Get Indexology® Blog updates via email.

In This List

Pure Style Eliminates the Muddle in the Middle

Recession Rumors

Details of the Two-Factor Model

Can Sustainability Be Quantified?

2015 - The Year of Hope and Despair for the India Market

Pure Style Eliminates the Muddle in the Middle

Contributor Image
Shaun Wurzbach

Managing Director, Head of North American Client Coverage

S&P Dow Jones Indices

Financial advisors who implement style investing seek to outperform the blended benchmark whenever they believe that market conditions will favor either a growth or a value approach.  Their view could be influenced by research, fundamental factors, or technicals.  To implement such a view does not require 100% conviction in either growth or value.  In fact, some prefer to “tilt” toward growth or value by maintaining a reduced position in the less-favored style.  As a hypothetical example, advisors have shown me portfolios with a 60% weighting in value and 40% in growth.  Such an example overweights value stocks compared to the blended benchmark.

If we accept that some style investors “tilt” as their implementation technique, then we recognize that these advisors are creating a mixed basket of stocks that have a combination of growth and value characteristics.  In accepting this mix, many advisors overlook that the overlap in styles is more profound than they may expect based on a “technical” term that I call “the muddle in the middle.”

This “muddle in the middle” is a side effect of the way most index providers create style baskets.  Using the S&P 500® as an example, Exhibit 1 shows how the S&P 500 Growth and S&P 500 Value are constructed.


While this index construction technique has existed for many years and is widely practiced, it is less understood that the stocks in the middle, or blend basket, are assigned to both the growth and value indices.  This “muddle in the middle” currently leads to 172 overlapping stocks in the S&P 500 Style Indices that don’t have strong growth or value characteristics (see Exhibit 2).


The S&P Pure Style Indices were created to measure concentrated style expressions while eliminating the blend basket.  The S&P Pure Style Indices measure, select, and retain only the strongest growth and value stocks and weight the constituents in accordance with their style score.  The two approaches to basket selection can be compared in Exhibit 3 with the S&P Style Indices on the left and the S&P Pure Style Indices on the right.


The S&P Pure Style Indices seek to create style baskets without any stock overlap.  The S&P Pure Style Indices eliminate the “muddle in the middle” problem for style investing (see Exhibit 4).


The ramification for advisors employing a style tilt is that the same 60% value and 40% growth tilt imagined before now results in zero stocks overlapping in the resulting portfolio, instead of 172.  S&P Dow Jones Indices has over 10 years of live index history for the S&P Pure Style Indices (launched on Dec. 16, 2005) that can be shared with advisors in the S&P 500, S&P MidCap 400®, and S&P SmallCap 600® size classifications.

Sam Stovall, Equity Strategist at S&P Global Market Intelligence, plans to cover S&P Pure Style Indices as Smart Beta in one of his “7 Rules of Wall Street Strategies” at our FA Forum in Miami on Feb. 24, 2016.  Advisors may register at no cost to attend in person or by live streaming.

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

Recession Rumors

Contributor Image
David Blitzer

Former Managing Director and Chairman of the Index Committee

S&P Dow Jones Indices

One sign that people are worried about a recession is getting questions about one on days the market rises.  There seem to have been more down days than up days since the start of the year and the recession question is being asked more on all days.

The current recovery is weaker than other recent rebounds. The first chart compares the last several recoveries and expansions by indexing each one to 100 at the quarter of the pre-recession peak.  The horizontal axis is the time dimension measured in quarters. The thick black line at the bottom is the current recovery. The low point took a bit longer to reach than some other recession/recovery cycles; the track is below all the other cycles shown on the chart.

To paraphrase Mark Twain, predicting recessions is quite difficult, especially about the future.  One theory popular in the press is that as recoveries get older they get weaker and eventually collapse into the next recession. Though this may be an appealing analogy to nature, the statistics don’t support it.  Research, including a recent note published by the San Francisco Federal Reserve Bank, shows that since the end of the Second World War, there is no link between longevity and the timing of the next recession.  Then there is the stock market which Paul Samuelson noted successfully predicted nine of the last five recessions. Doubters can examine the second chart which shows the S&P 500 and the recessions since 1947.

In fact, most recessions weren’t even recognized until a few months after they began.  At the moment recession fears seem to be overdone – the unemployment rate is falling, weekly initial unemployment claims are far below any danger zone and consumers are busy buying houses and cars.

I will speak more on recessions and the outlook during my keynote at the upcoming CBOE Risk Management Conference.  Register:

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

Details of the Two-Factor Model

Contributor Image
Hong Xie

Former Senior Director, Global Research & Design

S&P Dow Jones Indices

After identifying value and low volatility as factors that can effectively explain the return and volatility of an investment-grade corporate bond portfolio, we proposed a two-factor model to capture the security selection process of active corporate bond managers.

The underlying universe for our study is the S&P U.S Issued Investment Grade Corporate Bond Index from June 30, 2006, through Aug. 31, 2015.  To enhance the liquidity profile and tradability of the index portfolio, we first derived an investable subuniverse, applying seasoning and outstanding amount as criteria.  Of that investable subuniverse, the bonds were then divided into groups based upon their effective duration and credit rating.  Within each group, bonds were selected by credit spread and low volatility factors; bonds with Libor OAS wider than the median level of the group were ranked by yield volatility, and only the 20% of those ranked bonds with the lowest volatility were then selected.  The weights of selected bonds were designed in such a way that the weight for each grouping matched that of the underlying base universe.

Utilizing a volatility factor is a key step in the index component selection process.  Without the overlay of this factor one is simply picking the cheapest bonds with the widest OAS and, therefore, most likely piling on credit risk.  Screening first by OAS results in a pool of bonds that have higher potential for spread tightening and better carry.  The subsequent low-volatility screening is designed so that bonds with less risk, as demonstrated by their trading pattern, are selected, while duration and credit rating are held equal.  One can think of our selection process as identifying the cheapest bonds with wide credit spreads that are not justified by their historical trading volatility in their respective duration and credit groups.

Exhibit 1 shows the improved risk-adjusted return of the two-factor portfolios versus the underlying universe.  The Sharpe ratio for the two-factor model improves to 1.15 (monthly rebalancing) or 1.05 (quarterly rebalanced) from 0.87 of the base universe.  The two-factor model also provides better downside protection, demonstrated by a maximum drawdown of 13.28% (monthly rebalancing) or 13.69% (quarterly rebalanced) compared to 14.57% of the base universe.


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

Can Sustainability Be Quantified?

Contributor Image
Kelly Tang

Former Director

Global Research & Design

This is the second in a series of blog posts relating to the launch of the S&P Long-Term Value Creation (LTVC) Global Index.

The Index

S&P Dow Jones Indices collaborated extensively with the Canada Pension Plan Investment Board (CPPIB) over the past nine months to create an index that seeks to measure the performance of global firms that are considered on track to create long-term value.  Long-term investing requires looking at metrics that go beyond the standard GAAP financial accounting measures.  The S&P Long-Term Value Creation (LTVC) Global Index incorporates S&P Quality Scores but goes further, including long-term sustainability scores.  Sustainability (or ESG) scores garner many questions, as there is no uniform, widely accepted methodology on how to measure sustainability.  This blog will dig deeper into how our partner, RobecoSAM, a sustainability asset management and research company, approaches formulating its Economic Dimension Scores, which are used in the S&P LTVC Global Index.

RobecoSAM and Economic Dimension Scores

For the qualitative assessment in the S&P LTVC Global Index, we relied on the Economic Dimension scores (ED) provided by RobecoSAM.  Each year, RobecoSAM conducts an annual survey, the Corporate Sustainability Assessment, covering over 2,500 publicly traded companies with a 100-question survey on financially relevant economic, environmental, and social factors.  Based on the sustainability data collected through the survey, each company is assigned a total score, as well as a component economic, environmental, and social score.  The ED score is RobecoSAM’s governance score, which focuses largely on corporate governance criteria such as board independence, board effectiveness, management incentives, and vesting.  However, the differentiating factor for RobecoSAM’s ED score is that it also covers a series of criteria that evaluate the quality of a company’s management systems as well as its ability to manage issues over the long term.  ED scores are at the intersection between extra-financial information and financial data, and they evaluate a company’s ability to plan the business proactively in relation to long-term opportunities and risks.

The ED scores are calculated using a combination of both general and industry-specific questions.  The following are the general criteria used across all industries.

  1. Corporate Governance
  2. Risk and Crisis Management
  3. Codes of Conduct/Compliance/Corruption and Bribery
  4. Antitrust Policy
  5. Customer Relationship Management
  6. Brand Management
  7. Innovation Management
  8. Supply Chain Management
  9. Tax Strategy

There is also a series of sector-specific criteria, with the applicable industries in parentheses.

  • Anti-Crime Policy/Measures (Financials)
  • Financial Stability and Systemic Risk (Financials)
  • Efficiency (Utilities)
  • Market Opportunities (Utilities)
  • Reliability (Utilities)
  • Water Operations (Utilities)
  • Exploration and Production (Energy)
  • Gas Portfolio (Energy)
  • IT Security and System Availability (Information Technology)
  • Privacy Protection (Information Technology)
  • Marketing Practices (Pharmaceuticals)
  • Product Quality and Recall Management (Pharmaceuticals)
  • Fleet Management (Airlines)
  • Compliance with Applicable Export Control Regimes (Aerospace/Defense)
  • Health and Nutrition (Food Products)
  • Independence of Content (Media)
  • Payment Transparency (Materials)
  • Principles for Sustainable Insurance (Insurance)

RobecoSAM has been conducting its questionnaire since 1999 and has established itself as a leader in the sustainability assessment arena.  While some may view sustainability as too qualitative to assess in a simplified, readily understandable manner, RobecoSAM has applied a quantitative, structured, and consistent approach to assess companies vis-à-vis long-term ESG metrics.

The next blog will analyze the S&P Quality Score and the role it plays in the structure of the S&P LTVC Global Index.

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

2015 - The Year of Hope and Despair for the India Market

Contributor Image
Mahavir Kaswa

Former Associate Director, Product Management

S&P BSE Indices

The calendar year (CY) 2015 started with high optimism among domestic and international investors that the recently (September 2014) formed Modi Government would be able to push a reform agenda to help clock GDP growth in India from 8%-10%, if not more. The high expectations could be seen as the S&P BSE SENSEX reached an all-time high of 30,024.74 on March 4, 2015.

Exhibit 1: S&P BSE SENSEX Performance During CY 2015
Sensex Ex 1






Key macroeconomic factors such as falling inflation, falling crude oil prices, current account deficits, and fiscal deficits showed improvement during CY 2015. However, dismal corporate earnings, a poor (or below average) monsoon season, fear of the U.S. Fed increasing interest rates, and concern over the expected slowing of China’s economy were the negative factors for India’s economy throughout the year.

For CY 2015, the S&P BSE SENSEX noted a total return of -3.68% (and price return of -5.0%). The March quarter (Q1) showed the best total return, at 1.85%; in line with global stock markets, the September quarter (Q3) noted the worst total return, at 5.45%, which was primarily on account of growing concern over the slowing of the Chinese economy.

Sensex Ex 2



Let’s See the Contribution of Stocks and Sectors to the S&P BSE SENSEX Total Returns During CY 2015

Stock Contribution

As opposed to other information technology stocks in the index, Infosys Ltd. noted an impressive total return of 14.79%, contributing the most out of all other constituents during the CY 2015 and helping the S&P BSE SENSEX gain 1.15% for the year. Reliance Industries, with its enhanced oil-refining margins and high expectations for the launch of Reliance Jio (an upcoming provider of mobile telephony, broadband services, and digital services), noted positive total returns of over 15%, which pulled S&P BSE SENSEX up by 0.97% at the end of 2015.

The S&P BSE Bankex was down by over 9% during 2015, which can be seen from leading bank constituents that are part of the S&P BSE SENSEX, such as the State Bank of India and ICICI Bank Ltd.; each were down by over 25% and dragged the S&P BSE SENSEX down by 1% and 2%, respectively. However, the HDFC Bank noted total returns of over 14%, helping S&P BSE SENSEX gain by 1.12% for the year.

Sensex Ex 3




BSE Sectors Contribution

Historically, the service sectors such financials and information technology have had significant weights in the broader Indian market and S&P BSE SENSEX.

Out of the 10 BSE sectors, information technology, consumer discretionary, and energy were the only sectors that pulled the S&P BSE SENSEX up in CY 2015. Impressive performance by Infosys Ltd, the falling Indian rupee, low commodity prices, and falling crude oil prices were considered the key reasons for the good performance of these sectors.

Industrials, financials, and materials pushed the S&P BSE SENSEX down the most out of the other BSE sectors. Dismal corporate earnings, low credit growth, rising NPAs, and falling commodity prices were the potential causes of poor performance by these sectors.

Exhibit 4: BSE Sector Contribution to the S&P BSE SENSEX Total Returns During CY 2015 Sensex Ex 4


Despite global concerns, India is considered by many to be a bright spot in the coming years (for the medium to long term), assuming internal demand picks up and macroeconomic factors improve; however, there are differences of opinions over the short-term outlook.

The first month of 2016 noted negative total returns of 4.75%, which was the third consecutive month with negative returns. Many hopes have been set on the passage of important legislation such as the GST and Land bills, as well as on the coming budget at the end of February.

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