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The Source of Uncertainty

Dow Jones Industrial Average® 2016 Year in Review

Year in Review: 2016 Asset Class Performance

Most Major Islamic Indices Lag Conventional Benchmarks in 2016 as Strong Q4 Financials Sector Gains Detract From Performance

A New Metric for Smart Beta: The Cost-Adjusted Factor Efficiency Ratio

The Source of Uncertainty

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David Blitzer

Managing Director and Chairman of the Index Committee

S&P Dow Jones Indices

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In 2017 politics, not economics will be the major source of market uncertainty.  The world’s major economies moved past the financial crisis and Great Recession: unemployment rates are at more acceptable levels and central banks are discussing the end of quantitative easing. Equity markets in the US and the UK made new all-time highs while those in Europe, Japan and Australia are well above their lows.  Yields on ten-year treasuries are rising in the same countries. Inflation remains low and deflation worries have faded away.

Just when investors thought they could look forward to less complicated times, politics re-appeared with Brexit, oil, the new administration in Washington and elections in France and Germany.  Politics is the focus now.  Many investors follow economic calendars for events like the employment report on the first Friday of each month. A political calendar may be useful as well — a few likely events are cited below. By late this year uncertainty won’t be erased but some direction might be visible.

Shortly after the January 20th presidential inauguration we are likely to see proposals and bills appear on Capitol Hill with details on tax cuts and spending increases.  These will be closely watched but will contain little real information for investors until they are close to being enacted.   Every president since Franklin Roosevelt made promises about the first 100 days – and only Roosevelt in 1932 achieved much in his first 100 days. If either tax cuts or infrastructure spending are enacted before Brexit’s article 50 is invoked, it will show unexpected speed.

Brexit came on the scene last June with the British vote to leave the EU. Recent remarks by British Prime Minister Theresa May suggest a “hard Brexit” with very limited migration allowed between the UK and EU and a need for several new trade agreements.  The first step is to invoke Article 50 to start the clock running on two years of negotiations on new rules of engagement between Britain and Europe. Article 50 is promised by the end of March but few expect everything to be settled in two years. For markets, some clarity may be found when both sides explain what they want. As talks drag on there could be periodic swings in the pound and euro against each other and the dollar.

Elections in 2017 in France and Germany will also be closely watched. In France Election Day is April 23rd with a run-off on May 17th.  One question is whether the populist anti-elite pattern seen in Brexit and Donald Trump’s US victory will carry over to France. Any sign of populist or nationalist gains could reverberate through markets in Europe and the US.  The German election in the fall may be a larger test of populism because Angela Merkel will be running for re-election. Germany’s election must be held between August 27th and October 22nd 2017; a September date is likely.

Politics and oil often mix. The recent agreement among OPEC to reduce output, which boosted oil prices over $50 per barrel, was built on political agreements within OPEC and outside with Russia and other producers. The cuts took effect on January 1st and are planned to last for six months.  With the rig count in the US and Canada already creeping up, the oil markets may look different in June.

Just because politics is the source of uncertainty investors shouldn’t forget the fundamentals of earnings, inflation and growth – they’re what matters in the long run.

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

Dow Jones Industrial Average® 2016 Year in Review

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Jamie Farmer

Chief Commercial Officer

S&P Dow Jones Indices

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The Dow Jones Industrial Average ended 2016 at 19,762.60 – up 2.337.57 points for a 13.42% annual return, the best year since 2013 when the market surged over 26%.

  • Biggest Themes – markets were driven by the crash (and partial recovery) in oil prices, Fed-watching, China, Brexit and questions regarding the US economy. Oh yeah, there was a Presidential Election too – it was so under-reported I almost forgot to mention it.
  • Leader & Laggard – Goldman Sachs (GS) contributed the most to the DJIA’s advance during the year; Nike (NKE) was the biggest detractor.
  • Sector Performance – Financials were the best performing sector during 2016; the Consumer Discretionary sector posted the worst performance.
  • Best Day YTD (In Points & Percent) – January 29th, an otherwise bright spot in a rather tough month.
  • Worst Day YTD (In Points & Percent) – June 24th, when the UK votes for Brexit.
  • New Highs – the DJIA posted 26 new highs in 2016, including two separate streaks of 7 straight records in July and December.

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

Year in Review: 2016 Asset Class Performance

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Jason Giordano

Director, Fixed Income, Product Management

S&P Dow Jones Indices

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The high-yield corporate bond segment, as measured by the S&P U.S. High Yield Corporate Bond Index, was the top-performing asset class for 2016, posting a total return of 17.2%.  Despite a rather tumultuous first quarter, 2016 finished with a clear “risk-on” sentiment as evidenced by the asset classes that topped the list.

On Feb. 11, 2016, it looked like quite the opposite, as high-yield bonds were down over 4%, and U.S. equities (S&P 500®), REITs (Dow Jones U.S. Select REIT Index), and commodities (S&P GSCI) were down 11%, 12%, and 13%, respectively, to start the year.  Then, as if lifted by the price of oil bouncing off its bottom, higher-risk asset classes all entered positive teritory by the end of April 2016.  The second quarter ended with some increased volatility, as markets reacted to (and then quickly moved on from) the surprise Brexit referendum that was announced on June 24, 2016.  A brief flight to quality increased demand for U.S. Treasuries (S&P U.S. Treasury Bond Index), municipals (S&P Municipal Bond Index), and investment-grade corporates (S&P U.S. Investment Grade Corporate Bond Index), and U.S. equities briefly dipped back into the red.

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Excluding commodities, the third quarter saw relativley low volatility.  Positive economic results and strong earnings from higher beta sectors propelled equities, high-yield corporate bonds, and leveraged loans (S&P/LSTA U.S. Leveraged Loan 100 Index).  The fourth quarter largely hinged on market participant sentiment leading up to and then reacting to the unexpected result of the U.S. presidential election.  Post-election, a focus on potential inflationary conditions and increased interest rates put upward pressure on bond yields.  Market participants ended 2016 favoring higher risk asset classes such as equities (S&P 500), commodities (S&P GSCI), and REITs (Dow Jones U.S. Select REIT Index).

Exhibits 2 and 3 show the total return performance of the major asset classes, taking into account their respective volatility.  In Exhibit 2, the column on the left ranks the major asset classes in terms of total return for 2016.  The column on the right re-ranks the asset classes by risk-adjusted returns, or Sharpe ratio, based on volatility (i.e., daily standard deviation throughout 2016).  The Sharpe ratio is used to compare investment options in a manner that shows total return per unit of risk.  Perhaps most surprisingly, leveraged loans (S&P/LSTA U.S. Leveraged Loan 100 Index) jumped to the top with a Sharpe ratio of 6.4, helped by extremely low volatility for the asset class.  Investment-grade corporate bonds also benefitted from relatively low volatility moving to the top-three performing asset classes on a risk-adjusted basis.  Not surprisingly, commodities (S&P GSCI) experienced the greatest amount of volatility (standard deviation of 23.8%) and fell out of the top-three on a risk-adjusted basis.

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

Most Major Islamic Indices Lag Conventional Benchmarks in 2016 as Strong Q4 Financials Sector Gains Detract From Performance

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Michael Orzano

Senior Director, Global Equity Indices

S&P Dow Jones Indices

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Most of S&P Dow Jones Indices’ Shariah-compliant benchmarks lagged their conventional counterparts for the year, as the financials sector—which is largely absent from Islamic indices—outperformed, and health care—which tends to be overweight in Islamic Indices—was the worst-performing sector globally.

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The S&P Global BMI Shariah and Dow Jones Islamic Market World finished the year up 4.2% and 3.8%, respectively, lagging their conventional counterparts by approximately 2% each.  Meanwhile, in the U.S., the S&P 500® Shariah gained 6.3% in 2016, underperforming the conventional S&P 500 by 320 bps.  The Dow Jones Islamic Market (DJIM) Europe Index and DJIM Asia/Pacific Index performed relatively close to their conventional counterparts.

U.S. Equities Lead All Major Regions for the Year
U.S. equity markets led all major regions for the year, driven by enthusiasm following the U.S. presidential election in November.  Emerging markets experienced declines in the fourth quarter, as prospects for higher U.S. interest rates and concerns about increased protectionism weighed on emerging market currencies and equities.  Despite weakness late in the year, the DJIM World Emerging Markets Index finished 2016 up 8.5%.  Europe was the only major region to close the year in the red, as uncertainty over BREXIT and continued economic weakness contributed to declining equity markets.

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MENA Equities Close 2016 Strong, Reversing Losses From Earlier in the Year
After declining nearly 8% through the end of September, the S&P Pan Arab Composite gained 12.6% in the fourth quarter, closing the year up 3.7%.  The S&P Pan Arab Composite Shariah gained an even stronger 16.5% in the fourth quarter, outperforming the conventional S&P Pan Arab Composite by nearly 3% in 2016 due to the S&P Pan Arab Composite Shariah’s greater exposure to Saudi Arabia.

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

A New Metric for Smart Beta: The Cost-Adjusted Factor Efficiency Ratio

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Daniel Ung

Director

Global Research & Design

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With an increasing number of smart beta strategies that track the same factor in the marketplace, it is more important than ever to understand the underlying drivers of risk and return of these strategies, which can vary greatly.  This is because the underlying portfolio construction of these strategies determines risk and return and, ultimately, the factors to which a portfolio is exposed.  Portfolio construction also determines how investable a strategy is, and this is often manifested through both financial and non-financial costs.  For example, consider two strategies that are all but identical except their rebalance frequency.  The strategy that rebalances more frequently may have a higher factor exposure, but it is also likely to rack up higher transaction costs.  For this reason, if having the maximum possible factor exposure is one of the portfolio objectives, then looking at factor exposure via a risk model may be useful in understanding how much risk exposure you obtain from a strategy—but this should be seen in the context of how much cost is incurred in the process of achieving that exposure.

To that end, we have come up with the cost-adjusted factor efficiency ratio (ca-FER), which seeks to address this trade-off.  This new metric is built on Hunstad and Deskahyer’s[1] factor efficiency ratio (FER), and it may be used in conjunction with other criteria that are already at the disposal of market participants to judge smart beta portfolios.

DOES MORE CONCENTRATION ALWAYS MEAN HIGHER FACTOR EXPOSURE?

Moving away from the benchmark is necessary, but portfolio concentration alone may not yield exposure to the desired factor, in terms of the percentage of active risk taken on a total basis.  Exhibit 1 indicates how the level of FER in relation to the momentum factor, portfolio turnover, and amount of risk derived from non-momentum common factors changed for portfolios with a varying number of stocks.  All these stylized portfolios have the same aim: to maximize the amount of momentum exposure as far as possible by conducting optimizations via the Northfield U.S. Fundamental Equity Risk Model.

As can be expected, when we move away from the benchmark, the level of momentum exposure initially increases with fewer stocks in the portfolio, and this comes with a higher portfolio turnover rate.  Meanwhile, active risk derived from exposure to other common factors (excluding momentum and industry risks) also gradually rises with portfolio concentration and eventually overtakes the amount of risk derived from momentum, which is our targeted exposure.

Consequently, “high conviction” concentrated portfolios may experience a double whammy effect.  If they are too concentrated, they may experience falling efficiency to the targeted factor, and they may rack up higher portfolio turnover as well.

For more details, see our research paper Smart Beta Efficiency Versus Investability.

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[1]   Hunstad M. and Dekhayser J. (2015), Evaluating the Efficiency of “Smart Beta” Indexes, The Journal of Index Investing, Summer 2015, Vol. 6, No. 1: pp. 111-121.

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