IN THIS LIST

ETFs in Insurance General Accounts – 2021

Fleeting Alpha Scorecard: Year-End 2020

Why the S&P 500 Matters to China

Approaches to Benchmarking Listed Infrastructure

Political Risk and Emerging Market Equities: Applications in an Index Framework

ETFs in Insurance General Accounts – 2021

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Raghu Ramachandran

Head of Insurance Asset Channel

After a chaotic start to the year, U.S. insurance companies added USD 4 billion to exchange-traded funds (ETFs) to their general account portfolios in 2020. By year-end 2020, U.S. insurers increased their ETF AUM by 18% from 2019. Life companies, in particular, returned to the market and purchased large amounts of ETFs. In spite of, or because of, the volatility in the bond market, insurance companies had strong flows into Fixed Income ETFs, adding USD 5 billon in 2020.

In our sixth annual study of ETF usage in U.S. insurance general accounts, for the first time we analyzed the trading of ETFs by insurance companies (see page 37) in addition to the holding analysis. In 2020, insurance companies traded USD 63 billion in ETFs, representing a 10% growth over 2019’s trade volume. On average, insurance companies traded twice as many ETFs during the year as they held at the beginning of the year. Certain categories have substantially higher trade ratios. We also noted interesting observations about the size of insurance company trades.

HOLDING ANALYSIS

Overview

As of year-end 2020, U.S. insurance companies invested USD 36.9 billion in ETFs. This represented only a tiny fraction of the USD 5.5 trillion in U.S. ETF AUM and an even smaller portion of the USD 7.2 trillion in invested assets of U.S. insurance companies. Exhibit 1 shows the use of ETFs by U.S. insurance companies over the past 17 years.

In 2020, ETF usage by insurance companies increased 18.4%; this is a slightly higher rate than the 16.0% increase in 2019. The growth rate has remained consistent since 2004, when insurance companies began investing in ETFs (see Exhibit 2). This growth rate implies a doubling of ETF AUM roughly every four to five years (see Exhibit 3).

In 2019, the number of ETF shares held by insurance companies declined for the first time in 12 years, but in 2020, the number of shares held increased by 8.5% (see Exhibit 4).

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Fleeting Alpha Scorecard: Year-End 2020

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Berlinda Liu

Director, Global Research & Design

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Gaurav Sinha

Managing Director, Head of Americas Global Research & Design

SUMMARY

The Fleeting Alpha Scorecard combines elements of the SPIVA® U.S. Scorecard and the Persistence Scorecard to show how outperforming mutual funds from one three-year period continue to perform thereafter. The former report compares actively managed funds against their passive benchmarks, while the latter compares funds against their peers.

For the Fleeting Alpha Scorecard, we first identify funds that beat their benchmarks, based on three-year annualized returns, net-of-fees. We then examine whether these funds continue to outperform during each of the next three one-year periods.

There was significant dispersion in the likelihood of funds outperforming by category, with the most notable split occuring between growth and value funds. For example, as of Dec. 31, 2017, 84 of the 261 large-cap growth funds had outperformed the S&P 500® Growth in the previous three years. Of those winners, 21 (or 25%) outperformed for the subsequent three years. But on the value side, while 78 out of 338 funds had outperformed the S&P 500® Value as of Dec. 31, 2017, only 1 of those winners managed to continue outperforming annually through 2020 (see Exhibit 1 and Report 1).

Fleeting Alpha Scorecard: Year-End 2020 - Exhibit 1

In 4 of the 18 domestic equity categories tracked, no funds managed to repeat their outperformance, and fewer than 10% did so in an additional four categories (see Report 1).

Echoing a point from the SPIVA U.S. Year-End 2020 Scorecard, prior to the evaluation of alpha persistence, few funds beat the benchmark for the initial three years (2015-2017). In 13 of the 18 domestic equity categories, fewer than 20% surpassed the benchmark, significantly reducing the original universe into the pool of "winners" for subsequent tracking.

International equity funds had slightly higher rates of outperformance in the initial period and were more stable in their alpha maintenance across categories and time. The conspicuous exception was emerging market funds where no active manager managed to repeat their positive alpha through 2020.

We take into consideration that cyclical market conditions can unduly influence a snapshot of the performance persistence figure. The figures in Report 2 are calculated by: 1) creating a version of Report 1 for each quarter between December 2011 and December 2020, and 2) taking simple averages of the persistence figures for each of the categories.

This analysis showed that the average outperformance persistence in each of the subsequent three years fell rapidly. Across all funds in the tracking universe, the average outperformance persistence by year was 33.8%, 13.7%, and 6.7%, respectively.

The growth/value split was visible in this longer timeframe as well. As Exhibit 2 shows, while the percentage of outperforming value funds was reasonably similar to their growth counterparts in year one, their alpha proved substantially less durable, suffering a harsher decline by year three.

Fleeting Alpha Scorecard: Year-End 2020 - Exhibit 1

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Why the S&P 500 Matters to China

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Tianyin Cheng

Senior Director, Strategy Indices

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Hamish Preston

Director, U.S. Equity Indices

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Jason Ye

Associate Director, Strategy Indices

EXECUTIVE SUMMARY

Chinese investors tend to have high exposure to domestic equities and low exposure to international equities.  This home-country bias is common among investors globally.  U.S. equities represented 45% of the global equity market, as of Dec. 31, 2020.  Underallocation to international equities, including U.S. equities, means Chinese investors may be foregoing potential diversification benefits.

In this paper, we:

  • Discuss the global investment opportunities for Chinese investors and the potential results of investing globally;
  • Introduce the S&P 500 and explain how it is constructed;
  • Highlight how the S&P 500 could affect Chinese investors’ ability to diversify domestic sector biases, gain exposure to U.S. economic growth, and improve historical risk-adjusted returns; and
  • List different channels where Chinese investors may access global markets and review the Qualified Domestic Institutional Investor (QDII) program.

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Approaches to Benchmarking Listed Infrastructure

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Tianyin Cheng

Senior Director, Strategy Indices

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Claire Yi

Analyst, Strategy Indices

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Izzy Wang

Analyst, Strategy Indices

Investing in infrastructure has become popular among institutional and private investors in recent years. Investors could be attracted to the potentially long-term, low-risk, and inflation-linked profile that can come with infrastructure assets, and they may find that it is an alternative asset class that could provide new sources of return and diversification of risk.

WHY CONSIDER INVESTING IN INFRASTRUCTURE?

Infrastructure assets provide essential services that are necessary for populations and economies to function, prosper, and grow.  They include a variety of assets divided into five general sectors: transportation (e.g., toll roads, airports, seaports, and rail); energy (e.g., gas and electricity transmission, distribution, and generation); water (e.g., pipelines and treatment plants); communications (e.g., broadcast, satellite, and cable); and social (e.g., hospitals, schools, and prisons).  Infrastructure assets operate in an environment of limited competition as a result of natural monopolies, government regulations, or concessions.  The stylized economic characteristics of this asset class include the following.

  • Relatively steady cash flows with a strong yield component: Infrastructure assets are generally long lived. Most companies have long-term regulatory contracts or concessions to operate the assets, which can provide a predictable return over time.  As a result, infrastructure assets have the potential to generate consistent, stable cash flow streams, usually with lower volatility than other traditional asset classes.
  • High barriers to entry: Due to significant economies of scale, infrastructure assets are often regulated in such a way that discourages competition. The high barriers to entry often result in a monopoly for existing owners and operators.
  • Inflation protection: Revenues from infrastructure assets are typically linked to inflation and are often supported by regulation. In certain instances, revenue increases linked to inflation are embedded in concession agreements, licenses, and regulatory frameworks.  In other cases, owners of infrastructure assets are able to pass inflation on to consumers via price increases, due to the essential nature of the assets and their inelastic demand.

Consequently, the infrastructure asset class may provide investors with a degree of protection from the business and economic cycles, as well as attractive income yields and an inflation hedge.  It could be expected to offer long-term, low-risk, non-correlated, inflation-protected, and acyclical returns.

It is also generally believed that infrastructure is, as an asset class, poised for strong growth.  As the global population continues to expand and standards of living around the world become higher, there is a vast demand for improved infrastructure.  This demand includes the refurbishment and replacement of existing infrastructure worldwide and new infrastructure development in emerging markets.

Financing public infrastructure has traditionally been the responsibility of the state.  However, fiscally constrained governments are increasingly turning to the private sector to provide funding for new projects.  As a result, the investment opportunities in this sector continue to grow.

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Political Risk and Emerging Market Equities: Applications in an Index Framework

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Laura Assis Iragorri

Analyst, Global Research & Design

S&P Dow Jones Indices

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Hector Huitzil Granados

Analyst, Global Equity Indices

INTRODUCTION

Political risk is widely presumed to affect emerging market equities. However, its impact has historically been difficult to assess due to the lack of quantifiable, systematic, and standardized political risk metrics.

The growing popularity of alternative data derived from natural language processing and sentiment analysis of global news media has opened new opportunities in the political risk space, including novel methods of devising systematic investment and asset allocation frameworks that are uniquely informed by a new generation of political risk indicators.

To take advantage of this development, S&P Dow Jones Indices has collaborated with GeoQuant, an AI-driven political risk data firm, to devise a best-in-class Emerging Markets Political Risk-Tilted Concept Index (hereafter the “Political Risk-Tilted Concept Index” or "Concept Index").

The Concept Index takes the S&P Emerging BMI as its starting point and rebalances country allocations monthly based on GeoQuant's custom "Macro-Government Political Risk Indicator," yielding the Political Risk-Tilted Concept Index by overweighting (underweighting) countries with relatively low (high) political risk.

We find that systematically incorporating political risk as a factor into emerging market equity allocation decisions can potentially drive outperformance relative to the benchmark S&P Emerging BMI. Outperformance is largely attributable to reduced overall volatility and greater insulation from downside risk.

Over a 2013-2020 back-test period, the Concept Index outperformed the S&P Emerging BMI using a standard set of back-test parameters. Specifically, the Concept Index yielded higher return/risk ratios over three-and five-year horizons, and on a cumulative basis over the full back-tested period, with an annualized excess return of 1.31% relative to its benchmark. It also demonstrated a consistently lower level of volatility, a relatively low annualized tracking error of 2.03%, and a lower monthly average turnover than its benchmark. On a monthly basis, the back-tested Concept Index outperformed the S&P Emerging BMI in the majority of all months, and in a larger majority of down months in which benchmark returns decreased. The back-test also outperformed the S&P Emerging BMI over 2020 despite well-known challenges in forecasting equity market performance during the COVID-19 pandemic.

The Political Risk-Tilted Concept Index is the first of its kind (to the best of our knowledge) and offers novel opportunities to leverage S&P Dow Jones Indices and GeoQuant data to inform emerging market equity allocation decisions.

MEASURING POLITICAL RISK: AN OVERVIEW

GeoQuant is a venture-backed, AI-driven political risk data firm that fuses political science and machine learning to systematically measure and predict political risks in real-time.

Well before COVID-19, the interplay of macro-economic policymaking and government (in)stability, and the lack of high-frequency data to measure these factors, made it notoriously difficult to assess the impact of political risk on equity prices, particularly in emerging markets. Technical advances in monitoring and predicting political risk were necessary.

To that end, GeoQuant has developed a best-in-class set of more than 20 political risk indicators for modeling and understanding the impact of political risk on markets. These indicators enable data-driven and systematic asset allocation in response to measurable, real-time variation in political risk.

Exhibit 1 provides a snapshot of GeoQuant’s core set of risk indicators, which collectively comprise GeoQuant’s "Fundamental Risk Model." The indicators measure the full spectrum of risks that are likely to affect commerce, trading, investment decisions, and intergovernmental relations. All indicators are generated by real-time natural language processing of traditional news media using proprietary algorithms for text-based sentiment analysis, as well as synchronous inputs and review by a team of PhD political economists.

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