IN THIS LIST

Distinguishing Style From Pure Style

Constructing a Systematic Asset Allocation Strategy: The S&P Dynamic Tactical Allocation Index

A Glimpse of the Future: India's Potential in Passive Investing

A Performance Analysis of Variable Annuities With Risk Control

The Value of Research: Skill, Capacity, and Opportunity

Distinguishing Style From Pure Style

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Phillip Brzenk

Managing Director, Global Head of Multi-Asset Indices

S&P Dow Jones Indices

EXECUTIVE SUMMARY

  • The first-generation S&P Style Indices cover broad market segments, grouped into value and growth categories using style metrics commonly used in the investment community. This makes the indices relevant benchmarks for evaluating the skill of active Director managers, as well as making them suitable for those seeking a traditional “buy-and-hold” index-linked investment implementation with a tilt toward a particular style.
  • In contrast, the S&P Pure Style Indices have a stricter definition of value and growth style factors, leading each to have concentrated exposures.  Unlike the standard style indices, there are no overlapping securities between pure growth and pure value, potentially presenting them as better candidates for market participants looking to have precise tools in their investment process.
  • Driven by methodological differences, the indices have distinct risk/return characteristics and behave differently in different style cycles. Over the long-term investment horizon, the pure style indices have exhibited greater returns and volatility, lower cross correlations, and wider return spreads than the standard style indices.

INTRODUCTION

Launched in 1992, the first-generation S&P U.S. Style Indices brought broad style benchmarks for large-, mid-, and small-cap equities.  The indices group the investment universe into value and growth categories, based on relevant fundamental ratios for each style.  Certain securities may exhibit both growth and value characteristics; in this scenario, the company’s market capitalization is distributed between growth and value.

As a result, there are overlapping securities that fall into both growth and value indices.  Our analysis shows that over the past 10 years, on average, 166 securities in the S&P 500®, 131 securities in the S&P Midcap 400®, and 188 securities in the S&P SmallCap 600® fell into both the growth and value indices (see Exhibit 1).

Hence, roughly one-third of each size segment exhibits neither strong growth nor value characteristics.  Therefore, even though traditional style indices serve as investment universes and define the broad opportunity set for style equity managers, the overlapping nature of the indices may not appeal to market participants that desire more precise and focused measurements tools.

In 2005, S&P Dow Jones Indices introduced a second generation of style indices, the S&P Pure Style Indices, which require higher style scores for inclusion, resulting in clearer differentiation between growth and value.  The pure style indices include only securities that exhibit either pure growth or pure value characteristics.  Due to this, there are no overlapping securities between the pure style indices (see Exhibit 2).

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Constructing a Systematic Asset Allocation Strategy: The S&P Dynamic Tactical Allocation Index

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Phillip Brzenk

Managing Director, Global Head of Multi-Asset Indices

S&P Dow Jones Indices

SUMMARY

A typical long-term investor may seek exposure to riskier asset classes in their portfolios with the hopes of higher returns and better outcomes.  While the long-term historical returns for higher risk asset classes (such as equities, real estate, and commodities) have been higher relative to safer assets (like short-term U.S. Treasuries), losses can be substantial in downturns.  In times of distress, market participants may tactically allocate to safe haven investments, such as cash or government bonds.Nevertheless, knowing when to be fully “risk on” and when to move to safety is not an easy undertaking.

The capital asset pricing model (CAPM) assumes that investors are rational and risk averse.  However, in reality, behavior biases affect investor decision-making.  In fact, research has shown that when investor performance lags the market, it is often attributable to these biases (Elan, 2010 and Feldman, 2011).  

Behavioral biases, such as loss aversion, overconfidence, anchoring, or impulse, can lead to ill-timed or ill-advised investment decisions, resulting in less desirable outcomes (Kahneman and Ripe, 1998 and Pompian, 2018).  Investors can be hardwired to want to take action in times of volatility, whether warranted or not.  Although it can be challenging to overcome these behavioral tendencies, a systematic and dynamic allocation approach to control portfolio volatility can help prevent an unnecessary “anxious exit” from the market.

In this paper, we introduce the S&P Dynamic Tactical Allocation Index (DTAQ), which uses a systematic approach to asset allocation by incorporating dynamic and tactical investment strategies into the index design.  We first review the portfolio construction methodology, providing empirically driven rationale for the asset class building blocks and overall ruleset.  In part two of the paper, we review the historical index performance.  We compare the strategy with hypothetical static allocation versions and the classic 60/40 equity/bond portfolio.

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A Glimpse of the Future: India's Potential in Passive Investing

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Akash Jain

Director, Global Research & Design

S&P Dow Jones Indices

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Anu R. Ganti

U.S. Head of Index Investment Strategy

S&P Dow Jones Indices

EXECUTIVE SUMMARY

Fifty years ago, there were no index funds; all assets were managed actively. The subsequent shift of assets from active to passive management in U.S. and European markets may count as one of the most important developments in modern financial history. Our intent in this paper is to explore how and why this transformation took place in the U.S., why a similar transformation is beginning in India, and how India can look to the U.S. as an example of passive investing’s future growth potential.

The rise of passive management in the U.S. and Europe was the consequence of active performance shortfalls.2 In India, we observe the same shortfalls coupled with unique local factors, which can be attributed to three sources: cost, increased regulatory oversight and government initiatives, and the skewness of stock returns.

At the end of March 2018, the size of the Indian mutual fund industry was INR 21.36 trillion (approximately USD 300 billion), of which about 3.8% of assets were managed passively (see Exhibit 1).3 At this passive AUM share, a 100 bps cost differential (between active and passive) results in annual savings of INR 8 billion (approximately USD 115 million) for Indian investors and asset owners.

THE RISE OF PASSIVE MANAGEMENT IN THE U.S. AND ITS EVOLUTION IN INDIA

The U.S. has witnessed a significant growth in passive investing due to headwinds for active management in the following areas: cost, the professionalization of investment management, market efficiency, and the skewness of returns.4

Underperformance by active managers is not a new phenomenon and has been documented as early as 1932 by Alfred Cowles. It still holds true, as seen in the S&P Indices Versus Active® (SPIVA® ) U.S. Mid-Year 2018 Scorecard results (see Exhibit 2). S&P Dow Jones Indices has been the de facto scorekeeper of the ongoing active versus passive debate since the first publication of the SPIVA U.S. Scorecard in 2002. Over the years, we have expanded the scorecard’s coverage to Australia, Canada, Europe, India, Japan, Latin America, and South Africa. The results have been almost uniformly discouraging for the advocates of active management.

The evidence, over many years, is clear: a large proportion of active funds underperform their respective benchmarks over different time horizons. This is not unusual—in fact, over the history of the global SPIVA database, underperformance is far more common than outperformance.

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A Performance Analysis of Variable Annuities With Risk Control

EXECUTIVE SUMMARY

  • A variable annuity is a tax-deferred retirement vehicle with account values linked to the performance of underlying investment options, typically mutual funds.
  • A variable annuity with risk control framework has the added feature of providing caps and floors to the investment performance, which in turn is linked to the performance of the underlying investment options, typically a price index.
  • We construct hypothetical portfolios that allocate between a variable annuity with a risk control mechanism and a blended portfolio of stocks and bonds. Historical performance for the hypothetical portfolios with allocation to products with a risk control feature showed better downside protection than a stock portfolio or a traditional 60/40 stock/bond portfolio in some scenarios.

INTRODUCTION OF VARIABLE ANNUITIES WITH RISK CONTROL

A variable annuity is a tax-deferred retirement vehicle with account values linked to the performance of the investment options chosen by the market participant. The investment options for a variable annuity are typically mutual funds that invest in stocks, bonds, money market instruments, or some combination of the three.

A variable annuity that uses a risk control framework has the added feature of providing caps and floors to investment performance that are linked to the performance of the underlying investment options. If the underlying index delivers returns greater than the cap level or lower than the floor level, market participants will receive guaranteed payments at the cap or floor level, respectively. Therefore, variable annuities with risk control offer downside protection to investors at the expense of forgoing a degree of upside return. They offer market participants better visibility and predictability on future cash flows from annuities by effectively incorporating risk management tools in investment products.

A variable annuity with risk control features shares the same concept as and similar structure to those of risk control indices. Risk control indices are designed to measure the performance of underlying equity or futuresbased indices at specified volatility levels. As a benchmark provider of risk control indices, S&P Dow Jones Indices finds it relevant and meaningful to investigate the impact of incorporating a risk control framework into investment products, such as variable annuities, in a portfolio context.

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The Value of Research: Skill, Capacity, and Opportunity

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Tim Edwards

Managing Director and Global Head of Index Investment Strategy

S&P Dow Jones Indices

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Craig Lazzara

Managing Director, Index Investment Strategy

S&P Dow Jones Indices

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Hamish Preston

Head of U.S. Equities

S&P Dow Jones Indices

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Anu R. Ganti

U.S. Head of Index Investment Strategy

S&P Dow Jones Indices

EXECUTIVE SUMMARY

How much should a portfolio manager be willing to pay for research?

The question is of importance to any manager, but has become particularly pertinent since newly imposed European rules require that the costs of investment research—previously offered by many investment banks as an in-kind consideration in return for brokerage business—be unbundled from trading.

Unfortunately, attempts to determine a fair value for research in the most general circumstances are doomed to fail. Even if we only consider direct recommendations to buy or sell certain securities, the value of such recommendations to a portfolio manager will vary according to the absolute size of positions taken in response. Instead, we provide a framework for estimating relative research values across markets and constituents, under certain stylized (but reasonable) assumptions.

Exhibit 1 provides a summary of our main result—comparing the putative value of recommendations in selected markets, expressed as a multiple of the equivalent measure applied to stock-based recommendations within the S&P 500® .

INTRODUCTION: THE IMPACT OF “UNBUNDLING” RESEARCH COSTS

The Markets in Financial Instruments Directive (MiFID) II is an updated version of a regulation that has been in force throughout the European Union (EU) since November 2007.1 The update came into effect on January 3, 2018, and seeks “to reform market structures, bring more transparency to the trading of financial instruments, and strengthen investor protection.”2

For our purposes, the relevant regulatory change is that execution costs and charges must be separated, or “unbundled,” from the cost of research, and that investment managers must either absorb research costs or explicitly pass them on to their clients under pre-agreed terms.3 Since investment managers were formerly allowed to pay for research by the allocation of client trading commissions, MiFID II has the potential to produce major changes in the economics of research sales.

While these rules are of most immediate concern to institutions operating in the EU, MiFID II has potential global implications: the updated directive applies to all firms that conduct business in Europe, and many expect the legislation to be extended to other regions.4,5

From a practical perspective, MiFID II requires managers to set research budgets and to decide where to spend them. Obviously, the size of a particular research budget will depend on idiosyncratic factors, such as a firm’s assets under management. But when it comes to allocating resources, the relative value of research is likely to be comparable—if I find one analyst’s recommendations to be worth double those of other analysts, it is reasonable to hypothesize that these recommendations would also prove to be twice as valuable to anyone else.

This paper argues that the relative value of research is driven by a combination of three things: the information content of the research, the dispersion within the market where recommendations are made and implemented, and the capacity of each market to allow for active positions of varying sizes. While we do not claim to offer a universally applicable framework for setting research budgets, we hope to offer a practical and useful way to think about the value of signals for markets of varying size, concentration, and risk levels.

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