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Eighty-one years later...

The year in balance

The Persistence of Non-Persistence

Taking Risk and Making Money

Indexing Beyond Large-caps: What happens to top performing funds?

Eighty-one years later...

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Tim Edwards

Managing Director, Index Investment Strategy

S&P Dow Jones Indices

Harbouring year-end reviews and final accounts, the last weeks of December are infused with nostalgia. In this seasonal spirit, I’d like to draw your attention to an under-celebrated piece of work, completed in the year that Katharine Hepburn, Cary Grant and Shirley Temple saw their debuts on the silver screen. In 1932, Fred had not yet met Ginger, ground had just been broken on the Golden Gate Bridge, and on New Year’s Eve, a joint meeting of the Econometric Society and the American Statistical Association considered the results of an inquiry that opened the debate between active and passive management.

The question “Can Stock Market Forecasters Forecast?” is a natural one to ask. The economist Alfred Cowles III was probably the first to investigate this question empirically. In July 1927, he began collecting information on the equity investments made by financial institutions of the time as well as on the recommendations made by various “oracles” in contemporary financial media, embarking on a multi-year project to record and evaluate their performance. It was a heroic effort: over 7,500 recommendations and transactions tracked and tabulated, against hundreds of stocks prices and dividends collected by hand over 4 ½ years.

Importantly, Cowles didn’t just measure absolute performance. He also compared the returns to what “the market averages” (in his case, the Dow Jones Industrial Average) would have achieved. Using fairly modern statistical techniques1 combined with meticulously hand-drawn charts, Cowles expertly diagnosed contemporary active management: poor on average; appearing skilful most probably through sheer luck.


Source: Cowles ; “Can Stock Market Forecasters Forecast?” ; Econometrica, Volume 1 Issue 3 (1933)

Cowles presented his research on December 31st, rounding off a year in which he also established the Cowles Commission for Research in Economics, subsequently to become a veritable breeding ground for Nobel-prize winning ideas (Robert Shiller’s being the most recently recognised).

And his comparison of stock selection strategies to market averages and random portfolios is thoroughly modern.   With almost identical methods and conclusions2, the progeny of Cowles’ research continue to stimulate debate.


  1. Cowles’ ideas are considerably ahead of their time. His use of playing cards to simulate random portfolios is a more than a decade prior to Stanislaw Ulam’s & Von Neuman’s celebrated first use of the “Monte Carlo” method at Los Alamos in work relating to the development of the hydrogen bomb.
  2. Today a market-cap weighted benchmark is usually seen as the bogey, but it would be more than 30 years before William F. Sharpe explained why.

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

The year in balance

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David Blitzer

Former Managing Director and Chairman of the Index Committee

S&P Dow Jones Indices

The US stock market did very well in 2013, up 25% (before dividends) through December 16th, with better results than the overall economy and most other developed markets.  The one big exception is Japan where the market is up almost 47% in Yen terms, though within a percentage point of the S&P 500 when measured in US dollars.

Looking across the US market, growth and value, and all ten sectors, showed results broadly similar to one-another.  Unlike some past years, no single sector or style accounted for the lion’s share of the gain. 

Sector Rank Price ‘Return
Cons Discretionary 1 36.4%
Health Care 2 34.4%
Industrials 3 32.0%
Financials 4 29.1%
InfoTech 5 21.1%
Consumer Staples 6 20.0%
Energy 7 18.1%
Materials 8 16.8%
Utilities 9 7.1%
Telecomm 10 3.9%

Likewise, growth and value came in very close with growth up 25.9% and value up 24.5%.

Where did the balanced growth come from? Largely the Federal Reserve’s QE 1-2-3 policies which provided liquidity, kept interest rates low and boosted asset prices.  This is also the challenge for 2014: whether or not the Fed begins its tapering after tomorrow’s FOMC meeting, or waits until sometime in 2014, some of the underpinning of the market is going away in the new year.

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

The Persistence of Non-Persistence

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Aye Soe

Former Managing Director, Global Head of Core and Multi-Asset Product Management

S&P Dow Jones Indices

The phrase “past performance is not a guarantee of future results” has never rung more true for active mutual funds. Our semi-annual publication, the Persistence Scorecard, takes a look at the performance of top quartile active funds over three- and five-year consecutive 12-month periods. Based on the most recently released report, out of 265 large cap funds that were in the top quartile as of September 30 2011, only 5.28% (amounting to about 14 funds) remained in the top quartile at the end of September 2013. Only 10.31% of the funds managed to stay in the top quartile in the mid cap space while 8.28% of the small cap funds stayed in the top quartile. The breakdown of each fund category is highlighted in the table below.

Performance Persistence over Three Consecutive 12-Month Periods

Our study finds that performance persistence declined further over a longer-term five year horizon.  Only 3.95% of the large cap funds (amounting to approximately 10 funds) and 1.92% of small-cap funds (merely 3 funds) remained in the top quartile at the end of the study period.  It is worth noting that no mid cap funds managed to remain in the top quartile.

Performance Persistence over Three Consecutive 12-Month Periods

In short, the report is a sobering reminder that we cannot use the past performance figures as the sole or the most important criterion in fund selection.  In addition, the transition matrices in Report 4 and 5 suggest that a healthy percentage of top quartile funds in the subsequent period come from prior period second or third quartiles.

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

Taking Risk and Making Money

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Jodie Gunzberg

Former Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

My colleagues, Daniel Ung and Xiaowei Kang, recently published an article on alternative commodity strategies. Below is an intro and some highlights:

“Ever since the publication of Professor Harry Markowitz’s work in 1952, modern portfolio theory has been one of the cornerstones of asset allocation and portfolio construction. Until recently, the principal building blocks used to construct investment portfolios have always been individual assets or asset classes. However, recent crises have brought into sharp relief the lack of diversification of many investment portfolios, despite appearances to the contrary. In reality, the correlation between traditional asset classes has increased steadily over the past decade, surging to alarmingly elevated levels during the 2008-09 financial crisis. Indeed, seemingly unrelated assets moved in lockstep, and portfolios once thought to be diversified did not weather the storm. This has led to some investors exploring risk-factor-based asset allocation as a potential new framework for portfolio construction, and looking at alternative beta strategies in an effort to rectify the “defects” of conventional market portfolios.”

Risk Weighting is SUPERIOR to Minimum-Variance

“In addition, it is also apparent from the results that the Risk-Weight strategy was far superior to the Minimum-Variance when seen through the prism of risk and return trade-off. Indeed, commodity prices and volatility often go hand in hand with each other, particularly during periods of supply shortage, when both will spike upwards; this is why the distribution of commodity returns tends to be positively skewed. For this reason, merely targeting the lowest level of volatility appears counterintuitive, and a more satisfactory approach would be to target risk reduction by assigning a risk budget across different commodities and sectors.”

Risk Weight Min Variance

Value Strategies Perform when Fundamentals Diverge

“Despite the attractiveness of value strategies, they can experience periods of underperformance too, especially in periods where commodity fundamentals play a secondary role to the general macroeconomic environment in influencing prices. … It follows from this that such strategies are the most effective when the fundamentals of different commodities are divergent, enabling value to be extracted via active selection.”

Value Strategies

Flexible Curve Strategies Perform in Demand Growth Expansion

“Even more dynamic strategies—such as the S&P GSCI Dynamic Roll and the Dow Jones-UBS Roll Select indices—have also garnered much interest in recent years. Unlike their static counterparts, their objective is not only to minimize the effect of contango, but also to maximize the effect of backwardation by adopting a different roll strategy with respect to the term structure of the commodity concerned. In practice, they roll into the futures contract with the lowest implied roll cost when a commodity trades in contango, and roll into the futures contract with the highest implied roll benefit when a commodity trades in backwardation.”

Curve Performance

Momentum Is Worth the Risk in Trending Markets

“An important advantage of momentum strategies is that they may provide downside protection during sharp market corrections, while maintaining upside participation during bull markets… Undoubtedly, these strategies also experience periods of subpar performance. In range-bound markets where there is no clear trend, they are unlikely to generate returns. For instance, in the oscillating markets over the last two years or so, momentum strategies—irrespective of their construction—posted disappointing results, as compared with their benchmarks.”


Liquidity / Transparency Tradeoff

“In light of the changing liquidity conditions, a possible improvement to the static [rolling] approach explored above would be to adopt a dynamic rolling schedule in which the roll would occur over a rolling window that is determined on an ongoing basis, rather than defined in advance… adopting different roll schedules can produce very different returns, depending on the time period in question. Obviously, this would come at the expense of transparency. Finally, the analysis finds no evidence to show that lengthening or shortening the rolling window enhances or reduces return on a consistent basis.”


“Alternative beta strategies can serve a variety of different investment objectives, which may include reducing volatility or achieving tilts to systematic risk exposures… Two main approaches to alternative beta are reviewed in this paper: the “risk-based approach,” which entails reducing portfolio risk; and the “factor-based approach,” which involves enhancing return through earning systematic risk premia, with a focus on the latter. While alternative beta is fairly well established in equity strategy investing, it is still a nascent concept in commodities. However, as a result of investors’ pursuit of better-diversified portfolios and a recognition that systematic risk factors explain the majority of returns, the development of commodity alternative beta products is gathering pace… From our investigation in this study, there appears to be potential benefit in allocating into alternative beta strategies as part of a portfolio’s commodity allocation, and we find that combining risk-based and factor-based commodity strategies has historically delivered higher return and lower risk than passive long-only strategies on their own.”

Please contact us for more information about these ideas. We’d love to hear from you!

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

Indexing Beyond Large-caps: What happens to top performing funds?

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Philip Murphy

Former Managing Director, Global Head of Index Governance

S&P Dow Jones Indices

At S&P Dow Jones Indices, our research indicates that indexing small-cap and mid-cap stocks works as well as it does for large-cap stocks, even though the large-cap segment may be more efficient than its junior siblings. Nevertheless, the popular belief that indexing works better for large-caps is well-entrenched and widely endorsed by advisors, consultants, and other financial professionals.

A look at active fund performance through time, as excerpted from our July 2013 Persistence Scorecard, sheds light on why indexing works irrespective of market efficiency and is at least as effective for small-cap and mid-cap exposure as for large-cap. The figure below depicts performance results over two non-overlapping three-year periods for active funds that achieved first quartile status after the first period.

1st Quartile Funds

  • While 23.2% of top quartile small-cap funds stayed in the first quartile after a second three-year period, almost a third (31.3%) fell to the fourth quartile.
  • Over 1 in 10 (about 11.7%) first quartile small-cap funds were either merged with another fund, liquidated, or changed investment style (diverging from small-cap exposure).
  • An equal proportion of first quartile mid-cap funds remained in the top quartile and fell to the bottom quartile (17.6%).
  • Over 1 in 3 (about 33.8%) first quartile mid-cap funds were either merged with another fund, liquidated, or changed investment style. The large proportion (20.3%) diverging from mid-cap exposure seems to be unique to the mid-cap space. These managers may have more of a tendency to drift upwards or downwards in capitalization focus within their portfolios than large-cap or small-cap managers do.
  • Active large-cap fund performance seems more uniformly distributed from period to period – with more equal proportions of top quartile funds subsequently finishing in second through fourth quartiles. This behavior could be related to market efficiency because higher information levels characteristic of large-cap stocks could drive less differentiation between active funds’ performance; i.e., they inherently may have less active risk.

Contrary to popular belief, the potential inverse relationship between market efficiency and active risk may be good reason to index small-cap and mid-cap stocks. Indexing has shown it can reliably deliver market returns and remain style consistent, whereas investing in active small-cap and mid-cap funds may result in overshooting markets during some periods, undershooting in others, altering style unpredictably, and generally compounding total risk without commensurate reward.

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