.  Historically, one of these style indices almost always beats the S&P 500.  Going back to 1995, either growth or value outperformed the composite in every year except 2001. Source: S&P Dow Jones Indices

However, the winning style is not known in advance and both styles never beat the S&P 500 in the same year, so picking the winner might be like flipping a coin.  Combining them is difficult also, because only a specific combination that is 54% growth and 46% value produced a more frequently winning combination.  It beat the S&P 500 in 16 of 24 years, more than either style alone with growth winning 15 times and value winning 8 times.  On average, over this time frame, the growth excess return has been 1.3% whereas value has lost 1.4%; however, when growth or value won, its alpha in either style was 4.1% annually.

One way to possibly increase returns is to modify the constituents and weights.  A more modern design to style is used to construct indices like the S&P 500 Pure Growth and S&P 500 Pure Value.  Pure style indices include the stocks ranked in the top quarter of its style, without any overlap, so only about half the parent index is included in pure style.  The other key distinction is that stocks in style are market capitalization weighted versus the stocks in pure style that are weighted by their style ranking.

An example of the resulting constituents shows the pure style eliminates the stocks appearing in both styles of value and growth.  While both pure styles lost in 1996, 1997 and 2008, both won in 2000, 2003, 2004, 2005, 2007, 2009, 2010, 2012 and 2013.  On average when the S&P 500 Pure Value beat the S&P 500, it added 12.3%, and when the S&P 500 Pure Growth beat the S&P 500, it added 9.1%.

In order to explore the deeper reasoning of why pure styles outperform and by how much, S&P Dow Jones Indices recently hosted a webinar (replay here) with external content contributors from BDF, Ambruster Capital Management, Inc.,  and Cardan Capital Partners.  BDF pointed out that while style and factor investing is helpful over the long term, there are certain behaviors to be mindful of when implementing those strategies.  This is since tilting with factors can lead to outperformance compared to simple float market capitalization weighted benchmarks, but factors are not unique to one another.  Ambruster Capital Management supported this with a periodic table of factors showing the performance rotation with all factors outperforming the S&P 500 over the past 20 years.

In S&P DJI’s own research, pure style indices offer a way to more precisely tilt and provide a higher exposure to the desired style that is more representative of what an investor may be getting from an actively managed strategy.  Selection and weighting are the two key drivers of performance differences between style and pure style. The same factors used to select are used to weight, so there is an interaction effect.  Pure style indices have more discriminatory power (ie when value is beating growth). Style indices have market beta near 1.00, while pure style indices have market beta higher than 1.00.

Finally, Cardan Capital Partners showed pure style is a more effective way to capture the old growth and value factors, but that it is important to use both value and growth rather than only value or growth.  When equally weighting growth and value across sizes, almost any of the pure style combinations achieved nearly the best case scenario of the traditional styles. In other words, the worst performers in pure style are near the top of the traditional styles.

Today’s Fed announcement keeping the Fed funds target range at 2.25% to 2.5% was more than simply leaving rates unchanged for the moment. Behind the headlines are changes in their expectations for inflation and the economy and adjustments in their operating procedures:

• The FOMC will be patient as it determines what future adjustments to the target range for the federal funds rate may be appropriate.
• The Fed expects overall inflation and inflation for items other than food and energy to remain near 2%.
• The FOMC views sustained economic expansion, strong labor markets and inflation near 2% as the most likely outcome.

Given this view of the economy and inflation, there is no need to raise rates unless conditions change. The Fed is dropping its plan for gradual rate increases.  It will be closely watching the incoming data, but it won’t rush to judgment.

Supporting this change are continued and gradual reductions in the still overly large Fed balance sheet combined with ample bank reserves that should help curtail any market volatility. The Fed manages the Fed funds rate by adjusting the level of excess bank reserves – the extent by which bank reserves exceed reserves required by regulations and deposit levels – and by setting the interest rate it pays on excess reserves held by banks. By assuring ample reserves, the Fed will be limiting the risk of the kind of market gyrations seen at the end of 2018.

Market expectations align with the Fed’s stance. The CME’s Fed Watch Tool calculates the probability of a rate increase at each FOMC meeting through January 2020. Through the end of 2019, the probability that the Fed holds the rate at its current target is 80% or more. Even in early 2020, the probability of keeping the rate only dips slightly to 73%.

Needless to say, there are no guarantees in anything financial. However, for the moment interest rates seem likely to stay close to where they are.

The S&P Pure Style Indices select and weight securities based on their style scores, unlike the traditional S&P Style Indices. In our previous blog post, we demonstrated that differences in index construction play a major role in the performance differential between the S&P Style Indices and the S&P Pure Style Indices. We estimated that the differences in style purity and weight scheme mostly contributed positively to the excess returns of pure style indices over style indices.

In this blog, we examine the excess returns from a sector perspective. With its higher style focus, we expect the S&P Pure Style Indices may also have more concentrated sector exposures. Therefore, we assess the performance differences between the two style series using sector grouping. In Exhibit 1, we lay out the sector weights for the two style indices compared with their benchmarks.

Across all size segments for value indices, the pure versions had higher concentration in fewer sectors compared with the style indices. One such sector is Consumer Discretionary, where the pure value had almost double the weight versus value.

Interestingly, the sector allocation for pure growth indices was less distinctive compared with growth indices, based on data as of Dec. 21, 2018. Energy was the only sector where pure growth indices had consistently more weight relative to growth for all size segments. A potential reason for this lies in the growth factors used in index construction. Although Energy did poorly in 2018 in terms of price momentum, it increased significantly in terms of earnings and sales growth (which is on a three-year basis).[1] We covered the fundamental analysis for these indices with more detail in the first blog of this series.

But did this higher concentration in sectors detract from performance? Using sector grouping, we computed the performance attribution on an annual basis and reported the average of the figures in Exhibit 2.

We found that stock selection played a larger role in explaining the returns than allocation differences for large- and mid-cap segments when grouped by sectors. The opposite occurred in small caps, where allocation differences among the sectors drove the excess returns. For full details and numbers by sector, please see our paper, Distinguishing Style from Pure Style.

In a following post, we will look at how these indices behave in different market and style cycles and explore implications for those characteristics.

[1]   Based on the Index Earnings Report for the S&P 500, S&P MidCap 400 and S&P SmallCap 600, which can be accessed under the Additional Info tab at https://spindices.com/indices/equity/sp-500, https://spindices.com/indices/equity/sp-400, https://spindices.com/indices/equity/sp-600, respectively.

The S&P Style Indices and the S&P Pure Style Indices have distinct long-term performance differences and risk/return characteristics. We highlighted those in a prior blog where we reviewed the two approaches to constructing traditional style and pure style indices.

What are the drivers of the return differentials between pure style and style? We know that pure style indices differ from style indices in two aspects: weighting scheme and security selection. In this post, we continue to take a deeper dive into these style indices by examining the impact that weighting scheme and style selection have on relative performance.

To estimate the portion of excess returns arising from weighting scheme,[i] we compute the hypothetical market cap weighting of the pure style indices. We then compare the returns of the market-cap-weighted versions to the returns of the actual indices, which are weighted by style score.

Exhibit 1 shows the average annual excess returns of the pure style indices relative to the style indices. The second column shows the average annual excess returns when the pure style indices are weighted by market cap. The difference between the first and the second column is an approximation of the resulting excess returns coming from alternatively weighting. For example, the average annual excess return of the S&P 500^® Pure Growth and S&P 500 Growth in period 1 was 3.68%, of which roughly 3.28% was due to the weighting scheme.

Over the long-term investment horizon, with the lone exception of the S&P MidCap 400 Pure Growth, weighting by style score resulted in positive excess returns compared with weighting by market cap.

Next, we determine the performance impact of holding only pure style securities—those with a style score of 1—compared with the overall style universe, which contains pure and non-pure securities. To test this, we group securities of a given style universe into two groups (pure and blended) and look at the performance attribution using the groupings.

The allocation effect in Exhibit 2 indicates the amount of average annual excess returns that were attributable to style purity between the S&P Style Indices and S&P Pure Style Indices.[ii]

For the most part, the difference in style purity (pure versus blended), as indicated by allocation effect, contributed positively to excess returns, with the exception of the S&P 500 Pure Value. For example, the average annual excess return of the S&P 500 Pure Growth over the S&P 500 Growth over the entire period was 1.43%, of which the difference in value definitions (allocation effect) added 0.83%.

In an upcoming post, we will review allocation differences among sectors for the two style series to see if stock selection remains the main driver of the performance differential.

[i]   It is not possible to cleanly attribute how much of the return difference came from security selection versus weighting by style score. This is because style scores are used in both selection and weighting, creating an interaction effect between the two.

[ii]   Although reported in Exhibit 1, selection effect is not meaningful for this analysis, as it also includes the interaction effect between selection and weighting. Exhibit 2 better represents the impact of the weighting scheme on performance.