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Is There Merit in Blending Factors in Smart Beta Strategies?

Factor-Based Investing in US IG Corporate Bonds: Volatility and Credit Spread

Looking Beyond the Short Term

Be Careful What You Wish For

Why January's Commodity Performance Is Promising

Is There Merit in Blending Factors in Smart Beta Strategies?

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Priscilla Luk

Managing Director, Global Research & Design, APAC

S&P Dow Jones Indices

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Despite the fact that many single-factor strategies have empirically delivered positive excess returns in the long run, they have suffered periods of substantial underperformance under certain market conditions due to their cyclicality.  Blending a number of desired factors with low correlations is a potential way to attain more balanced and diversified portfolios.  The obvious questions that arise are: Are they likely to achieve better performance?  How do they behave in different financial environments?

Our stylized portfolios that blend six factors (volatility, value, quality, size, momentum, and dividend yield) with four different strategies (marginal risk contribution, minimum variance, Sharpe-ratio weighted, and equity weighted) demonstrated higher risk-adjusted returns than the S&P 500®, with a lower tracking error than most single-factor strategies (see Exhibit 1).

Capture

Over the entire period, marginal risk contribution and equal-weighted strategies exhibited less cyclicality than other multi-factor and most single-factor strategies.  They achieved more consistent and higher excess return than other strategies across various market cycle phases.  On average, they produced higher information ratios and a higher incidence of outperformance during recovery and bearish periods.

The minimum-variance strategy had a significantly lower information ratio and a lower incidence of outperformance in bullish and recovery markets, similar to, but less defensive than, the single low-volatility strategy.  The Sharpe-ratio-weighted strategy performed well in bear markets, but it significantly lagged the S&P 500 in recovery periods.  This suggests that using recent momentum to tilt factor exposures did not improve the risk-adjusted return of the multi-factor portfolio, even though it had a lower drawdown as a result of the strategy moving into cash during the global financial crisis.

For more information on our research on multi-factor smart beta strategies, please click here, where you will also find details about:

  • What is driving risk/return of various smart beta strategies, and
  • How each of the smart beta strategies have performed in different macroeconomic and market environments.

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

Factor-Based Investing in US IG Corporate Bonds: Volatility and Credit Spread

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Hong Xie

Senior Director, Global Research & Design

S&P Dow Jones Indices

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Factor-based investing in equities is a well-established concept supported by over four decades of research. However, factor-based investing in fixed income remains in its nascent stages. Our analysis has found that factor-based fixed income strategies implemented in a rules-based, transparent index can represent an alternative tool for fixed income portfolio construction. In the next few blogs, we will detail our approach to and back-tested results of employing credit spread (value) and volatility as factors in order to systematically construct a portfolio of U.S. investment-grade corporate bonds.

Investment Philosophy
In practice, an active portfolio manager for a corporate bond mandate mostly focuses on credit returns, specializing in expressing views on the direction of credit spreads and security selection. We propose a two-factor model to seek to collect an active return from security selection, identifying relative value opportunity in credit returns while keeping portfolio duration and credit duration natural to the underlying universe.

Two Factors: Volatility and Credit Spread
To achieve better security selection, we chose two factors that empirically have demonstrated a strong relationship between factor exposure and performance statistics and that have long been incorporated in investment analysis by corporate bond portfolio managers. Our selection of factors was by no means exhaustive.

The fixed income investment community has long used volatility in analyzing bond valuations and identifying investment opportunities. We have defined volatility as the standard deviation of bond yield changes for the trailing six-month period. All else being equal, the more volatile the bond yield is, the higher the yield needs to be in order to compensate for the volatility risk.

For the credit spread factor, we consider the option-adjusted spread (OAS), which represents the yield compensation for bearing credit risk and other risks associated with credit. OAS is a common measure of valuation for corporate bonds.

Back-Testing Total Return

Exhibit 1 shows the cumulative total return for our two-factor model versus the broad market. In the next post, we will demonstrate how we identify these two factors.

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

Looking Beyond the Short Term

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Kelly Tang

Director

Global Research & Design

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

The debate continues on the detrimental impact of the short-term mindset of public companies.  Short-termism (a.k.a. quarterly capitalism) is defined as companies’ fixation on managing for the short term, with decisions driven by the need to meet quarterly earnings at the cost of long-term investment.  Short-termism is a problem because it has the potential to undermine future economic growth.  The lack of long-term investment will ultimately lead to slowing GDP, higher unemployment levels, and lower future investment returns for savers—all combined, these effects hurt everyone.  There’s a consensus that the main source of the problem is the tremendous pressure that public companies face from financial markets to maximize short-term results time and time again.  Back in 2013, McKinsey and the Canada Pension Plan Investment Board (CPPIB) conducted a McKinsey Quarterly global survey of more than 1,000 board members and C-suite executives to gauge their long-term approach in managing their companies.

  • 63% of respondents said the pressure to generate strong short-term results had increased over the previous five years.
  • 79% felt pressured to demonstrate strong financial performance over a period of just two years or less.
  • 44% said they use a time horizon of less than three years in setting strategy.
  • 73% said they should use a time horizon of more than three years.
  • 86% declared that using a longer time horizon to make business decisions would positively affect corporate performance in a number of ways, including strengthening financial returns and increasing innovation.
  • 46% said that the pressure to deliver strong short-term financial performance stemmed from their boards; while the board members expressed that they were just channeling the short-term pressures felt from institutional investors.

The results were startling and bring to light how deeply the short-term mindset has permeated corporate culture.  However, the good news is that a coalition of institutional investors is realizing that telling company management to focus on the long term, and thereby placing the entire onus on them, is both unrealistic and ineffectual.  They feel that the only way to shift the mindset to long-term value creation is by calling upon other asset owners who control the assets that companies need to change their current approach.  Asset owners are the key constituents to effect real change and their buy-in to long-term thinking will facilitate the process for other players such as asset managers, corporate boards, and company executives to move away from short-termism.

Our next blog will discuss how CPPIB and S&P Dow Jones Indices worked together to design an index that seeks to address the short-termism undermining global economies.

 

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

Be Careful What You Wish For

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Craig Lazzara

Managing Director and Global Head of Index Investment Strategy

S&P Dow Jones Indices

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One of the few things more reliable than active managers’ general run of underperformance is their confidence that, despite what happened last year, this year will be different.  Two years ago, e.g., active managers were arguably poised to excel because correlations had declined from their financial crisis peaks; a year ago it was active managers’ putative ability to navigate declining markets that provided the rationale.  The data contradict both arguments, of course — there’s no reliable tendency for active management performance to improve when correlations are low or when markets are weak.

When considering whether we’re in an attractive environment for active management — the long-sought “stock picker’s market” — it’s important to bear in mind the difference between the existence of skill and the value of skill.  Suppose I am blessed with the ability to identify stocks whose performance is one standard deviation better than a market index’s average return.  The value of my skill will increase as the spread among stocks in the index widens.  If I were (or thought I were) a good stock picker, I would want to operate in an environment of widely-dispersed returns.

Dispersion, in fact, is a systematic measure of the weighted standard deviation of index component returns, and gives us a way to gauge the potential benefit of active stock selection.  In January 2016, dispersion in the S&P 500 rose sharply, reaching its highest level in more than four years.

S&P 500 dispersion_Jan 2016

One month does not a new regime make, of course, but the trend in the data suggests that S&P 500 dispersion may be beginning to climb above its long-compressed level.  High dispersion goes hand in hand with high volatility, however, and high volatility often signals negative returns.

Thus the irony: active equity managers may finally have the stock picker’s market for which they’ve hoped.  But the price of a stock picker’s market may be, at least in the short run, a period of volatile and negatively-biased returns.

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

Why January's Commodity Performance Is Promising

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Jodie Gunzberg

Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

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Considering commodities were on pace to set the worst January since 1975 at one point, down 14.3% by Jan. 20, the final monthly loss of just 5.2% is impressive. The S&P GSCI Total Return rebounded 10.6% with nine of the twenty four commodities posting gains for the month.

Does this mean commodities hit the bottom or that this is just a bounce in a much darker scenario? That probably depends on the oil supply decisions from Saudi Arabia, Russia and Iran, in addition to Chinese demand growth, the strength of the dollar and the weather. However, an examination of the historical annual performance of the S&P GSCI based on the direction of returns in January for single commodities and sectors gives hope that 2016 may be a positive year.

Again, nine of the twenty four commodities in the S&P GSCI were positive in January. Historically, there is a higher chance the year will end positively than negatively based on the first month’s performance for seven of those commodities. The most interesting statistic of the positive single commodities is that when gold has gained in January, the S&P GSCI has gained for the year almost 3 of every 4 times, or in 72% of the time. Gold gained 5.3% in January 2016, so there may be a 72% chance of a positive year in 2016 for the S&P GSCI, based on that historical data point.

What is more compelling is that of the fifteen negative commodities, only three have had the majority of years ending negatively based on their losing January months. For most of petroleum, the first month’s direction is only as good as a coin flip, but when Brent Crude loses, that has been a good thing in 63% of years for the S&P GSCI. Another namesake commodity, copper, that many watch as an indicator of economic health, lost 3.1% in January, but based on history, the S&P GSCI has gained in 68% of years where copper lost in the first month.

On average, there is a 59% chance of a positive year in 2016 for the S&P GSCI  based on the number of times in history positive years have followed the direction of commodities this past January. The sectors tell the same story with a slightly higher chance, 64%, of a positive commodity year in 2016. Still, the outcome for the year is uncertain, especially since the direction of the January performance of the S&P GSCI itself, doesn’t say much. According to the historical data, there is only a slightly greater chance, 53%, of a negative year than a positive one in 2016.

Source: S&P Dow Jones Indices. Historical performance is not indicative of future results.
Source: S&P Dow Jones Indices. Historical performance is not indicative of future results.

 

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