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Where Can Smart Beta Take You? Our FA Forum Is Coming to an Internet Near You

Why Choosing Between Managers Requires a Two-Dimensional View - Part 1

Smart Beta on the Rise in India

Worst Crude Oil Start In History: Or Best Rebalance?

Using Indexing Tools for Risk Management — Sophisticated Strategies from Basic Building Blocks

Where Can Smart Beta Take You? Our FA Forum Is Coming to an Internet Near You

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Shaun Wurzbach

Managing Director, Head of Commercial Group (North America)

S&P Dow Jones Indices

I am excited about our Miami Financial Advisor Forum, “Where Can Smart Beta Take You?”  This educational event will occur at the Epic Hotel in Miami on Feb. 24, 2016.  For the first time, we will livestream this financial advisor forum.  We hope that by broadening access to this event, more of you will find it possible to partake.

As our title suggests, this FA Forum is geared toward smart beta or factor-based investing.  We divided our smart beta education and thought leadership into three areas of interest:  The Practitioners, the Gurus, and the Strategist.

The Practitioners: Four eminent financial advisors representing large, successful RIA and Wirehouse firms will discuss how they evaluate smart beta and implement it into client portfolios.

  • Combining smart beta with traditional indexing and the alpha that the advisor as a portfolio manager can generate at the asset-allocation level.
  • Different ideas for evaluating and incorporating smart beta into client portfolios to position for growth and opportunities.
  • Ways that smart beta can help to manage downside risk or balance risk across asset classes.

The Gurus: The future of smart beta from three of the pioneers who started it.  Tom Dorsey, co-founder of Dorsey, Wright & Associates, Jason Hsu, co-founder of Research Affiliates, and Ben Fulton, CEO of Elkhorn Investments, will tell us what to expect and where we are headed with smart beta.

  • Using smart beta and tactical approaches together and how factors are being combined in new index-based products.
  • How new smart beta ideas originate and the ways that these ideas are brought to market.
  • Applying fundamental weighting in indices across all asset classes.
  • The relevancy of newly indexed factors such as CAPEX to returns and risk.

The Strategist: Sam Stovall, Equity Strategist at S&P Capital IQ/SNL will share how smart beta works with some of his “7 Rules of Wall Street.”

  • The historic outperformance of strategies incorporating the S&P Dividend Aristocrats Series as a factor-based approach to growing dividends.
  • Using readily available smart beta index data to keep investment strategies relevant.
  • Use of low volatility in lieu of cap weighting as a defensive alternative.

I hope that you will join us for this forum—in person, or virtually.  It will be a unique opportunity to learn about strategies using smart beta, best practices for incorporating smart beta in portfolios, and where smart beta may take us in the future.

Livestreaming invitation

In-person invitation

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

Why Choosing Between Managers Requires a Two-Dimensional View - Part 1

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Raewyn Williams

Director of Research & After-Tax Solutions

Parametric™ Australasia

For large superannuation funds and other investors with institutional-sized portfolios, a common practice is to spread the allocation to a particular asset class among a number of managers within a “multi-manager” structure.  This provides the benefits of diversification not only across asset classes, but also within key allocations like Australian and global equities.  The aim of good manager selection is to construct an optimal style blend, noting that no one style is likely to perform well in all market conditions.

Manager research and selection is a specialist skill that requires a comparison of alternative managers across an array of attributes, especially their performance “track record.”  It is well accepted that past performance is no predictor of future results, so other attributes to be considered typically include each manager’s credentials, experience, fees, structures offered, technology, research pedigree, operational support, and trading efficiency.  Large superannuation funds will typically engage an asset consulting firm to assist them with manager research and may also subscribe to surveys and publications that report and rank manager performance.

Because so much attention is paid to managers’ performance track records, the way that performance is measured and compared by funds and advisors is important.  Yet, there is a vital piece of the picture missing, a concept that is continually overlooked when assessing managers’ performance: taxes.  Superannuation funds, like most investors, are subject to taxes on investment performance, and what really matters is “what members and investors eat” in the form of after-tax returns.  In an ideal world, it would be reasonable to assume that manager performance is, as standard practice, measured and compared on an after-tax basis.  Unfortunately, this assumption is wrong.

Consider two hypothetical international equity managers holding the same stock from the perspective of a taxable superannuation fund client with realized capital losses (see Exhibit 1).


In this scenario, a pre-tax focus tells the client that manager A is superior to manager B.  When faced with a reason to change the investor portfolio, the client is (in the absence of other differences) more likely to withdraw money from manager B than manager A, or terminate the mandate altogether.  Yet, viewing each manager’s performance through an after-tax lens shows that manager B has been more successful at building wealth for the superannuation fund client.

In part 2 of this article, we move from the hypothetical to an actual 10-year performance history of 198 U.S. managers.  We depict the “one-dimensional” view by plotting the pre-tax performance of these managers along a y-axis where seemingly “superior” managers rise to the top.  We then create a “two-dimensional” view by plotting these managers’ performance on an after-tax basis along an x-axis to show how truly revealing a two-dimensional view of manager performance can be.

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

Smart Beta on the Rise in India

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Utkarsh Agrawal

Associate Director, Global Research & Design

S&P Dow Jones Indices

Globally, passive investment products have amassed significant assets. According to ETFGI, the global assets parked in ETFs and ETPs stood at USD 2.971 trillion at the end of Q2 2015, surpassing the level of global hedge fund assets. The introduction of smart beta ETFs and ETPs has made it possible to gain exposure to certain risk factors through a passive route based on indices. An inherent advantage of the use of indices to incorporate risk factors, apart from the lower cost and tax efficiency, is transparency. According to ETFGI, as of October 2015, globally, smart beta equity ETFs and ETPs had assets of USD 399 billion. The U.S. and Europe have been at the forefront of passive smart beta adoption, with the Asia-Pacific region swiftly catching up on the smart beta wave. Within the Asia-Pacific region, India currently has one smart beta product based on dividends.

A factor-based portfolio allocation strategy aims to offer diversification benefits, as individual factors have generally low correlation with each other. These factors aim to help explain the sources of portfolio returns. Asia Index Private Limited, a joint-venture between S&P Dow Jones Indices and BSE, recently launched a suite of factor indices for the Indian equity market, designed to individually capture the low-volatility, momentum, quality, and value factors. These four factors are grounded in academic literature and have empirically shown their own risk premia. Let us take a quick look at the performance of these factor indices. Exhibit 1 shows the cumulative relative performance of these indices with respect to the S&P BSE SENSEX. Each factor index noted its own cycle over the past 10 years ending Nov. 30, 2015. From Exhibit 2, we can note that over the same 10-year period, the S&P BSE Momentum Index and the S&P BSE Enhanced Value Index had the lowest correlation of monthly returns, while the S&P BSE Low Volatility Index and the S&P BSE Quality Index had the highest correlation of monthly returns.

Exhibit 1: Cumulative Relative Returns 

Smart Beta 1

Source: S&P Dow Jones Indices LLC. Data from Nov. 30, 2005, to Nov. 30, 2015. Past performance is no guarantee of future results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. The S&P BSE Momentum Index, S&P BSE Enhanced Value Index, S&P BSE Low Volatility Index, and S&P BSE Quality Index were launched on Dec. 3, 2015.

Smart Beta 2

Source: S&P Dow Jones Indices LLC. Data from Nov. 30, 2005, to Nov. 30, 2015. Past performance is no guarantee of future results. Table is provided for illustrative purposes and reflects hypothetical historical performance. The S&P BSE Momentum Index, S&P BSE Enhanced Value Index, S&P BSE Low Volatility Index, and S&P BSE Quality Index were launched on Dec. 3, 2015. 

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

Worst Crude Oil Start In History: Or Best Rebalance?

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Jodie Gunzberg

Former Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

In the first 5 days of 2016, the S&P GSCI Crude Oil Total Return lost 10.5%, making it the worst start for oil in history. This oil mess has spilled into other commodities, driving the 3rd worst overall commodity start in history since 1970, losing 5.5% in 5 days. It is the worst start in almost a decade when the S&P GSCI Total return lost 6.4% in the first 5 days of 2007, and that was the worst start since 1975, when the index began with a 7.4% loss.

Energy is now down 8.8% driven by double digit losses in crude oil (-10.5%) and unleaded gasoline (-11.3%). If it weren’t for the cold weather supporting natural gas (+5.8%,) the whole sector might be down double digits. It seems the middle east tensions may have driven the likelihood for a supply increase rather than disruption, but the focus has shifted to the dollar strength and Chinese demand weakness.

The slowing Chinese demand and currency weakness are problematic for all commodities, not just energy. Already in 2016, there are 17 losers of 24 commodities with 4 of 5 sectors down. All five constituents in the Industrial Metals (-4.0%) are getting hammered with the S&P GSCI Lead Total Return down 9.9%, although energy is still the worst of the sectors.

Many of today’s reports pointed out that oil hit a new 12-year low, but the pace at which the price is falling is alarming. Now the S&P GSCI Crude Oil (Spot) level is the lowest since Feb 2004 and the price would need to be cut in almost in half to lose another multi-year leg that would put oil down to the bottom seen in Nov 2001. That’s not bad news.

The concern is for futures investors that need to pay rolling costs.  The S&P GSCI Crude Oil Excess Return that includes rolling costs is down far past a 2004 low, reaching its lowest since Feb 1999, and is on the verge of another multi-year loss. If the S&P GSCI Excess Return loses just another 5.5%, it will shed another 5 years of gains. 

Source: S&P Dow Jones Indices
Source: S&P Dow Jones Indices

This is happening at the most important time in the year for the indices, precisely at the rebalance. Not only is the timing important but (WTI) Crude Oil is taking over Brent Crude as the biggest index constituent in 2016. Maybe there is a silver lining that index investors are rebalancing back to crude with a 10% discount from the start of 2016. It is the “best buy” the index has ever seen at its annual rebalance based on the worst start for crude ever.

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

Using Indexing Tools for Risk Management — Sophisticated Strategies from Basic Building Blocks

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Jerry Miccolis

Principal and Chief Investment Officer

Giralda Advisors

Advisors today share a problem new to the careers of all but the eldest of us. As I discussed in a recent webinar, at Giralda Advisors, we call it the Portfolio Problem — unique in the last 30 years and arguably the most significant issue facing financial planning professionals over the next several years, if not decades.

The Portfolio Problem arises from these facts:

  • Most investors need a sizeable allocation to equities in their portfolios
    • Equities are the primary driver to help them achieve their long-term financial goals and stay ahead of inflation
    • However, equities are volatile and subject to significant drawdowns
  • Non-equity asset classes, a key purpose of which is to buffer the risk of equities, have become problematic
    • Fixed income investments, in particular, are poised for historically poor returns for the next several years, as their 30-year bull run fueled by declining interest rates is coming to an end — this is what makes the Portfolio Problem unique in the last three decades
    • Attempts to enhance fixed income returns introduce their own problems — increased risk and increased correlation with equities — that compromise the mission of this asset class
  • Diversification itself does not always protect the portfolio from equity risk
    • Contagion among asset classes, which occurs in times of extreme market stress, is immune to diversification
    • Even in the best of environments, portfolio risk mitigation through diversification is not guaranteed

So, how does a financial advisor solve the Portfolio Problem? We believe the answer may lie in an approach we call risk-managed investing (RMI). RMI attempts to explicitly mitigate equity risk at its source — directly within the equity investment itself, via dampening volatility and/or limiting downside potential. Let us illustrate by example how this can be done.

The two primary risks facing equity investors include recurring bear markets and sudden, severe market crashes. An effective RMI strategy attempts to address both of these risks.

Our RMI approach seeks to tackle bear market risk through a momentum-based sector rotation strategy. After detailed modeling and rigorous testing with basic industry sector indexes, we developed a strategy that provides buy and sell signals with the goal of exiting early from sectors that lead market declines. We execute the strategy with highly liquid industry sector ETFs. An illustration of the sector activity within our Sector Dynamics RMI strategy is shown in the graph below.


We address market crash risk with an RMI strategy that incorporates a custom-designed suite of tail risk hedges. These hedges are delivered via swaps whose value is derived from proprietary volatility-based indexes. The idea is to capture and monetize the spikes in volatility that typically accompany sharp equity market declines and to do so very cost-effectively. Several of these indexes are based on signaled exposure to VIX, itself a very popular volatility-based index.

We benchmark our RMI strategies against relevant indexes. Three in particular developed by S&P/CBOE that are very well suited to RMI are:

  • PPUT — an index of the S&P 500 and a rolling put
  • CLL — an index of the S&P 500 and a rolling collar
  • VXTH — an index of the S&P 500 and a VIX-based tail risk hedge

Indexing has played an important role in our RMI efforts, from strategy development, to product construction, to benchmarking. By using accessible indexing tools, a properly implemented RMI strategy can provide a sophisticated, innovative approach to mitigating downside portfolio risk — thereby elegantly solving the Portfolio Problem.

This material is for informational purposes only. Nothing in this material is intended to constitute legal, tax, or investment advice. Investing involves risk including potential loss of principal.
The views and opinions of any contributor not an employee of S&P Dow Jones Indices are his/her own and do not necessarily represent the views or opinions of S&P Dow Jones Indices or any of its affiliates.  Information from third party contributors is presented as provided and has not been edited.  S&P Dow Jones Indices LLC and its affiliates make no representations or warranties of any kind, express or implied, regarding the completeness, accuracy, reliability, suitability or availability of such information, including any products and services described herein, for any purpose.

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