In This List

The VIX Index and Volatility-Based Global Indexes and Trading Instruments

ETF Transactions by U.S. Insurers in Q1 2020

How Smart Beta Strategies Work in the Australian Market

ETFs in Insurance General Accounts – 2020

The S&P Composite 1500®: An Efficient Measure of the U.S. Equity Market

The VIX Index and Volatility-Based Global Indexes and Trading Instruments

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Berlinda Liu

Director, Global Research & Design

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Matt Moran

Vice President of Business Development, Chicago Board Options Exchange (Cboe)

The Cboe Volatility Index® (VIX® Index) measures the market’s expectation of future volatility conveyed by S&P 500 Index option prices. The VIX is recognized as a premier gauge of expected US equity market volatility. The 2000–09 decade experienced two deep bear markets for equities that saw numerous short-term periods of high levels of investor uncertainty. Most investors recall how during the financial crisis of 2008–2009, the correlations between equities rose globally and traditional diversification goals became difficult to achieve. Exchange-listed VIX futures were launched in 2004, and VIX options were launched in 2006. During the 2008–09 financial crisis, VIX futures and VIX options experienced tremendous growth, as interest in and use of such index-based products as exchange-traded notes and exchange-traded funds grew. These products have become widely used in investors’ strategies ranging from trading tactical views on volatility to incorporating volatility trades and hedges in risk management and multiasset strategies.

This study addresses several questions investors have asked related to the VIX Index, volatility-based trading products, and the use of VIX futures in portfolio construction. These questions include the following:

  1. What does the VIX Index measure, and what does a VIX level signify?
  2. What are some indexes that measure expected volatility of European or Asian stock indexes?
  3. How do features such as convexity and negative correlation make the VIX an intriguing investment gauge?
  4. Is the VIX Index tradable, and if not, why?
  5. What tradable volatility-based futures and options products are available?
  6. How do contango and backwardation affect the returns of VIX futures-based strategies?
  7. What volatility benchmark indexes are available, and what is their impact when added to S&P 500 portfolios?

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ETF Transactions by U.S. Insurers in Q1 2020

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Raghu Ramachandran

Head of Insurance Asset Channel

INTRODUCTION

In May 2020, we published our annual study of ETF usage by U.S. insurance companies. The data for that analysis is only available annually. However, because of the market volatility in the first quarter of 2020, we wanted to analyze the use of ETFs by U.S. insurance companies prior to the next annual analysis. While holdings data is not available on a quarterly basis, we were able to analyze ETF transactions. In Q1 2020, U.S. insurance companies increased their ETF usage by USD 4.1 billion, as well as the number of transactions.

ETF TRADES

In the first quarter of 2020, insurance companies traded USD 24.6 billion in ETFs (see Exhibit 1).  This amount is roughly on scale with the total holdings of USD 31.2 billion as of year-end 2019.   

Exhibit 1

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How Smart Beta Strategies Work in the Australian Market

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Priscilla Luk

Managing Director, Global Research & Design, APAC

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Liyu Zeng

Director, Global Research & Design

EXECUTIVE SUMMARY

With increasing interest in smart beta strategies in the Australian equity market, we examined the effectiveness of six well-known risk factors, size, value, low volatility, momentum, quality, and dividends, in the Australian equity market from Dec. 31, 2004, to May 29, 2020.

  • Quintile analysis showed that low volatility, high momentum, and high quality delivered the most persistent absolute and risk-adjusted return spreads, but small cap and value did not generate incremental return in the Australian market.
  • Among the Australian factor indices offered by S&P Dow Jones Indices (S&P DJI), the quality and momentum indices delivered the highest excess returns, while the low volatility and dividend indices had lower volatility than the S&P/ASX 200.
  • Our macro regime analysis showed that most factor portfolios in Australia were sensitive to local market cycles and investor sentiment regimes.
  • The distinct cyclicality of factor performance in Australia indicated its potential for implementation of active views on the local equity market.
research-how-smart-beta-strategies-work-in-the-australian-market-exhibit1

FACTOR-BASED INVESTING IN THE AUSTRALIAN EQUITY MARKET

Smart beta strategies have gained significant attention in the asset management industry, and the exchange-traded products (ETPs) tracking factor indices have experienced significant asset growth since the end of 2008. Factor-based strategies are a category of smart beta strategies that target specific risk factors.  They share some common characteristics with passive investing, such as rules-based construction, transparency, and cost-efficiency, and they also share features of active investing in that they aim to enhance return and reduce risk compared to market-cap-weighted indices.

Single-factor indices are constructed explicitly to capture a specific risk factor and exhibit distinct cyclicality in response to a changing market environment, which also makes them ideal tools for implementation of active views. 

In Australia, although the adoption of factor-based investing by local market participants is behind the U.S. and some Asian markets (like Japan), the growth of factor-based ETPs has accelerated in recent years, achieving 46% growth in net assets in the past 18 months in local currency terms as of Dec. 31, 2018, and accounting for 10.5% of the Australian ETF market. Dividend products still dominate the Australian factor-based ETP market, but we observed the proliferation in categories and the increasing demand for factor-based index-linked products within the Australian equity market.

Based on the performance contribution analysis for the S&P/ASX 200 portfolio, the Financials and Materials sectors contributed about 63.6% of the total performance of the portfolio for more than 15 years.  At a stock level, the top five large-cap contributors (BHP Group Ltd, Commonwealth Bank of Australia, Westpac Banking Corporation, CSL Limited, and Australia and New Zealand Banking Group Limited) together contributed approximately 49% of the total portfolio performance over the same period.  This suggests that sector or size bias might have  a significant impact on the excess return of factor portfolios in the Australian market.

In this paper, we examined the effectiveness of six well-known risk factors (size, value, low volatility, momentum, quality, and dividend) in the Australian equity market and the behavior of these factors under different market regimes.

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ETFs in Insurance General Accounts – 2020

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Raghu Ramachandran

Head of Insurance Asset Channel

INTRODUCTION

In our first report in 2015, we used historical trends to project that insurance companies would double their use of exchange-traded funds (ETFs) in five years. Now five years later, usage of ETFs in insurance general accounts has indeed doubled since 2015. In the one-year period ending Dec. 31, 2019, insurance companies increased their ETF assets under management (AUM) by 16% to reach USD 31.2 billion. We saw companies increase their use of Equity and Fixed Income ETFs. While the overall use of ETFs increased, we did observe some parts of the industry that had been active in using ETFs pull away. Although the use of Fixed Income ETFs increased, the use of Systematic Valuation (SV) declined.

OVERVIEW

As of year-end 2019, U.S. insurance companies had USD 31.2 billion invested in ETFs. This represents a tiny fraction of the USD 4.4 trillion of ETF AUM and an even smaller portion of the USD 6.7 trillion in admitted assets of U.S. insurance companies. Exhibit 1 shows the use of ETFs by U.S. insurance companies over the past 16 years.

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The S&P Composite 1500®: An Efficient Measure of the U.S. Equity Market

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Hamish Preston

Associate Director, U.S. Equity Indices

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Phillip Brzenk

Senior Director, Strategy Indices

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Aye Soe

Managing Director, Global Head of Product Management

EXECUTIVE SUMMARY

Launched in 1995, the S&P Composite 1500 (hereafter the "S&P 1500") serves as a benchmark indicator for U.S. equity market performance, aggregating price movements of S&P 500®, S&P MidCap 400®, and S&P SmallCap 600.

The S&P 1500 also increasingly serves as a basis for constructing portfolios designed to deliver a "market" return at lower cost than those active managers who offer to beat it. We shall examine the S&P 1500 from both perspectives, as well as examining its merits in comparison to popular alternatives. In particular, we observe that:

  • The sizeable representation of U.S. companies means tracking U.S. equity market performance may be relevant to investors, globally;
  • The S&P 1500 has outperformed the S&P 500, historically;
  • Incorporating smaller companies in a U.S. market benchmark provides a more holistic view of the U.S. economy (see Exhibit 7); and
  • Compared with other U.S. equity market indices, the S&P 1500 avoids relatively illiquid, lower priced, and lower quality stocks (see Exhibit 1).

MEASURING THE U.S. EQUITY MARKET

U.S. companies represented an average of 49.47% of the S&P Global BMI’s capitalization at each year-end between 1995 and 2019, more than five times the average weight of second-place Japan (9.39%). Given that U.S. companies also accounted for over 50% of the market capitalization in most global industries at the end of 2019, many investors may need to turn to the U.S. in order to obtain certain exposures.

The S&P 1500 is designed for investors seeking to replicate the performance of the U.S. equity market, or benchmark against a representative universe of tradable stocks. The S&P 1500 combines three widely followed indices—the S&P 500, S&P MidCap 400, and S&P SmallCap 600—in proportion to their free-float market capitalizations. Hence, the S&P 1500 uses the same inclusion criteria as its three component indices.

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